MAALBS Big Data agile framwork

1 MphasiS BIG Data Analytics practice

The use of Big Data is becoming a crucial way for leading companies to outperform their peers. In most industries, established competitors and new entrants alike will leverage data-driven strategies to innovate, compete, and capture value. Indeed, we found early examples of such use of data in every sector we examined. In healthcare, data pioneers are analyzing the health outcomes of pharmaceuticals when they were widely prescribed, and discovering benefits and risks that were not evident during necessarily more limited clinical trials. Other early adopters of Big Data are using data from sensors embedded in products from children’s toys to industrial goods to determine how these products are actually used in the real world. Such knowledge then informs the creation of new service offerings and the design of future products

Big Data will help to create new growth opportunities and entirely new categories of companies, such as those that aggregate and analyze industry data. Many of these will be companies that sit in the middle of large information flows where data about products and services, buyers and suppliers, consumer preferences and intent can be captured and analyzed. Forward-thinking leaders across sectors should begin aggressively to build their organization’s Big Data capabilities.

In addition to the sheer scale of Big Data, the real-time and high-frequency nature of the data are also important. For example, ‘now casting,’ the ability to estimate metrics such as consumer confidence, immediately, something which previously could only be done retrospectively, is becoming more extensively used, adding considerable power to prediction. Similarly, the high frequency of data allows users to test theories in near real-time and to a level never before possible.

Why Big Data a competitive advantage?


Success Stories of Big Data

Business Values of Big Data

Data centers can reduce storage costs and improve utilization rates by as much as 30%.

Financial services firms can store and provide access

to granular transaction records for the 5–7 year timeframes mandated by the regulatory demands of Dodd-Frank, Sarbanes-Oxley, etc.

Transportation companies can save up to USD

0.5million per annum by retaining its truck drivers. Enterprise Information Technology departments can

cut production support costs by 30%.. Companies can move from batch processing of MRO

data to event driven processing. Statistical models can be executed up to 50 times

faster improving response times for business decisions.

Insurance companies can increase profitability by 30% by identifying 5% more fraudulent claims

Increased customer satisfaction Improving Patient Care Identifying and Reducing Fraud Optimizing Network Geo-Location marketing Assessing & Monitoring Risk Preventive Maintenance Unlimited scale of storage and processing

provides new flexibility. Scalable real-time processing New data accessibility Clinical trials Genomics Spatial Science Weather Predictions Disease patterns Patients behaviors ……………………………………………………

MphasiS Big Data Technology Partners

IBM Vertica


MphasiS Future plans on Hadoop BigData

Building Big Data COE

Partnering with Hadoop Vendors like Cloudera, IBM, Hortonworks,

Map R

Working currently to build the Big Data team of 10-12 team size

with Hadoop and other Big Data skills in next 2 quarter of time

Working on setting up the infrastructure with Hadoop technology

for the POCs, trainings and POCs

Next Steps - Mphasis is willing to partner with HP to define the use

case for Big Data and take it forward as POC at 50% of Mphasis

cost investment

GTM Strategy with HP

To start with, Mphasis can provide the Hadoop resources for

the confirmed Big Data projects/POCs for HP and work as an

extended team for HP.

Once we have couple of implementation cycles completed in

next 2 quarters, we can own and delivery of the Big Data

projects

3 Dimensions of Big Data COE

Trained talents on Hadoop and its Ecosystems

Doing POC’s on Sentimental analysis using Semi Structured Data on AMAZON

Cloud using EC2 platform

Working currently to build the Big Data team of 10-12 team size with Hadoop and

other Big Data skills in next 2 quarter of time

In the process of evaluating the Big Data use cases across our customer base in

Insurance and BCM market units and plan for 2-3 POC’s in next 2 quarters

Working on setting up the infrastructure with Hadoop technology for the POCs,

trainings and POCs

MphasiS ASIS state on Hadoop Bigdata MphasiS current capability on Hadoop and Ecosystems

10+ trained resources on Hadoop and its Eco systems out of

which 4 have been trained on IBM Big Insights.

2 certified talents on Cloudera

4 certified talents on UBM Big Insights


MphasiS AGIL Application Life cycle Business Service for BigData services


Every IT organization wants to accelerate innovation, lower costs, and ensure the high quality of its services. Yet, each of these goals presents challenges.

