THE ART OF DIGITAL JUJUTSUIn a nutshell, the Digital Jujutsu is all about disrupting digitally...

Mohammed HashimPractice ManagerCognizant Technology Solutions [email protected]

THE ART OF DIGITAL JUJUTSU

2016 EMC Proven Professional Knowledge Sharing 2

Table of Contents

1. Overview ....................................................................................................................................................... 3

1.1. Trends of Leaders and Laggards ............................................................................................................... 4

2. Going Digital Stratagem ................................................................................................................................ 5

2.1. People Centric Business Quad .................................................................................................................. 7

2.2. Dynamic Platforms for Changing Waves ................................................................................................... 8

2.3. Codifying Platforms for SDx .................................................................................................................... 10

2.4. Cybernetic Applications .......................................................................................................................... 12

2.5. Analytics of Everything ........................................................................................................................... 15

3. Envisioning the Digital Enterprise ............................................................................................................... 17

3.1. Adoption Barriers & Enablers ................................................................................................................. 20

3.2. Digital Transformation Approach ........................................................................................................... 21

4. Steering to Being Digital .............................................................................................................................. 23

4.1. Digital Trust ............................................................................................................................................. 24

4.2. Design Thinking ....................................................................................................................................... 26

4.3. Data Democratization ............................................................................................................................. 28

5. Going Digital vs. Being Digital ...................................................................................................................... 30

6. Digital Disruptions Impact ........................................................................................................................... 31

7. Looking Beyond ........................................................................................................................................... 34

Appendix A: Research References ....................................................................................................................... 36

Appendix B: Future of Learning (A Digital Impact Case in Point) ......................................................................... 39

Appendix C: Rise of the Fourth Platform ............................................................................................................. 40

Appendix D: Fishing in the Enterprise Data Lakes................................................................................................ 41

Appendix E: Pivotal Big Data Analytics Platform .................................................................................................. 42

Appendix F: Reference Architecture for API Management.................................................................................. 43

Appendix G: IaC Integration Pipeline ................................................................................................................... 44

Appendix H: A Framework for Creativity & Innovation ....................................................................................... 45

Disclaimer: The views, processes or methodologies published in this article are those of the authors. They do not necessarily reflect Dell EMC’s views, processes or methodologies.

Dell, EMC and other trademarks are trademarks of Dell Inc. or its subsidiaries.


1. Overview

In this era of Digital economy, the battles of business competition are being tactically fought on newer turfs of the Third Platform

coupled with Cybernetic Applications, Codified Infrastructure, and Analytics of Everything. ‘Digital’ refers to the multidimensional

capability to dynamically connect businesses, data, devices, systems, people, and technology for continuously transforming business

outcomes and user experiences. It is hard to overstate the impact of digital in our lives. In less than a decade, it has affected nearly

everything we do daily in our social, financial, and personal spheres. As we turn towards a mobile-first in a digital-first world,

Information is the quick currency that funds business growth. As a result, the ideal Enterprise Information Architecture (EIA) is

undergoing multiple paradigm shifts from Technology-Centered to Service-Oriented to Digital-Driven powered by Real Time Business

Intelligence (RTBI) or Continuous Insights.

Enterprises need to integrate newer digital approaches with complex business operations, products, skills, customers, and IT

systems (including legacy and brownfield at times); even if they are performing well, meeting or exceeding current expectations. It is

literally the survival of being the most digital by both design and practice. The application of digital strategy, processes, tools, and

technology across end to end business service lines for Enterprise Information Management (EIM) would be the main constituents

for ‘Going Digital’. This is evident from the overriding success of digitally-savvy organizations which have been creating

unprecedented levels of innovative business value and redefining customer experience. Some of these which continue to be

disrupters and keep outpacing their sector peers include Airbnb, Amazon, Apple, Burberry, Etsy, Facebook, GE, Google, GoPro,

Macys, Netflix, Nike, Pandora, Salesforce, Samsung, Tesla, T-Mobile, Uber, Verizon, WhatsApp, Yelp, YouTube, and so on. Although

most of them are also early adopters, the strategic difference for ‘Being Digital’ is to constantly maintain the momentum and

willingness to revamp quickly, by shifting gears to adopt technology innovations and adapt to dynamic market trends. This can be

realized only when they embrace the wider organizational and cultural changes of the digital DNA, without dropping the humane

service approach of trust.

This paper discusses the business perspectives and technology blueprint for steering from ‘Going Digital’ to ‘Being Digital’ in order to

succeed in the digital economy. People-Centric strategy and elements of Dynamic platforms for navigating from Transactional to

Engagement to Experiential to Digitally Intuitive is covered here. The role of Cybernetic Applications, Infrastructure as Code (IaC),

and advanced analytics based on Internet of Everything (IoE) ecosystems is also touch on. This leads to the new digital expressway

which lifts the shutters for a data deluge beyond comprehension, and is widely and wildly referred as the Digital Beast. The myth

and mystery of taming this digital beast is also unraveled in this research. Analytics of Everything embedded in Enterprise Data Lakes

for realizing Continuous Business insights is studied in the milieu of Digital hyper connectivity. The crucial role of Digital artisans,

Data democratization, various drivers and barriers, business impact of digitization, and future of digital transformation is further

examined here. In a nutshell, the Digital Jujutsu is all about disrupting digitally without getting digitally disrupted and tumbling in

chaos.


1.1. Trends of Leaders and Laggards

According to the study by Capgemini Consulting and the MIT Center for Digital Business1, on average Digital leaders are 26%

more profitable than their industry competitors. They generate 9% more revenue through their employees and physical

assets. And they create more value, generating 12% higher market valuation rates.

According to McKinsey, companies that use big data analytics effectively exhibit productivity and profitability rates that are

5% to 6% higher than those of their peers2.

Gartner predicts that by 2020, 75% of businesses will be a digital business or will be preparing to become one3.

Consider one of the most trending – the Smart Wearables segment. Recent IDC Tracker report4

states a total of 21 million

wearable devices shipped last quarter, an increase of 198% from the same quarter last year.

Fifty-two percent of the Fortune 500 companies have merged, been acquired, have gone bankrupt, or fallen off the list since 20005.

This has been mainly due to the disruption of traditional industry models by digital models. The pace of change is so fierce that, as

business models converge, competitors simply pop up from nowhere. The undisputable reality is that digital has been and will

continue to disrupt our lives regardless of what it is possible to do here and now. Digital Darwinism is unkind to those who wait;

leading to the absence or presence of any transitory reluctance resulting in Digital Leaders or Digital Laggards, respectively. Hence, it

is paramount to smartly embrace digital before it’s too late.

All analysts and researchers have been stating the obvious many times over; every Industry will undergo a digital redesign to get on

the Digital bandwagon. However, would this be sufficient for generating practical insights compared to those already on the front

lines of major digital upheaval? Actually, there is no straightforward approach for dealing with the volatile nature of digital change.

Even the Leaders can become complacent or disoriented as change builds on change, leaving almost nothing certain. Yet, the worst

is to do nothing and ending up as Laggards or Failures.


2. Going Digital Stratagem

Although Digital is on everyone’s mind, there is a nerve-racking lack of strategic direction required for a long term successful

adoption and execution of Digital business blueprint that would serve as the line of attack. According to Forrester, only 27% of

today’s businesses have a coherent digital strategy that sets out how the firm will create customer value as a digital business6. Also,

it is time for companies to stop thinking about digital transformation and start acting on it7.

An ideal Digital stratagem should encompass four key tenets as outlined in Figure 1.

Figure 1: Tenets of Digital Stratagem

1. People-Centric Enterprise: Digital creates a hyper connected world with hyper connectivity in three fundamental

dimensions: people, information, and infrastructure. The people-centric paradigm is central to the business blueprint,

where organizations always turn towards people for innovative ways to engage and deliver value for business and society.

Here, the dynamic collaboration of employees, customers, and partners play an important role in operating as a digital

business. This calls for the twin mandate to internalize digital operations as well as externalize digital interactions. Only

when enterprises start operating as digital can they cater to the digital needs of their employees, customers, and partners.

The prerequisite is to really engage with people to understand their actual user experience during interactions across all the

touchpoints in a process lifecycle and identify spaces to eliminate redundancies, reform processes, and improve efficiencies

to maximize tangible value outputs (minor or major) at each stage.

Digital Stratagem

People Centric

Enterprise

Dynamic Platforms

Cybernetic Applications

Analytics of Everything


‘Going Digital’ revolves around organizations adopting a business strategy which is more ‘Innovation’-centric while ‘Being

Digital’ is more ‘People’-centric. Carving the Digital business as a start-up within the organization would be a good practice

for large enterprises, so that the radical shift does not affect their core business services in the short term while

transitioning towards Digital. The People-Centric Business Quad discussed in Chapter 2.1 covers this aspect in detail.

2. Dynamic Platforms: Digital Economy is metamorphosing into a sharing economy driven by platforms which are aligned to

industry domains and business functions. The platforms would be the backbone with services delivered in any XaaS

(Anything as a Service) model; predominantly in BPaaS, PaaS, or SaaS. The ideal platforms for this journey would be either

the Third Platform of SMAC (Social-Mobility-Analytics-Cloud) or futuristic Fourth platform (led by Ambient Computing. The

model vision is uncovered in Appendix C). The key elements of a Dynamic Platform are discussed in depth in Chapter 2.2.

3. Cybernetic Applications: These are Adaptive or Cognitive application models dynamically aligned to the business logic

interactions encompassing people, process operations, devices, and tools. The APIs here closely sync with the business

applications to create a more humane experience across channels. This is realized by tapping and processing the colossal

data trove, to become more intimate with the end users while meeting short-term requirements and more connected with

their supply chains and larger ecosystem to facilitate medium- to long-term requirements. Exposing an API with the right

safeguards into the cloud facilitates resources of an existing enterprise application to be available for newer and smarter

development. The architecture and role of Cybernetic applications is covered in Chapter 2.4.

4. Analytics of Everything8 represents the advanced analytics with IoE ecosystems. Consuming Data Lakes, it decentralizes

real-time BI to locally focused IoT analytics at gadgets, homes, vehicles, workplaces, industries, and so on. IoE will act as the

zesty catalyst for the expansion of digital transformation to all corners of the digital economy by bringing all the endpoints,

edge sites and user interfaces to a common platform. Chapter 2.5 explains more about this advanced form of analytics and

role of IoE. Appendix D illustrates a reference architecture and Appendix E shows a sample solution of Pivotal that supports

this.


2.1. People-Centric Business Quad

The Fourth Industrial Revolution will not only change what we do but also who we are. All the earlier revolutions were primarily

about improving efficiency and productivity and rationalizing costs in our daily activities. However, the Digital revolution – aka the

Fourth Industrial revolution – will, willfully or not, transform our works and shake our very identity as to privacy, ownership, diet and

nutrition, resource consumption, work-life balance, social interactions, relations, career and skills development, and so on. It is

already changing our individual self by influencing buying patterns, hobbies (literature, movies, music, plays, politics, religion, sports,

etc.), financial plans, health styles, group activities, and future formation. The list is infinite and bound only by our wild imagination.

People are at the epicenter of the digital economy, whether they are companies or consumers. Anything and everything can now be

enhanced with digital smart capabilities continuously increasing intrinsic value in this apparently ‘sharing’ economy. The People

Centric-Business Quad illustrated in Figure 2 depicts the A-B-C-D of attaining people centricity with the main objective and activities

at each phase.

Figure 2: A-B-C-D of People Centricity

A – Assess: What is Digital in the context of your customers, services, and operating markets? Who are your current and

possible competitors in this space? Which disruptors are you going to adopt?

B – Build: What capabilities do you currently have or should build to meet the digital goals? Build or bring the right people

skillsets, tools/technology and partners to cater to the blurring boundary. You would need Digital Artisans9 who exemplify

the digital DNA of Data Sciences required for the new era with multifaceted skills like Business Data Analysts, Data

Architects, and Data Visualizers.

C – Change: Change your Business process model, products, and services to embrace uncertainty as the new norm.

Introduce operational flexibility and process automations to create market differentiations.

D – Drive: How should you start your journey toward ultimately Being Digital? Drive data derived business insights to

simplify dynamic decision making across the organization through advanced analytics. Lead Data democratization and

promote innovations harvesting.


2.2. Dynamic Platforms for Changing Waves

In the Digital era, organizations are re-examining their business model, end-to-end process operations, people capabilities, tools,

and platforms based on digital capabilities. Moreover, digital technology continues to evolve at a rapid pace with each market player

positioning their solution primarily around their expertise or niche offerings. An ideal digital platform goes beyond just tools and

technology-based functionalities.

While the market is still nascent with an end-to-end solution for changing data waves, enterprises can start to leverage the Third

Platform (SMAC Stack) by building new systems of engagement that act as a front end to existing legacy and/or brownfield systems

of record. The key elements of a cutting-edge digital business platform are shown in Figure 3.

DIGITAL USER EXPERIENCE & COLLABORATION

ANALYTICS OF EVERYTHING

IN-M

EMO

RY

GR

ID

ENTERPRISE DATA LAKES

BIMODAL IT

APIs & INTEGRATION FABRIC

CYBERNETIC APPLICATIONS

CODIFIED INFRASTRUCTURE (SDI)

Figure 3: Digital Platform Elements

The dynamic platform elements for Digital business are:

1. Digital User Experience & Community Collaboration: This is the capability to capture data insight and deliver personalized

interactions across multiple channels, enabling customers to engage with companies in their service context. It also

features a collaboration medium for user community interactions across enterprise silos. This is fully realized by ‘Being

Digital’ discussed at length in Chapter 4 and its sub-chapters.

Google Micro-Moments study reveals that "Consumer Intent Is More Powerful than Demographics." This is very evident

from their research which shows that marketers who try to reach their audience solely on demographics risk missing more

than 70% of potential mobile shoppers. (Source: (Mobile search & video behavior analysis, Millward Brown Digital, U.S.,

January-June 2015)

2. Enterprise Data Lakes: These are a major advancement from existing EIA and EIM systems. It is technically an unlimited data

storage repository for all data types supported with complex computing and dynamic processing engines. It enables the


user community to refine, explore, and enrich information with flexible access to interactive business insights. A reference

enterprise data lake architecture is covered in Appendix D. This also supports the consolidation of transactional and

analytical data into one common in-memory structure and leverages real-time processing.

3. Analytics of Everything: This is the nerve center for digital business command and control realized by Predictive or

Prescriptive analytics powered by advanced process automation. Chapter 2.5 covers this element in detail.

4. In-memory Grid: This is the capability of super speed in-memory computing by keeping data in the random access memory

(RAM) of dedicated servers rather than complicated relational databases. It applies to complex event processing that

requires extensive access to data analytics, data mining, data warehousing, and big data applications.

5. APIs & Integration Fabric: APIs connect data transfer between people, applications, systems, and devices/machines across

the IoE landscape. It ensures the seamless flow of interactive smart sensors information, functional logic, and business

process integration across the other elements. The Integration Fabric is a combination of tools, accelerators, and built-in

migration capabilities that helps organizations define, implement, and manage their integrations faster in modular or mash-

up fashion.

6. Bimodal IT: This is the ability to operate and manage IT delivery in two distinct modes. The first one is focused on stability

and efficiency with sequential conventional approach. The second is an experimental and DevOps based, primarily focused

rapid application evolution and scale aligned to market dynamics.

7. Cybernetic Applications: These are Adaptive applications built on a Four-tier architecture suited for the Digital age. The

detailed application architecture and features are covered in Chapter 2.4.

8. Codified or Software Defined Infrastructure: Software Defined Infrastructure (SDI) is the adoption of software development

methodologies for realizing Dynamic Infrastructure to operating in an agile manner at scale and speed. Chapter 2.3

discusses this from an Infrastructure as Code (IaC) point of view, which enables decoupling of services from physical

hardware and simplifies horizontal and vertical consolidation opportunities as needed for the organization.


2.3. Codifying Platforms for SDx

Generation Z or Post-Millennial enterprises are born digital whereas most others, including Millennials, recognize the necessity to

quickly become digital while carrying the dragging baggage of legacy and brownfield systems. Hence, the non-millennial or

traditional enterprises would not be in a position to simply fast-forward until they get equipped with digital‑ ready infrastructures.

The Third Platform consisting of SMAC (Social, Mobile, Analytics and Cloud) lays the foundation for a digital service delivery.

Cybernetic applications help to realize a digital application solution while IoE helps in digital analytics and smart interactions to

create an intelligent ecosystem.

IaC is vital here in realizing an agile digital infrastructure solution geared to the demands of the digital economy. It acts as a stepping

stone for enterprises to embrace the upcoming technology transformation of Software-Defined Anything (SDx). SDx represents the

combined initiatives towards promoting a greater role for software systems in managing and programming various hardware and

devices by abstracting the control plane of the underlying entities and then treating them wholly as software cutting across physical

boundaries.

IaC is the next-generation SDx infrastructure which can connect and manage the increasing number of software-defined devices and

applications to other SDx networks, IoE ecosystems, and eventually to end users. IaC adopts a novel approach to build and manage

dynamic infrastructures. It treats the entire infrastructure, dependent tools, and services as a code aligned within software

engineering10

. Hence, all best practices, proven procedures, and tools from software development are applied here to create a

reusable, sustainable, extensible, and testable infrastructure. The software configuration automation approach on the hardware

installed helps in consistent agile-based deployment at speed and at scale to meet the challenging dynamic demands. Again, all

which can be controlled centrally from one place. The market players catering to IaC include Ansible, Chef, CloudPassage, Puppet,

RightScale, SaltStack and Scalr.

Advantages of adopting IaC are:

Helps align the IT infrastructure organization to SDx from Day 1

Builds, enhances, and secures custom cloud solutions that exploit digital business opportunities through infrastructure

programmability and data center interoperability

Creates a bimodal strategy that delivers core services and enables agility without ignoring existing legacy and brownfield

investments

Compatible with hyper-converged solutions which offer new levels of scalability and cost control for massive expansion

Improves business agility and deliver effective services while allowing customers to benefit from the resulting simplicity,

cost reduction, and consolidation opportunities

Overhauls the technical support roles, skills, and work culture for better meeting the digital landscape

Introduces alternate costing models such as business output or outcome-based pricing helping simplify commercials and

licensing


Figure 4 depicts the typical workflow of the conventional Infra Configuration/Management (Upper-Half) and the Infra as a Code

(Lower-Half) lifecycle from planning to production.

The key differences between IaC and conventional Infra configuration in Figure 4 are:

IaC practices an integrated DevOps and end-to-end managed ITSM model all across while the other is siloed and

aligned to different towers

Abstraction of physical hardware and devices reusable Cookbook Repository/Templates is the key differentiator in IaC,

thus promoting accelerated agility and standardization

Intelligent automation across phases for Continuous Everything (Develop, Build, Test, Release, Integrate, Deploy),

thereby jumpstarting rollouts in IaC

App and Infra teams have their phases synchronized and response execution calibrated realizing greater synergies in

IaC

Change Management is more structured, swift, and safe through clear, reliable automated processes resulting in more

predictable results, resulting in optimized resource utilization, higher productivity, and rationalized costs

Appendix G illustrates a sample IaC Integration Pipeline using the DevOps lifecycle process in AWS platform.