Companies need to discover and evaluate the implications that business innovations may have on their system landscapes — and IT must work to minimize any

system downtime these innovations may require. Companies need to ensure ongoing quality in terms of functionality, performance, availability, and security; the

business simply depends on it.

The system development and support process is complicated and complex. Therefore maximum flexibility and appropriate control is required. Evolution favors

those that operate with maximum exposure to environmental change and have optimized for flexible adaptation to change. Evolution deselects those who have

insulated themselves from environmental change and have minimized chaos and complexity in their environment.

Inline with the agility existing in the current business and technology challenges , MphasiS has adopted a framework called MAALBS -MphasiS AGIL

application Life Cycle Business Services which is a blend of AGILE SCRUM + ITIL+ LEAN for effective delivery model for BIG Data Services which is a proven

for short term wins which is of iterative and incremental and adopts the effective change management process for responding to the change which depends on

the degree of Change request and also adopts the LEAN methodology for eliminating the waste , Amplify Learning, Deliver as Fast as Possible, Empower

Teams and Build Integrity In on the deliver quality workable product right from DISCOVER, DESIGN, DEVELOP.DEPLOY & SUPPORT. (4D) = (4A) (Acquire ,

Analyze , Assemble and Act ).

We are uncovering better ways of developing software by doing it and helping others do it . Through this work we have come to value

Team collaboration over the processes and tools

Quality deliverable over comprehensive documentation

Stakeholder’s collaboration over contract negotiation

Rooms for innovations and welcoming Changes over following a plan

Manifesto of MAALBS - MphasiS AGIL Application Life cycle Business Services


Our highest priority is to satisfy the customer through early and continuous delivery of valuable software.

Welcome changing requirements, even late in development.

Providing rooms for Innovation across Project Process and Technology

Deliver working software frequently, from three weeks to six weeks, with a preference to the shorter timescale.

Business people and developers must work together daily throughout the project.

Build projects around motivated individuals. Give them the environment and support they need, and trust them to get the job done.

The most efficient and effective method of conveying information to and within a development team is face-to-face conversation.

Working software is the primary measure of progress.

MAALBS processes promote sustainable development. The sponsors, developers, and users should be able to maintain a constant pace indefinitely.

Continuous attention to technical excellence and good design enhances agility.

Simplicity -- the art of maximizing the amount of work not done -- is essential.

The best architectures, requirements, and designs emerge from self-organizing teams.

At regular intervals, the team reflects on how to become more effective, then tunes and adjusts its behavior accordingly.

Principles of MAALBS - MphasiS AGIL Application Life cycle Business Services


MphasiS Mind maps on Big Data Projects


Phases of MAALBS -MphasiS AGIL Application Life cycle Business Services

MAALBS has the following group of phases

Pre-game: Story Gathering and Design

Discover: This phase involves “what to do”, it’s a story or the requirement gathering phase on a currently known Product backlogs which will be shared by the Product

owner holds high level information. Each and every member of the team individually interacts with the Product owner, get the confirmed requirements or

approved requirements by continuous interactions by verification validations and review process. Once the requirement gets frozen it is estimated in terms of 8

hours chunks on each activity, which gives a consolidated effort estimate for a particular Product Backlog. For a new story board i.e. the requirement this

discovery consists of both conceptualization and analysis and for an existing story or requirement is being enhanced this phase consist of limited analysis.

The Discover phase includes the Design, on how the backlogs items will be implemented. This phase includes the architectural design of a particular backlog

which is subjected to documentation, verification validation and review of the design document.

Game: Code/Interface development, Testing and Deployment

Development Sprints:

This phase is followed on the approval of the Design document where the team starts developing the Interface. Once the code development of the product

backlog has been completed it will be subjected to verification, validation and review process with stakeholders from the client side. This code development is

accomplished by thorough unit test by individuals responsible for that Product/Interface. The Deployment of Product backlog will be executed based on

documentation of an appropriate build case followed by the manual verification of the entries in the document constructed by the individual. There are multiple,

iterative development sprints/cycles that are used to evolve the system.