Figure 4: Conventional Infra Configuration vs. IaC


2.4. Cybernetic Applications

Cybernetic Applications are built keeping in mind the need to connect to various user ecosystems, in order to provide augmented

services without hosting all the capabilities in-house. Application Programming Interfaces (APIs) would increasingly help in bridging

these meshed ecosystems and the enterprise data lakes.

Industry has been using the various architectural approach like Monolithic or Client-Server or 3-Tier for developing enterprise

applications. The 3-Tier architecture (Web/Presentation-Application-Database) is widely used among these. Here, the application

occupies the middle layer of a three-tier design, with a presentation tier at its front end and a data tier behind it. The application

delivers data to the web browser in the presentation tier, which interfaces with the end-user requests to view, update, or modify

data based on the context and access rights. The application reads and writes information from and to the data tier where a

database or storage device or application organizes and maintains it. The business process logic for interaction and data

transformation is fully contained in the application tier. Although this approach has been working well, it is becoming outdated. This

is mainly because it was designed before smart phones and other mobile gadgets existed and when applications only needed to

interact with a single object at the presentation tier. Its biggest shortcoming is that the application is written as a single unified code

base, irrespective of the number of layers or how data processing is spread across them. The very monolithic nature complicates it

for both developer teams to change an application with the agility and flexibility required to match the end-user expectations and

for operations teams to scale the application up/down to match alternating market demands.

Consequently, the need of the hour is a modern approach designed specifically for the digital age in order to achieve the agility,

flexibility, and scalability required today. The Cybernetic application architecture is based on the 4-Tier Engagement platform

(Source: Forrester Research) depicted in Figure 5. An engagement platform supports a distributed, four-tier architecture natively

engineered to deliver compelling experiences, excellent performance, and modular integration on any device over any network at

Internet scale11

.


Figure 5: The Four-Tier Engagement Platform Makes Delivery Its Own Tier11

(Source: Forrester Research)

The distinct entities that constitute the 4-Tier engagement platform are:

1. Client Tier: This layer is the unique differentiator capable of handling all the diverse endpoints, end user interfaces, mobile

devices, and IoT. This is the user-facing layer that serves the twin purpose of capturing their continuous inputs (voluntary

and non-voluntary) and realizing their customized user experience (related abstract outputs). It is designed to be robust,

responsive, scalable, flexible, and channel independent. Hence, users would be able to receive a consistent and high quality

of service regardless of their channel of choice.

2. Delivery Tier: This layer is responsible for dynamically aligning the output based on the multidimensional intelligence

received from the client layer. It is designed to handle middle and last-mile changes ensuring optimal end-user experience,

irrespective of their location or channel connectivity and changing behaviors, leveraging content delivery networks (CDNs),

real-time optimization tools, ADLM based DevOps framework, and complex caching algorithms.

3. Aggregation Tier: This is the API layer that acts as the nerve center for integrating internal and external services using real-

time analytics driven multi-directional communication crucial for Cybernetic applications in processing and transforming

data in IoE ecosystem. It is designed to interface/integrate business solutions and components for making these processes

available to the Client layer by means of fully supported, presentation layer-independent APIs.

4. Services Tier: This acts as the broker for linking internally and externally provisioned data and functionality to other tiers. It

is designed for a micro services approach which is open and pluggable, and focuses on the integration and composition of

existing services as well as capability to extend to future ones. This helps in reusing and reducing the overall number of

solution components used with the goal of delivering best-in-class, integrated, and optimal processes whilst minimizing the

requirement to interface between multiple business solutions/workflows and streamlining design/implementation/support

costs.


Cybernetics-based architecture helps harness application intelligence to dynamically reconcile with the changing user expectations,

behavior, and environment. The Digital economy is virtually powered by the Application algorithm all through our daily routines. The

come into play every time we shop online, make reservations, book a cab, bank using mobile devices, rate up/down an ad or news,

watch a streaming video, opt for an online course, and so on. All these interactions generate a treasure trove of data which can

constantly guide the respective businesses. All this data is centered on people interactions ultimately driving enterprises to adopt a

people-centric business strategy realized through cybernetic apps residing on dynamic platforms powered by IoE-based analytics.

Perhaps never before in the history of IT, customers had a major say and varied choices to determine what technology cannel they

would use to connect and which enterprises they would reach out for the same needs. As enterprises start embracing the Third

Platform and transition towards Fourth Platform, the systems integration and process operations would start getting more complex.

To sustain these changes, they would need to dynamically align their IT systems and interfaces to business.

APIs serve as a bridge connecting useful information and plentiful data to and from between machines (as in M2M) which

collectively links the Internet of Things which jointly helps in realizing the IoE. APIs form the key to enabling a Digital economy. They

make IoT valuable by connecting many disparate things into a powerful mesh of IoE that offers astounding potential. The

communication industry is already moving towards service-oriented infrastructures based on Internet Protocol (IP), Service Oriented

Architectures (SOA), and Service Delivery Platforms (SDP) to cater to M2M and IoT communications indispensable for the IoE

ecosystem. APIs would help in extending SOA to the cloud, mobile devices, diverse applications, and an ever expanding host of

connected devices injecting itself into every aspect of our lives. One of the upcoming operational challenges is in constantly

managing the APIs at speed at scale in an agile manner without compromising stability and delivering remarkable user experiences.

API Management is vital for gluing together and controlling all these entities. It enables apt and reliable access connectivity for

secure communication from sensor nodes to applications residing just about anywhere, i.e. cloud-hosted environments, data

centers (own or partners), API-enabled devices, and computing platforms (Web, Smartphones, Tablets, Televisions, Gaming

Consoles, Cars, Smart Home gadgets or just about anything like "things" in the Internet of Things). A reference sample for an API

Management architecture is described in Appendix F.


2.5. Analytics of Everything

90% of companies think advanced/predictive analytics is important but <30% have deployed them12

, according to Source

Sandhill Dressner Benchmark Study

The global IoT analytics market is expected to grow from $4.85 Billion in 2015 to $16.35 Billion by 2020, at a Compound

Annual Growth Rate (CAGR) of 27.48% according MarketsandMarkets forecasts13

The expanding scale, speed, and diversity of user data can provide rich and fresher insights, enabling enterprises to engage with

customers in innovative ways, transform user experiences, and disrupt entire industries. However, in an IoE ecosystem where data

will be generated rapidly, distributed extensively, and have a brief shelf life, organizations would need an altogether different tactic

to transform data into valuable business insights in real time.

Analytics of Everything covers wide-ranging analytics aspects of a digital economy where people, processes, data, and things are

dynamically connected. This includes data stream management, big data analytics, real time business intelligence, predictive

insights, and data monetization. The analytics platform helps combine the steaming data deluge at the network edge with historical

business patterns and data science algorithms to spot the business moments, make meaningful connections, predict situations,

recommend practical actions, and aid or automate instant decision making. Some of the real life examples are:

Netflix recommender system, which understands the viewer and rightly predicts their next selections14

Amazon.com recommendation engine, which interprets user behavior and prompts them to buy more products15

Waze algorithms, which provide cars with better routes in real time based on numerous independent inputs, changing

traffic patterns on the fly16

The Internet of Everything (IoE) encompasses a wider context to the Internet of Things (IoT) wherein connectivity and intelligence

gets added to just about every device giving them distinctive functions and extra capabilities. IoE is considered in the industry as a

superset of IoT while M2M communication is considered a subset of IoT. IoE was coined by Cisco to describe the next generation of

IoT. Cisco defines IoE as bringing together people, process, data, and things to make networked connections more relevant and

valuable than ever before; turning information into actions that create new capabilities, richer experiences, and unprecedented

economic opportunity for businesses, individuals, and countries17

.

Principally, IoE would cater to all industries involving IoT and M2M and would have much wider scope and far reaching impact. So all

industries will have to deal with issues related to information security, privacy laws and regulations, IT infrastructure, systems and

interface compatibility, wired and wireless connectivity, data synchronization, mining and analytics along with myriad other things

that will crop up when interacting within the humungous IoE ecosystems the world over.


‘Analytics of Everything’ represents an end to end advanced analytics platform aligned to IoE for meeting these challenges. Figure 6

represents the six key levels in realizing analytics of everything by transforming raw data to continuous deeper insights that help

optimize key business assets and processes for any organization.

In Figure 6, the six stages involved for an ‘Analytics of Everything’ platform is shown on the right-half (Input to Dynamic decision-

making) while the key scope and activities in each stage is shown on the left-half (Input to Decision Guide). The market for ‘Analytics

of Everything’ or Predictive/Prescriptive analytics is fast growing with newer platforms enabling individuals and businesses to

succeed in the digital economy. A reference architecture for advanced analytics using Enterprise data lakes is outlined in Appendix D.

Also, a sample solution of Pivotal BigData suite is depicted in Appendix E.

According to Gartner-

By 2020, predictive and prescriptive analytics will attract 40% of enterprises' net new investment in business intelligence

and analytics18

Dell, IBM, KNIME, RapidMiner, and SAS are recognized as Leaders in the Gartner Magic Quadrant for Advanced Analytics

Platforms18

The advanced analytics platforms are designed to empower common users to be Citizen Data Scientists18

who will be able to

perform sophisticated analytics tasks that previously required complex expertise, now in a simpler manner. Gartner defines a

"citizen data scientist" as a person who creates models that leverage predictive or prescriptive analytics, but whose primary job

function is outside of the field of statistics and analytics.


3. Envisioning the Digital Enterprise

The Digital Strategies discussed in earlier chapters can be realized only with an Integrated Digital Enterprise Architecture (IDEA) as

the backbone. It should encompass people, process, tools, technology, and flexibility to scale at speed on-demand to cater to

changing market scenarios. The guiding principles at a high-level to build a game-changing digital savvy organization are:

Fluidic architecture aligned to Digital Strategy in terms of business vision, operating model, and goals

Robust delivery platform driven by continuous insights, derived through collecting and processing unparalleled volumes of

diverse data from various touchpoints

Empowerment of users and customers by self-service access to information by Data democratization (discussed later) for

creating engaging experiences

Predictive mechanism based on user behavior and service experiences with dynamic value-based journey mapping of

customer interactions (discussed in Analytics of Everything)

Social and Mobile engagement linked to user custom profiles to promote and nurture focus campaign from initial contact

through long-term relationships

Next Generation IT with SMAC-based platform, Cybernetic applications linked to business logic and IaC to support on the fly

data and application changes

Support collaboration and harvesting of digital assets, tools and accelerators, capability models, process innovations, and

operational best practices across business functions

The IDEA reference model depicted in Figure 7 presents an end-to-end design for bringing the digital future into present focus. The

sketch is based on the perspective of CIO to best cover all facets like business strategy, people engagement, user experience of

products and services, organization capabilities, application and infrastructure systems, technology and tools integration,

information management, data security, automation, analytics, and so on when architecting the solution. It illustrates the different

elements that have to be united to enable a modern seamless multichannel (digital and physical) experience19

. (Source: LiquidHub)

The 9 prime entities (Refer to Callouts in Figure 7) and their functions that constitute this architecture are:

1. User base: This represents the entire user community including employees, customers, partners, and other interested

followers who are directly or indirectly involved with the organization.

2. External: This represents the unified layer for all external integrations to public and partner ecosystems. It connects with

public and hybrid clouds, social platforms, third party devices, and applications.

3. Channels: This represents all modes of supporting user connections like mobile, email, chat, apps, etc. The user experience

is sensed and realized here in an iterative manner based on the dynamic computing in the ‘Experience’ layer.


4. Experience: This represents the digital value realization of user engagement and interactions with the products and

services. This supports the transient interactions processing based on inputs received from channels.

2-External

1-User base

3-Channels

4-Experience

5-Applications

9-Internal

6-Integrations

7-Enablers

8-Infra

Figure 6: Integrated Digital Enterprise Architecture19

(Source: LiquidHub)


5. Applications: This represents the Applications layer where the business process logic and algorithms are running. It includes

both COTS (Commercial off-the-shelf) and non-COTS applications.

6. Integrations: This represents the different integrations with data, people, and systems. This layer further refines the

information from the ‘Enablers’ to facilitate RTBI; Advanced (prescriptive or predictive) analytics; Interactive and

Continuous insights. Heuristics-based automations come into play in this layer.

7. Enablers: This represents the user identity and access management, digital assets management, standard analytics, security

analytics, and event management layers. This is mainly involved in supporting routine decision-making processes and

optimizing operations to support initial user expectations. Robotic Process Automation/Business Process Orchestration is

commonly used here.

8. Infra (or Infrastructure): This represents the dynamic infrastructure that acts as the supporting backbone and consists of on

premises (Data Centre/Private Cloud) or off-premises (Hybrid/Community Clouds) systems (Compute/Storage/Networks),

APIs, Intra gateways, and transactions.

9. Internal: This represents the internal capabilities; backend data systems (Backup, Recovery, Archival), Brownfield, and

Legacy systems, and built-in foundation analytics.

Concept of Blurring Boundaries

One of the most distinctive traits in the digital world is the several overlaps of people, process, tools, technology, and

platforms. It is very evident from the topics of strategy and architecture discussed. You will surely notice this in the coming

chapters as well. This blurring of boundaries across entities is perhaps the biggest singularity of the fluidic and volatile

digital ecosystem.

In the digital economy, this shifts boundaries of a physical and digital world. This in turn affects the products and services of

businesses, as customer value is data-centric and digitally controlled. In this both exciting and challenging reality, every

business starts to become a technology company in order to build and expand their platforms and ecosystems, while

seeking newer opportunities before someone else conquers their market space.

Blurring boundaries would compel organizations to adopt a Digital DNA at the earliest and build diverse competencies to

avert market space invaders who can digitally disrupt them. Chapter 4 elaborates on these facets of ‘Being Digital’.


3.1. Adoption Barriers & Enablers

To support an increasingly digital environment, today’s enterprises are relying primarily on in-house innovation teams, business

process automations, and mobility-based solutions. The most significant barriers to implementing digitalization is unpredictable

costs and change management, apart from not having a comprehensive strategy. As depicted in Figure 8, the net Barriers outweigh

the enablers in most enterprises beginning the journey of Digital transformation. These are typically either Digital followers or

laggards.

Figure 7: Typical Barriers Offsetting Enablers

The key ways to overcome the barriers are:

1. Value Change/Creation: Enterprises should look at creating digital value by revisiting one or more of their business process

execution and supporting systems. The common ones are adopting a Gateway-centered model, opting for either Alternate

Pricing models based on Business Outcomes or Service Unit-based, Omni-channel marketing, and selling. Chapter 3.2 covers

the steps for this transformation.

2. Organization Strategy & Structure: Unlike the rigid hierarchical decision making in Bureaucracy and ideal solution selection

based on exhaustive assessment in Meritocracy, Adhocracy promotes an Experimentation-based approach with the right

flexibility necessary for creating agile value propositions at speed and scale. This in turn helps adapt continuously to

changing markets, customer needs/behavior, and emerging technologies. The People-centric Business Quad in Chapter 2.1

and Design Thinking in Chapter 4.2 would together help in revisiting the organization DNA.

3. Talent Management: Enterprises pursuing digital transformations would need to significantly ramp up their development

teams in coming years. Talent hiring should focus on key skills like mobile apps development, big data analytics, heuristics-

based automation, and design thinking.

Key Barriers Key Enablers


3.2. Digital Transformation Approach

Organizations can adopt different proven approaches for a digital business transformation journey best suited in their spheres. On

the whole, it is important to embrace the Digital DNA with people-centric business strategy, understand how digital initiatives

impact all facets of the organization, and obtain buy-in from key stakeholders before embarking on a Digital journey led by

innovation leaders, driven in a phased manner with comprehensive change and risk management, and supported by tools and

technology for ensuring a successful transformation.

A three-phase reference approach to implementing a Digital Solution is shown in Figure 9.

Figure 8: Digital Transformation Approach20

(Source: Cognizant Technology Solutions)

The approach is based on "A Framework to Speed Manufacturing’s Digital Business Transformation20

" by Cognizant Business

Consulting and “The Digital Business Transformation Playbook21

” by Forrester. The papers have additional insights on proven

frameworks, best practices and use cases that would come in handy for the transformation journey.


The different phases, steps involved, and key activities are:

I. Phase 1: Assess - This phase involves methodical assessment by conducting brainstorming workshops and interviews with

stakeholders and external experts. The steps followed are:

1) Step 1: AS-IS (Current) state: SWOT (Strengths-Weakness-Opportunities-Threats) Analysis based on existing

capabilities and Digital Stratagem (Chapter 2)

2) Step 2: TO-BE (Future) state: Blue Ocean Strategy planning on how to create uncontested market space, demand

analysis, global challengers, and competitiveness review of People, Process, Tools, and Technology for ‘Going’ or

‘Being’ Digital journey

II. Phase 2: Plan - This phase involves feasibility deep-dive of opportunities identified in ‘Assess’ phase. The steps followed are:

1) Step 3: Gap Analysis: Evaluation of actual performance with potential or desired performance and Industry

benchmarks from Digital Leaders

2) Step 4: Prioritization and Business Case Preparation: This captures top digital themes aligned to the business

charter, the rationale for initiating related Projects with compelling value propositions, and Return on Investment

(ROI) estimates

3) Step 5: Roadmap Preparation: This is a strategic sequenced plan illustrating the business objectives aligned to the

agreed mission, vision, and growth direction across four mandates; People Centricity, Operational Excellence,

Agility, Products/Services, and Innovation. It also recognizes the different dependencies and together serve as a

basis for comprehensive project and execution planning towards realizing an Integrated Digital Enterprise

Architecture (Chapter 3)

III. Phase 3: Recommend & Transform - This phase includes the final steps towards realizing a Digital solution.

1) Step 6: Recommendation Workshop: This comprises mainly an in-depth business case presentation followed by

review discussions and approvals submission to key executives and stakeholders. The report includes all revenue-

and cost-related metrics directly or indirectly impacted by the digital transformation. It also identifies

improvement targets and determines the net business benefits. The workshop helps in final validation of the

digital value proposal, budget, and implementation timelines and risks mitigation measures before proceeding to

execution.

2) Step 7: Roadmap Execution: This is the execution phase where the digital initiatives are implemented according to

the agreed roadmap. The project progress is monitored in a timely manner and corrective actions taken as needed

until completion. The business outcomes of the digital initiatives are continuously measured to assess business

impact and appraise the journey towards ‘Being Digital.’