Post-Game: Supporting Functions

Post-Game activity of Development & Deployment phase is supporting functions where the MAALBS employs the ITIL process which comprises of Operations,

Knowledge & Continuous service improvement.

Discover – Story Gathering

Phase Gate IN Process Phase Gate OUT High level requirements will be

shared in brief through

PowerPoint, Excel or

Documents.

The product owner will prioritize the product from the product backlog and

provide the details to the MAALBS team.

In sprint planning meeting the team will analyze the requirements like business

requirement document, functional requirement document for all the prioritize

product and scope it for the upcoming Sprint. The products which cannot be

agreed to complete in the sprint will be directly pushed back to the product

backlog with proper justification provided to the product owner like

requirements (BR/FR) not signed-off, huge estimates due to report complexity,

resource capacity, etc.

Approved Business/Functional

requirement

Document

Design

Phase Gate IN Process Phase Gate OUT

Approved Business/Functional

requirement document

MAALBS team starts work toward the initial design of the

product/Interface if more than one approach has been suggested to

Design the interface ,all the approach options are properly documented

in Technical design document (TDD) and the approach which will be

followed get it singed-off in order to avoid the confusion at later stage

Approved Technical design document


Development


Approved Technical design

document

The development activities are sub-categorized into multiple task/steps

as per the level of estimates (LOE) shared to the product owner and

each task/steps are carried out sequentially like Code development,

Report development, application/interface development etc. Each

task/step will have to go through verification, validation and review

before the start of the next task.

Develop verify validate review Develop

The product owner get a frequent update on the progress of

development activities in “Daily breakfast meeting” from the Scrum

master. The status on every day’s development activities are discussed

in “Daily SCRUM meeting” among the team members and Scrum

master

Workable Product

Testing

Phase Gate IN Process Phase Gate OUT Workable Product MAALBS team takes the sole responsibility of constructing the test

cases and test plan in line with business requirements. The product is

tested for each and every functional clauses the expected and actual

results are captured

Test Case Results


Deployment


Deployable document The Deployment phase bridges the gap between the MAALBS

Development team and MAALBS support. The MAALBS Development

team construct the deployable document pertains to the particular

product / Interface and checks manually checks all the entries in the

Deployable document with respect to the particular environment. The

Support uses the Deployable document shared by the MAALBS and

deploys to the respective environment say PRODUCTION

Workable Product

MAALBS -MphasiS AGIL Application Life cycle Business Services for Operational challenges

MAALBS service operation related activities is carried out by the MAALBS support team. The MAALBS support team is responsible le for following service operation

Service Desk Function

The MAALBS team is responsible for the following Service operations

Serves as a First Point of contact

Owns the logged request and ensure it is getting in line with user acceptance

Do a First level fix and First level Diagnosis

Serve as liaison between the end user and IT service provision teams

Support other IT provisions activities on need basis

Escalate to the appropriate team when things goes out of control

Plays a vital role in achieving the customer satisfaction


Incident Management

The MAALBS support team is responsible for restoring the service of the application in line with agreed SLA on the Interrupted services.

The Incident is acknowledged and the events of the incidents are recorded on a timely basis in the Incident Management tool used by the MAALBS team.

The MAALBS team tracks and updates the progress of the incident until it gets closed in line with the user acceptance.

Problem Management

The MAALBS team executes a professional approach on identifying root cause of the incident.

The MAALBS support team ensures that problems are identified and resolved.

The MAALBS support team eliminates the recurring incidents.

The MAALBS support team minimizes impact of incidents or problems that cannot be prevented.

The MAALBS team employs a strategic approach to execute a permanent fix or a work around.

These records are documented in the Knowledge management records

MAALBS Knowledge management

The MAALBS team adopts a professional approach by Gathering, Analyzing Storing and sharing the knowledge throughout the MAALBS life cycle approach.

The MAALBS support as well as MAALBS development team cross trains themselves across Process, Project. Technology to build a strong team.