4. Steering to Being Digital

In order to steer from ‘Going Digital’ to ‘Being Digital’, enterprises would need to further imbibe the following distinguishing

potentials into their DNAs:

1. Digital Trust

2. Design Thinking

3. Data Democratization

Figure 10 represents the Enterprise DNA constituents of ‘Being Digital’, all of which is vital on their journey from ‘Going Digital’.

1. Digital Trust: The Digital economy is a ‘sharing’ economy realized by breaking down barriers and silos and providing access

to user data for an expected value, when and where it is needed at any given moment. This definitely raises severe

concerns around the numerous risks inherent with allowing unbound access to potentially sensitive data. Section 4.1 covers

Digital Trust in detail which comes into play in order to allay such concerns of every user.

2. Design Thinking: This is a human-centered design tactic for the new age where dynamic and digital algorithms are at the

core of any user interaction. This requires a totally new viewpoint to build and support systems which users want to think

and act for them. Section 4.2 elaborates on this creative style of thinking.

3. Data Democratization: This is all about enabling everybody to access and understand data as needed anytime, anywhere,

over any channel. The information intelligence of hindsight, insights, and foresights derived from the data is what would be

of value to the user. Section 4.3 covers Data democratization in depth.

Going Digital

Digital Trust

Design Thinking

Data Democratization

Being Digital

Figure 9: Enterprise DNA of 'Being Digital’


4.1. Digital Trust

Data is everywhere, mounting up by leaps and bounds in varying complexity and formats. On the one hand, this provides immense

opportunity for businesses which are equipped to draw insights from it to drive highly relevant and compelling products and

services. On the other hand, this success is dependent on the digital trust consumers and end users place in the prevailing system

and process to participate in the widely connected and growing ecosystem.

The McAfee Labs 2016 Threats Predictions report22

states: Everywhere we go and in everything we do, we are leaving a trail of

“digital exhaust.” The data and derived insights offers incredible business opportunities and at the same time grave risks. Every data

breach or scandal gradually undermines the trust of users. Hence, safeguarding digital trust is more important than ever with the

unprecedented penetration of Third/Fourth platforms with Cybernetic apps and IoT-enabled devices; altogether constantly creating

data surges across user systems and storage stacks. Some concerning trends noticed in global surveys and researches are:

54% of digital consumers are cautious about the information they share due to lack of confidence in the online security that

protects their personal data. (2015 Accenture Digital Consumer Survey)

Trust in all technology-based sectors declined in 2015 with data privacy and security concerns a key factor. (Edelman Trust

Barometer 2015)

78% of consumers state that it is hard to trust companies when it comes to how they use consumer personal data. (Study

from Orange, Future of Digital Trust, 2014)

82% of consumers are concerned that companies find more ways to gather data without being completely clear about the

methods and reasons for it, described as hidden harvesting. (Study from Orange, Future of Digital Trust, 2014)

More than 70% think cybersecurity threats to their organization are escalating. (McAfee Labs 2016 Threats Predictions

Report)

In this digital revolution, business models are getting created entirely by tapping the data of individuals and sharing derived value

insights. Ironically, while they are the digital frontrunners, they are also arguably one of the most subject to scrutiny. The wider

ethical question beyond privacy and security concerns that constantly arises in the minds of users is “How are enterprises and

institutions the world over using their information, particularly in relation to the use of personal data?”


Being Digital Trust Pyramid (Figure 10) is designed for consumers, businesses, and government organizations to succeed in their

journey towards ‘Being’ Digital. By embracing it across people, process, tools, and technology, you would be able to successfully

leverage the immense potential of the digital age for growth, manage the underlying risks, and safeguard the digital trust ethos.

Figure 10: Being Digital Trust Pyramid

The trust pyramid has four doctrines central to its execution. They are:

1. Data Privacy: This determines who can have permission to access the information, what level(s) of access they would have,

how they can use it, and until when.

2. Data Security: This helps in protecting the information against any data breach arising from theft, leakage, and/or

unauthorized use.

3. Data Regulation: This enforces governance and accountability by putting in place mechanisms for preventing misuse,

disseminating false information, enforcing policies, and ensuring remedial measures.

4. Business Value: This determines the business relevance and service applicability to collect, store, and share the information

for clear and mutually agreed user benefits.

According to Global Tolerance, over two thirds of people think that businesses need to deliver more social and environmental

change. Nearly three quarters want to see more transparency, and 81% more accountability. (Source: Global Tolerance: The Values

Revolution Report)

Any increase in cybercrimes and data spillages continuously erodes the digital trust of customers. It is the collective responsibility of

customers, end-users, partners, businesses, and governments to constantly uphold all the doctrines of the digital trust pyramid.

Data Security

Data Privacy

Data Regulati

on

Business Value


4.2. Design Thinking

Every enterprise should not and need not blindly aspire to be like Airbnb, NetFlix, or Uber to be a Digital Leader. The crux lies in

actually beginning to align the organization's transformation journey in terms of people, process, and technology towards their

digital business goals and being well in sight of the changing market dynamics. The biggest challenge in this mission towards 'Being

Digital' is transforming the mindset of people, their habits, and behaviors.

Design Thinking is the newest undercurrent in a volatile world, being considered for solution design to transform business

imperatives through technology affecting everyday lives of one and all. Design thinking (aka Cognitive thinking or Solution-based

thinking) is an innovative iterative methodology aimed at unlocking an ideal future result by complex problem solving, creative

solution designing (products/processes/services), redefining user experience, and/or revamping human interactions. Adopting a

Design Thinking style in the organization DNA enables and empowers employees to continuously improve organizational

performance, at times even beyond their respective control spheres. The unique characteristics of this methodology include:

Analyzing alternatively

Designing collaboratively

Simplifying multi-functions

Cross-pollinating innovations

Implementing frugally tangible solutions

Monitoring and controlling continuous feedbacks

Modifying business processes to social experiences

The conventional Analytical thinking method begins by defining the boundaries and identifying all the constraints of the case before

commencing on solution building. On the contrary, Design thinking is solution-focused, divergent, and iterative. It begins with

setting a goal (ideal future state) and works towards solution building with both known and ambiguous aspects of the case. During

the course it tries to unlock hidden possibilities, explore goal-oriented alternate options, and follows iterative steps, which could

result in intermediate solutions and triggers for alternate tracks including redefining of the initial case. Design thinking can pretty

much be applied to anything at large, for coming up with human-centered solutions to real world challenges or even the very need

for a change. Although, there are quite a number of frameworks in circulation, the prominent ones closely associated with the

journey towards 'Being Digital' are:

1. The Human-centered Design23

from IDEO

2. A Framework for Creativity & Innovation24

by Linda Naiman, Creativity at Work (See Appendix H)

3. The Design Thinking Process25

from Hasso Plattner Institute of Design at Stanford (aka The d.school)

The essence of Design Thinking is captured within the insight of the famous architect Frank Lloyd Wright - “You can use an eraser on

the drafting table or a sledgehammer on the construction site.”


The design approach outlined in Figure 12 based on the d.school model is best suited for the journey towards ‘Being Digital’. The

Design Thinking process outlined here has people centricity (employees, partners, customers, end-users) at its core of building

solutions. At large, it is solution focused and action oriented involving logical reasoning, creative freedom, user intuition, risk taking,

collaboration, and continuous iteration for arriving on several desired outcomes benefiting the end user.

The 6 steps involved in the process are:

1. Empathize: This is the foundation to fully understand the people (those receiving the end solution/service) from their

perspective. This involves detailed observations, multilevel interactions, subjecting yourself and immersing in customer

experiences within the context of the case.

2. Define: This is where you process and analyze all the findings collected to form a user point of view that needs to be

addressed. It’s about making sense of the extensive information gathered to frame a meaningful design challenge.

3. Ideate: This is where you generate numerous possible ideas, allowing you to step beyond the obvious and explore a range

of solutions relating directly or indirectly to the case. It aids in becoming innovative, exploring divergent options, and in

building tangible prototypes.

4. Prototype: Here, you get to transform your abstract ideas into any material form or canvas so that you and team can

collaborate for absorbing, studying, and developing more freely. A prototype can be anything that user(s) can interact with

to bring out more contextual emotions and responses.

5. Test: Here, your customer or end-user gets the first glimpse of the solution. You should further use their observations and

feedback to improve prototypes, learn more about the user, and refine your original point of view.

6. Iterate: Iteration involves cycling through the process multiple times in a controlled manner, narrowing the scope from the

early broad concept and identifying various nitty-gritties affecting the solution. It is a continuous lever and can be

conducted after any step as deemed necessary by the core team in order to converge towards a perfect solution.

People Centric

Empathize

Define

Ideate

Prototype

Test

Iterate

Figure 11: Design Thinking Framework (Based on d.school Model25

)


4.3. Data Democratization

In a Digital economy, the boundaries of BI data keep frequently blurring and shifting. The rate at which more and more data gets

created only complicates the need to quickly analyze and respond to changing conditions. So, smart management of this data (often

considered to be critical, competitive, and confidential) is one of the most important aspects of IoE Information management. The

Democratization of Data determines the 5Ws of putting data into the hands of employees, business users, and partners. It helps get

the right data at the right time to the right users for taking right decisions. Most enterprises, including Digital laggards,

predominantly focus on tracking, measuring, and reporting projected business performance against actuals. Comprehensive

business insights are not derived from the vast data captured and end up most of the time for standard operational reporting and

regulatory requirements.

Digital Followers are enterprises that have adopted RTBI with Predictive Analytics and significantly automated the routine tracking

and reporting of business performance. They would be using business insights generated from the systems for strategic planning and

design making to pilot their businesses with improved foresights. However, most times the complexity of the BI and analytics tools

used restrict the business insights to select executives, thereby slowing the adoption and dissemination of far-reaching changes.

Digital Leaders are those enterprises who have mastered the art of data democratization through their people-centric strategy

embedded in Digital trust systems. They use the business insights generated across the organization based on the role(s) ensuring

the right insights reach the right people at the right times. They would have also shifted to the Fourth Platform aligned to their

domain or industry so as to overcome the challenge of managing the tons of information as it increases and changes day by day.

The 5W code of Data Democratization helps unlock the trapped BI potential of data is described in Figure 13. This lays the

foundation for getting a unified and comprehensive view of the business with faster and proper insights, contrary to the common

siloed data lakes approach which are incapable to meet the dynamic requirements of the evolving and complex technology and

business landscapes. The various points to consider when factoring each of the conditions is also defined in each of the phases

aligned to 5Ws - What, Why, Who, Where, and When in the figure.


Figure 12: 5Ws of Data Democratization

What?

What all data and amount can be exposed?

Data shared can be Strategic, Tactical, and/or Operational

Quantity of data can also be related to purpose, time, and recipient

Why?

Why is it required?

Faster response times and Increased productivity

Processing for new service areas and/or involving niche skills

Who?

Who can have secure access to the data?

Employees, Customers, and Partners based on role(s)

Levels of access and control they would have over the data

Where?

Where are all the data getting processed and/or changed?

Location(s) of all the interactions impacting data in the process

Business Dependencies across all the channel touchpoints in the lifecycle

When?

When should the data sharing begin and end?

Duration of sharing based on decision making, planning, research

Trigger based on process events, business schedules, and developments


5. Going Digital vs. Being Digital

The Digital transformation of an organization is not an instant switchover. It is in fact a journey from ‘Going’ to ‘Being’ with

noticeable differences across various people, process, tools, and technology adopted and planned. Table 1 depicts the broad

highlights across different parameters of ‘Going’ and ‘Being’ digital. There could be exceptions based on the industry/market

operating, business model, and transformations already implemented or in progress.

Parameters Going Digital Being Digital

DNA Technology/Innovation Centric, Semi-

Digital Collaboration People Centric, Digital Collaboration

Project

Approach Bolt-on Fully Integrated

Core Focus Productivity, Efficiency, Cost Optimization

of Resources

Agility and Innovation at scale and at speed

for Users

Governance

Model Meritocracy and Role Based Adhocracy and Collaborative

Automation

Analytics

Robotic Process

Automation/Orchestration, Bimodal IT

Heuristics based/Cognitive Automation,

Bimodal/Bimodal+ IT

Business

Insights Event driven, Rule based, Semi-predictive

Data driven, Interactive insights and

Predictive

Differentiators Cybernetic Applications, SDI and Big Data

Analytics

Data Democratization and Analytics of

Everything

Platform(s) Hybrid and XaaS aligned to Third Platform,

Micro services/DevOps

Dynamic Business Models aligned to

Third/Fourth Platform, DevOps+

Skillsets Automation Architects, Digital Assistants,

Data Modelers

Citizen Data Scientists, Design Thinking,

Digital Artisans

Customer

Experience Bionic Personalized

Commercials Unit or Usage based pricing Output or Outcome based pricing

Table 1: Snapshot of Going Digital vs. Being Digital


6. Digital Disruptions Impact

The Digital revolution is now being touted as the Fourth Industrial revolution. As the lines between physical and digital assets

continue to blur, it will affect the way people, governments, businesses, utility services, data systems, machines, and devices interact

with each other leading to wide ranging impact across sectors. Some of these already visible include:

1. Dynamic Medical Diagnosis through Digital Phenotyping and Personal HealthMap: Patient Diagnosis is the basic prerogative

of any practicing Medical Doctor which could later be followed by lab tests, additional checkups, and so on. Americans

experience about 12 million diagnostic errors a year, according to Institute of Medicine (IOM) report26

of Sept 2015.

A misdiagnosis in the initial stage leading to inappropriate treatment may not necessarily be due to the lack of knowledge,

experience, or attention of the medical fraternity. There are numerous other influencing parameters of the patient like

lifestyles, diet and nutrition, relationships, sleep/rest patterns, exercise/physical activities, stress levels, reacting/interfering

medicines, interactions with others, climate/allergies, previous/current environment, and so on which complicates the

procedure. Hence, an ideal medical diagnosis should be thorough considering the dynamic internal and external

environment of a patient supported by sound and secure rational.

Today, through technological advances in wearables and mobile gadgets we can monitor and measure our activities like

calories consumed/burnt, sleep cycle, blood pressure, brain waves, stress levels, internet behavior, and much more without

the need for invasive testing. Digital Phenotyping-based platforms primarily capture the discernable individualities of

people in relation to their surroundings. This is turning out to be a masterstroke in the clinical and biological domain owing

to its applications across pathology, drug research, phylogenetics, and pharmacogenomics.

All these data points create a digital health footprint of a patient that can be of significant clinical value for diagnosis and

treatment. However, the challenge is in accessing and deducing this information for us to make better daily choices; for

physicians adopting derived insights into clinical practice for informed decision making, maintaining patient safety and

privacy all through; and IT in integrating these with existing systems. All this leads to faster, accurate, customized, and cost-

effective patient care and health insurances.

CancerIQ in the area of Oncology, NextBio in genomic big data research, WellDoc in lifecycle management of Diabetics, and

Quantified Skin in the area of dermatology are some of the innovative players in this space27

.

2. Traffic Management, Auto Industry & Vehicle Insurance: Telematics along with IoE-based devices embedded in vehicles can

record the behavior of the driver such as speed, reflex, etc. across varying parameters such as time, traffic scenarios,

weather conditions, and so on. The capability to collect, process, and analyze actual driver behavior is going to help

insurance providers with better information for policy pricing and benefits based on predicted driving behavior. Self-driving

cars are no longer a futuristic automotive idea with all the major auto manufacturers involved. Recently, Google's self-

driving AI system had been officially recognized as a driver in the US28

. This would definitely help fast track the legalization


process of autonomous vehicles. ‘The Self-Driving Car Report’ by BI Intelligence estimates that there would be about 10

million self-driving cars will be on the road by 202029

.

3. Weather Forecasts, Climate Study and Impact Analysis on Business: Predictive Analytics of data collected and processed

from weather sensors, retail point of sales, etc. The data collected on daily weather conditions helps analysts learn climate

trends. The people behavior during different seasons can further be linked to commodity sales for studying market

shopping trends, customer service volumes, and even travel and hospitality across different groups.

Change London is a non-profit organization which is building a unique, , air quality monitoring network of thousands of

sensors which will help people of all ages connect with and understand air pollution, share real-time health information

with everyone through free apps, and enable solutions to be targeted accurately and efficiently30

.

4. Smartphone Companion and Internet of Me: Mobility has increased the amount of data exponentially as connected devices

collect data simply with their movement even without obvious user interactions. In fact, the connectivity signal (e.g.

between router and mobile device) itself creates data and information relating to the distance, duration, and history of user

behavior in a given vicinity. For retailers, valuable business insights can be derived by applying data science and advanced

analytics to this metric (i.e. most recent visit, frequency and duration of visits, and so on) coupled with user interactions,

behavioral pattern, and other external factors. This can be used for far-reaching predictive models for customizing user

alerts, ads or offers in malls, supermarkets, restaurants, and possibly anywhere.

5. Digital Homes (also known as Smart Homes): Digital Homes is a single amalgamation of where we can actually see and

experience the consumer impact of a complete digital outburst. Common devices such as coffeemakers, oven, refrigerators,

televisions, sleep beds, treadmills, vacuum cleaners, washing machines, and almost everything can get connected to the

internet and be controlled smartly. The information regarding the use of these smart devices combined with advanced

analytics opens up a plethora of new possibilities never imaginable earlier. Some of them are:

a. Usage of household devices linked to different insurance policies

b. Proactive device performance alerts to respective product vendors

c. Deep-dive on utilities consumption based on house demographics

d. Predict patterns based on behavioral trends like TV viewing

e. Study sleep patterns linked to medical diagnosis/history

f. Enhanced home security by setting monitoring parameters

The smart home automation market is thriving with players like Google Nest, Samsung SmartThings, INSTEON, and Wink

among others. The IoT standards and protocols are evolving with a majority of devices – from wall switches, bulbs, blinds,

thermostats, motion sensors, cameras, security sirens, and more – coming with their own apps, systems, and connections,

most unable to talk to each other. However, major technology vendors and smart home solution providers would be

looking beyond just inter device compatibility, cross-platform support hub ,and universal remotes by applying intelligence

to smart technology to achieve a connected home through the IoE ecosystem31

.


6. State affairs, Management and distribution of public utilities: The Digital Government objective involves embracing citizen-

centric methodologies of continuous enablement and empowerment for accessing government information and services

anywhere, anytime, on any device. This helps streamline process operations across the portfolio of public services and

utilities with higher efficiency, transparency, and accountability, thereby improving quality of governance and services

delivered economically on demand.

Almost all routine tasks like updating marital records, changing residential/official addresses, certifying/attesting

documents, applying for utilities, requesting individual licenses (hunting, fishing etc.), tracking progress of requests, voicing

opinion on completed/ongoing/planned programs and initiatives, and so on can now be performed instantly, avoiding

delays, costs and other redundancies across several touchpoints during the conduct of business.