MAALBS Continual Service improvement

MAALBS team adopts the continual service improvement model to efficiently manage their development as well as Service related activities


MAALBS LEAN Adoption

Optimal usage of resources by eliminate Waste

Amplify Learning through retrospectives (Create Knowledge)

Decide as Late as Possible (Defer Commitment)

Deliver as Fast as Possible (Deliver Fast)

Work collaboratively by empowering the teams (Respect People)

Deliver Quality work products inline with the internal and external stakeholders expectations (Build Quality In)

See the Whole (Optimize the Whole)


MphasiS Future Service offerings on Big Data

Mphasis provides a range of priori tized offerings to help you harness the power of Big Data. From pure technical solutions to store and process Big

Data, to blended or industry-specific offerings that combine business and technology components, we can help you overcome your biggest challenges

.

MphasiS Offering Solution Details

Analytics on Unstructured Data

MphasiS offers solutions in the areas of Unstructured Content Analysis, Text Analytics and Social Media Analytics. We enable organizations to make stronger data driven

decisions to improve Operations and better respond to customers. .

. MphasiS offers analysis on human .sentiment from social media posts to convert them into domain specific insights

MphasiS also offers solutions that are based on analysis of other unstructured content like Log files, Machine Logs, Images, etc

Integration of Structured &

Unstructured Data

Integrating unstructured types of data with other structured forms of data can lead to new insights for your business.

MphasiS offers Analytics and Visualization frameworks that blend business / industry specific knowledge with technology solutions to help clients integrate structured and

unstructured data and gain 360o insight in an accelerated manner.

. Advanced Analytics Solutions

MphasiS has applied Data Mining and Predictive Models to solve a variety of problems including Optimization, Employee Retention, Fraud prevention, and more.

Migration to a Big Data platform

( Future offerings)

MphasiS has expertise in all popular Big Data platforms, viz : a) Hadoop and its commercial distributions offered by Cloudera and IBM b) Hadoop ecosystem databases like Hive and Hbase c) Column oriented analytics databases like Vertica d) Appliances like SAP HANA, Teradata, Netezza, Oracle Exalytics, and more MphasiS offers consulting and technical offerings to enable migration to a Big Data platform : • Migration to an Appliance • Migration of entire technology platform to a Hadoop ecosystem

MphasiS leverages its proprietary technical solution accelerators to provide value-added services to clients.

Hosted Offerings

( Future offerings)

MphasiS offers hosted services in the Big Data space. Big data labs have been set up on leading technologies including : Cloudera Hadoop distribution • IBM Big Insights • HP Vertica •

Big Data Consulting Framework

( Future offerings)

From Business Case definition to Technology evaluation and Architecture recommendations, MphasiS consulting services facilitate adoption of a Big Data platform. We can

also assess unstructured data generated as part of regular business processes, and define the business value and insight they can deliver. The consulting framework

leverages a comprehensive library of artifacts which have been created by MphasiS Big Data Center of Excellence. These artifacts include :

• Business use cases

• Point of view collaterals on various Big Data tools and their application

• Questionnaires to assess existing business and technology landscape.


SMAC POC Implementation

Business Objective :

The objective of this POC is to identify the Positive and Negative comments tweaked on a specific event and suggest or recommend the business to come up with a effective decision based on the outcome of the tweak exchanged over on the .social media.

MphasiS Approach : Inline with the agility existing in the current business and technology challenges , MphasiS has adopted a framework called MAALBS -MphasiS AGIL application Life Cycle Business Services which is a blend of AGILE SCRUM + ITIL+ LEAN for effective delivery model for BIG Data Services which is a proven for short term wins which is of iterative and incremental and adopts the effective change management process for responding to the change which depends on the degree of Change request and also adopts the LEAN methodology for eliminating the waste , Amplify Learning, Deliver as Fast as Possible, Empower Teams and Build Integrity In on the deliver quality workable product..

MphasiS BIG Data technology approach :

MphasiS adopts 4A model say Acquire , Analyze ,Assemble and Act to accomplish the business and technical requirements inline with the stakeholders expectations .

Technology Stack :

Ubuntu 12.1.0 , Hadoop Version : 1.0.3 , MR Language : PIG v 0.8 , DW Database : HIVE : V0.9.0 , RDBMS : MYSQL : 5.5 , Algorithm TPE , SWN –SentiWordNet , Spell-check-GNU Aspel Library V 0.5.0.1 Cloud services : AWS , EC2 ,Clusters tested : 1 Master && 2 Slaves


MphasiS Global offices

MAALBS Big Data agile framwork

Data & Analytics

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