Most existing systems of public policy, government decision making, and law enforcement are outdated with their erstwhile

linear and bureaucratic processes. To cope up with the digital era, legislators and regulators will have to revamp

governance practices as do private sectors, in order to unlock the immense potential of knowledge economy for

spearheading sustainable community development. Owing to multipronged competition, redistribution, and

decentralization of power with digital practices, innovative policymaking would take center stage unlike conducting policy

and redressals which consumes an inordinate amount of time and energy today.

Everything can now become smart when connected to the milieu of IoE. Be it smart cars, smart appliances, smart wearables, and

more, all get ‘smart’ tagged when they become intelligently hooked up to the Internet and interconnect to a vast ecosystem of

devices, software, and services. According to SAP Center for Business Insight: The use of sensors will grow 700,000% by 2030, in

order to help solve nearly every human need and want, from smart shoes to cancer killing chips32

.


7. Looking Beyond

By 2020, information will be used to reinvent, digitalize, or eliminate 80% of business processes and products from a decade earlier

(Source: Forbes, Gartner predicts Three Big Data trends for Business Intelligence). Being Digital is the key to success in a hyper

connected ecosystem, to solve real-world problems through intelligent information and insights creating greater possibilities for

mankind.

The impact of Digital and allied technologies to society and industry has been quickly summarized at the recently concluded World

Economic Forum 2016 at Davos. Their findings state33

:

By 2025, the combined value of digital transformation across industries could be greater than $100 trillion33

The combined effects of digital technologies (mobile, cloud, artificial intelligence, sensors, and analytics, among others) are

accelerating progress exponentially. But, the full potential will not be achieved without collaboration between business,

policy-makers, and NGOs33

Gartner reveals mind boggling digital growth in 2016 where spending on the Internet of Things (IoT) will exceed $2.5 million dollars

per minute34

. Also, 125,000 large organizations are launching digital business initiatives now and CEOs expect their digital revenue to

increase by more than 80% by 202034

IDC expects that the percentage of enterprises creating advanced digital transformation

initiatives will more than double by 2020, from today’s 22 percent to almost 50 percent35

Blockchain is another major transformational idea in mainstream banking and finance. It uses computer code to engender trust in

digital economy transactions, creating a record of digital events that is cryptographically impossible to counterfeit or manipulate.

These are early days with many central and commercial banks and governments worldwide recognizing the immense potential and

starting to design, develop, and test systems and infrastructure to support this. Widespread adoption in the future can revolutionize

how all financial transactions, i.e. payments, transfers to clearing mechanisms, and intra-bank settlements are carried out to where

many of these transactions that now take days can be settled instantaneously and transparently. Blockchain implementation can

single handedly catapult the Digital economy through a global financial process overhaul36

.

Digital advancements in the fields of genetics, biomedical, and clinical analytics are leading towards customized medical treatments

in accordance to the dynamic profile of the patients. Although areas like Phenome research is an ongoing endeavor, even the

potential trapped in currently available data is yet to be unlocked. This coupled with the implementation of innovative technologies

like Precision Medicine, mHealth, and Biometric sensors would open exciting opportunities in the coming years in the healthcare and

life sciences industry.

The future of digital enterprises would be built on data insights that determine how to engage with farsightedness; to predict

behaviors of customers, employees, and business partners; and deliver personalized products and services offering true user value

at the precise moment of need, sometimes even before the need is realized. The most significant hurdle in this journey is the wide

range, varying risks, and immaturity of process, tools, technology, and services in the evolving Fourth Platform together with IoE.


This directly impacts the solution designs which should meet steady performance at speed and at scale enduring the test of time.

Although architecting solutions using layering and modularity methodologies can reduce the risks significantly, disruptive

technologies and connected services affecting core businesses should always be on the radar of every organization.

Digital technologies will empower customers and transform industries like never before. The speed of this digital revolution is only

going to get faster with the increasing hyper-connectivity among data, humans, and machines. Though Digital leaders already have a

head start and are enjoying a significant competitive advantage, this could simply vanish if they remain complacent. To compete in

the face of digital disruption, organizations need to transform and transform now before getting blindsided. The rigor must be in

continuously enhancing your digital customer experience while also driving agility and efficiency at scale, using continuous business

insights derived from the ever-increasing ‘data.’ Yes, it finally boils down to how companies churn the vast data into valuable

business insights. So, what happens when there will 200 billion connected devices on the Internet of Things by 202037

? Luckily, we

need not wait long as the waves of digital disruption are fast approaching!


Appendix A: Research References

End Notes

[1] "The Digital Advantage: How digital leaders outperform their peers in every industry" by MIT Center for Digital Business and Capgemini

Consulting

[2] “Big Data, Analytics, and the Future of Marketing & Sales” by Jonathan Gordon, Jesko Perrey, and Dennis Spillecke from McKinsey &

Company

[3] http://www.forbes.com/sites/gartnergroup/2014/08/26/where-are-you-on-the-digital-business-development-path/

[4] IDC Worldwide Quarterly Wearable Device Tracker, December 3, 2015

[5] “Disrupting Digital Business” by R Ray Wang; HBR Publication 2015

[6] Forrester Predictions 2016: The New Breed Of CIO- How Digitally Savvy CIOs Obsessed With Customers Will Drive Growth

[7] Ibid.

[8] http://in.teradata.com/News-Releases/2015/Breakthrough-Teradata-Software-Pushes-the-Analytic-Edge-with-Internet-of-Things-Data/

[9] http://blog.softwareinsider.org/2014/03/23/research-report-digital-artisans-the-seven-building-blocks-behind-digital-business-dna/

[10] Infrastructure As Code: Fueling The Fire For Faster Application Delivery by Forrester

[11] http://blogs.forrester.com/ted_schadler/13-11-20-mobile_needs_a_four_tier_engagement_platform

[12] Source Sandhill Dressner Benchmark Study Reveals Trends in Advanced and Predictive Analytics in BI

[13] http://www.marketsandmarkets.com/PressReleases/iot-analytics.asp

[14] The Netflix Recommender System: Algorithms, Business Value, and Innovation by Carlos A. Gomez-Uribe and Neil Hunt from Netflix, Inc.

[15] Amazon.com Recommendations: Item-to-Item Collaborative Filtering Industry Report by Greg Linden, Brent Smith, and Jeremy York from

Amazon.com

[16] https://wiki.waze.com/wiki/How_Waze_determines_turn_/_keep_/_exit_maneuvers#The_algorithm

[17] http://www.cisco.com/web/about/ac79/innov/IoE.html

[18] Gartner Magic Quadrant for Advanced Analytics Platforms, 09 February 2016

[19] http://blog.liquidhub.com/2015/10/implementing-digital-architecture

[20] http://www.cognizant.com/InsightsWhitepapers/A-Framework-to-Speed-Manufacturings-Digital-Business-Transformation-

codex1614.pdf

[21] https://www.forrester.com/The+Digital+Business+Transformation+Playbook+For+2015/-/E-PLA710

[22] http://www.mcafee.com/us/resources/reports/rp-aspen-holding-line-cyberthreats.pdf

[23] http://www.designkit.org/

[24] http://dschool.stanford.edu/redesigningtheater/the-design-thinking-process/

[25] http://www.creativityatwork.com/design-thinking-strategy-for-innovation/

[26] National Academies of Sciences, Engineering, and Medicine. 2015. Improving diagnosis in health care. Washington, DC: The National

Academies Press

[27] http://iq.intel.com/can-big-data-solve-big-health-problems/

[28] http://www.dezeen.com/2016/02/12/google-self-driving-car-artficial-intelligence-system-recognised-as-driver-usa/

[29] http://www.businessinsider.com/report-10-million-self-driving-cars-will-be-on-the-road-by-2020-2015-5-6?IR=T

[30] http://www.changelondon.org/about.php

[31] "Embedded Intelligence: Why the Smart Home Isn't Smart" report from Research and Markets

[32] http://spb-global.com/uncategorized/trillion-sensors-equivalent-150-sensors-per-human-earth/>>>

[33] http://www.weforum.org/press/2016/01/100-trillion-by-2025-the-digital-dividend-for-society-and-business


[34] http://www.gartner.com/smarterwithgartner/the-arrival-of-algorithmic-business/

[35] IDC On-Demand Webcasts: IT Industry 2016 Predictions; Digital Transformation 2016 Predictions; CIO Agenda 2016 Predictions

[36] http://www3.weforum.org/docs/WEF_The_future__of_financial_services.pdf

[37] http://www.intel.com/content/www/us/en/internet-of-things/infographics/guide-to-iot.html

[38] http://ww2.kqed.org/mindshift/2013/07/25/what-the-future-of-learning-might-look-like/

[39] http://dionhinchcliffe.com/2015/05/04/the-rise-of-the-4th-platform-pervasive-community-data-devices-and-intelligence/

[40] "Trolling in the Data Lake? Get Yourself a Fish-Finder," Cognizanti Digital Business 2020: Getting there from here!,

http://www.cognizant.com/perspectives/information-architecture-trolling-in-the-data-lake-get-yourself-a-fish-finder

[41] http://pivotal.io/big-data/pivotal-big-data-suite

[42] https://developer.ibm.com/apimanagement/docs/api-101/ibm-reference-architecture-api-management/

[43] https://blogs.aws.amazon.com/application-management/blog/tag/infrastructure, ARC307 - Infrastructure as Code

[44] https://d0.awsstatic.com/whitepapers/AWS_DevOps.pdf

Bibliography

[45] Big Data @ Work by Davenport

[46] Infrastructure as Code by Kief Morris

[47] The Design of Everyday Things by Don Norman

[48] From Internet of Things to Internet of Everything by Frost & Sullivan

[49] Design Thinking: Understanding How Designers Think and Work by Nigel Cross

[50] Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel

[51] Cognitive Automation of Data Science by Horst Samulowitz, Chandra Reddy, Ashish Sabharwal

[52] Building Real-Time Data Pipelines by Conor Doherty, Gary Orenstein, Steven Camiña and Kevin White

[53] The New Digital Age: Reshaping the Future of People, Nations and Business by Eric Schmidt, Jared Cohen

[54] Disrupting Digital Business: Create an Authentic Experience in the Peer-to-Peer Economy by R "Ray" Wang

[55] Demystifying Code Halos through the Lens of IoT by Mohammed Hashim from EMC Knowledge Sharing 2015

[56] Deloitte Centre for Health Solutions report "Connected health: How digital technology is transforming health and social care."

[57] The Phoenix Project: A Novel About IT, DevOps, and Helping Your Business Win by Gene Kim, George Spafford and Kevin Behr

[58] Digital to the Core: Remastering Leadership for Your Industry, Your Enterprise, and Yourself by Mark Raskino, Graham Waller

[59] Leading Digital: Turning Technology into Business Transformation by George Westerman, Didier Bonnet, Andrew McAfee

[60] Big Data: A Revolution That Will Transform How We Live, Work and Think by Viktor Mayer-Schonberger, Kenneth Cukier

[61] The Second Machine Age : Work, Progress, and Prosperity in a Time of Brilliant Technologies by Erik Bryniolfsson, Andrew McAfee

[62] Building a Digital Analytics Organization: Create Value by Integrating Analytical Processes, Technology, and People into Business

Operations by Judah Phillips

[63] The New Digital Revolution: From the Consumer Internet to the Industrial Internet by the Economic Commission for Latin America and

the Caribbean (ECLAC)

[64] Value Proposition Design: How to Create Products and Services Customers Want by Alexander Osterwalder, Yves Pigneur, Gregory

Bernarda, Alan Smith, Trish Papadakos

[65] Driving Digital: Welcome to the ExConomy by Stijn Viaene and Lieselot Danneels. Cutter Consortium Business Technology & Digital

Transformation Strategies Executive Update, Vol. 18, No. 16, 2015


Web links

[66] www.ieeesmc.org

[67] www.ideo.com/about

[68] www.smartthings.com

[69] designthinkingmovie.com

[70] www.thinkwithgoogle.com

[71] www.strategyanalytics.com

[72] hbr.org/hbr-analytic-services

[73] martinfowler.com/design.html

[74] www.connectedfuturesmag.com

[75] en.wikipedia.org/wiki/Design_thinking

[76] www.digitalistmag.com/digital-economy

[77] knowledge.wharton.upenn.edu/topic/technology

[78] latestthinking.cognizant.com/digital/digital-thinking

[79] www.mckinsey.com/client_service/mckinsey_digital

[80] www.fastcompany.com/919258/design-thinking-what

[81] reports.weforum.org/digital-transformation-of-industries

[82] www.gartner.com/technology/research/algorithm-economy


Appendix B: Future of Learning (A Digital Impact Case in Point)

The impact of Digital revolution would overhaul the Education and Learning sectors in coming years. The research from

KnowledgeWorks predicts a diverse learning ecosystem based on how technology and new teaching strategies are shaking up

traditional models. The infographic in Figure 14 captures a Glimpse into the Future of Learning in the digital era.

Figure 13: Glimpse into the Future of Learning38

(Source: KnowledgeWorks)

The lifecycle at large shows the transformation of 'How Post-millennials and Generation Z students want to learn and how modern

education and training institutions need to function' The new generation demands more flexible and customized models of learning,

empowering them to face the modern challenges with clear directions and benefits across all stages of their journey. Digital

transformation in personalized and adaptive learning experiences will be realized by deriving continuous insights from the data

surrounding students and their direct and indirect interactions with other entities in the learning lifecycle.

All the stakeholders involved in the end to end educational lifecycle (students, tutors, academies, career development centers,

employers, and so on) would benefit from this overhaul based on the data that is continuously collected, analyzed, and valuable

insights shared, to help determine the best options and opportunities across various stages.


Appendix C: Rise of the Fourth Platform

We are just settling down with the Third Platform – principally SMAC (Social-Mobility-Analytics-Cloud) – with extensive innovations

and growth. Although this would continue as the foundation for the next few decades, we cannot rule out the quicker emergence of

the Fourth platform considering the pace of the digital revolution.

Quoting Dion Hinchcliffe39

- “The Fourth Platform is ambient computing, which strong components that turn network potential from

our favorite ecosystems into data, and then data into knowledge, and make it as easy as just thinking about it. The next generation

commercial ecosystems will even augment time and thought for us, even predicting what we’ll need before we figure it out

ourselves.”

Figure 15 depicts the futuristic functional model along with comparison of the other platforms.

Figure 14: Reference Model of Fourth Platform39

(Source: dionhinchcliffe.com)


Appendix D: Fishing in the Enterprise Data Lakes

The reference architecture for Analytics of Everything is shown in Figure 16 which can help gain insights that enable organizations to

deliver the next great user experience, product, or service. It is a “fish-finder” for business insights designed in the form of a smart,

semantic model that captures the meaning of data, as well as the related domain expertise from data (whether it is structured,

unstructured, or semi-structured). The key building blocks for such a model are:

Resource Definition Framework (RDF): This organizes data in a graph structure, reducing development time and cost while

delivering business value more quickly.

Web Ontology Language (OWL): This provides a comprehensive model of data definitions and relationships that is human

and machine-readable.

SPARQL Query Language: This is a SQL-like query language for semantic data that can leverage ontological relationships to

execute smarter questions across multiple databases in a single query.

Inferencing: This makes it easier for users to construct queries by capturing and embedding expertise in the ontology

model.

The data flows from left to right. The tiers on the left depict the data sources, the tiers in the center indicate the data processing

management, and the tiers on the right depict the integration points on how business insights are expended.

Figure 15: Fishing in the Enterprise Data Lakes40

(Source: Cognizant Technology Solutions)


Appendix E: Pivotal Big Data Analytics Platform

The Analytics of Everything (Predictive or Prescriptive Analytics) discussed in Chapter 2.5 can be realized only when organizations

can tackle Big Data, Agile methodologies, Cloud-native applications, and IoT. Pivotal Big Data Suite depicted in Figure 17 has

solutions that help organizations satisfy evolving information needs while handling newer challenges including big data processing,

massive data sets, data access by various mobile users, and wide-ranging transactional systems. It has some of the most disruptive

enterprise data products such as MPP and column store databases, in-memory data processing, and Hadoop.

It is basically open, agile, and cloud-ready, and its components can be deployed on commodity hardware, pre-certified appliances,

virtualized and private cloud instances, and in public clouds. It can ascertain insights by integrating data from multiple sources and in

multiple formats, combining RTBI/Predictive analytics that provide enterprises with continuous valuable insights for informed

decision-making.

Figure 16: Pivotal Big Data Suite41

(Source: Pivotal)


Appendix F: Reference Architecture for API Management

A sample reference architecture for API Management is depicted in Figure 18. It is a key constituent of any Cybernetics application

architecture discussed in Chapter 2.4. The reference architecture below encompasses the entire API economy including API

consumers, API marketplaces to find APIs, and API providers.

Figure 17: API Management Reference Architecture42

(Source: IBM)


Appendix G: IaC Integration Pipeline

IaC is covered in-depth in Chapter 2.3. It basically treats infrastructure as software and follows the ADLM process aligned to DevOps

for end to end management. Figure 19 illustrates the various phases involved in the pipeline from concept to deployment in a typical

AWS platform.

Figure 18: IaC Integration in CI/CD Pipeline43

(Source: AWS ARC307 Infrastructure as Code)

This depicts a Continuous Deployment44

of DevOps model supported by:

AWS CodeCommit – a secure, highly scalable, managed source control service that hosts private Git repositories. It

eliminates the need to operate existing source control system or worry about scaling its infrastructure.

AWS CodePipeline – a continuous delivery and release automation service that aids smooth deployments.

AWS CodeDeploy – code deployment service ability to deploy applications across an Amazon E2C fleet with minimum

downtime, centralizing control and integrating with existing software release or continuous delivery process.

AWS CloudFormation templates – to provision infrastructure in a repeatable and reliable way.


Appendix H: A Framework for Creativity & Innovation

An alternate approach to Design Thinking discussed in Chapter 4.2 is illustrated in Figure 20. This model combines classic creative

problem-solving modalities with principles and practices of art and design25

. The Ten Stepped process as shown in the figure can be

applied for driving, managing, creating, and innovating anything and everything that needs to be optimized for human interactions.

This includes creating and enhancing products and/or services, redefining user experiences, and remodeling business and functions

for the digital economy.

Figure 19: A Framework for Creativity & Innovation25

(Source: CreativityatWork.com)


Dell EMC believes the information in this publication is accurate as of its publication date. The information is subject to change without notice. THE INFORMATION IN THIS PUBLICATION IS PROVIDED “AS IS.” DELL EMC MAKES NO RESPRESENTATIONS OR WARRANTIES OF ANY KIND WITH RESPECT TO THE INFORMATION IN THIS PUBLICATION, AND SPECIFICALLY DISCLAIMS IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Use, copying and distribution of any Dell EMC software described in this publication requires an applicable software license. Dell, EMC and other trademarks are trademarks of Dell Inc. or its subsidiaries.

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