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Maart 2021

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IBM’s statements regarding its plans, directions, and intent are subject to change or withdrawal without notice and at IBM’s sole discretion.

Information regarding potential future products is intended to outline our general product direction and it should not be relied on in making a purchasing decision.

The information mentioned regarding potential future products is not a commitment, promise, or legal obligation to deliver any material, code or functionality. Information about potential future products may not be incorporated into any contract.

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Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will experience will vary depending upon many factors, including considerations such as the amount of multiprogramming in the user’s job stream, the I/O configuration, the storage configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve results similar to those stated here.

Herman Nielens hij/hem/zijn

Data & AI Architect, IBM Technology

@hnielens linkedin/twitter/github

Herman Nielens werkt bij de IBM Technologie divisie als Data & AI Architect. Hij beraadt nieuwe en bestaande klanten én partners in België en Luxemburg over de integratie en het gebruik van IBM’s Data & AI oplossingen.

Herman is sinds meer dan 20 jaar actief in het domein van AI, data & analytics, voorheen bij DHL Express Benelux en sinds 2009 bij IBM.

Telenet, UCB, Umicore, de Federale en Vlaamse overheden en het Luxembourg Institute for Science & Technology zijn maar enkele van zijn klanten.

The AI Ladder

CONNECT & COLLECT - Make data simple and accessible

ORGANIZE - Create a business-ready analytics foundation

ANALYZE - Build and scale AI with trust and transparency

INFUSE - Operationalize AI throughout the business

AI

MODERNIZEMake your data ready for an

AI and hybrid cloud world

One Platform, Any CloudTalent &

Skills

IBM Cloud / September 2019

Agenda

• The Journey to Cloud

• IBM Cloud Paks

• Cloud Pak for Data

• Demo

5

IBM Cloud / September 2019

Agenda

• The Journey to Cloud

• IBM Cloud Paks

• Cloud Pak for Data

• Demo

6

Share of organizations using a mix of cloud models

Share of enterprises using more than one public cloud provider 67%

A real-world look at multicloud

Movement between clouds 73% priority

concernConsistency of management 67% priority

concernConnectivity between clouds 82% priority

concern

Traditional IT

Public clouds and SaaS

Private clouds

Dedicatedclouds

Sources: IDC Cloud Forecast; BCG & McKinsey

Hybrid and multicloud are the new normal

94%

Modern Cloud Technology is based onContainers and Kubernetes

Container Runtime

Container Runtime Container Runtime

Container Runtime

Container Runtime Container Runtime

LegacyCalculator

App(monolith)

IN : A, BOUT

C = A+B(microservice)

ModernCalculator

App(microservices)

LegacyCalculator

App(monolith)

Kuber... what-now?

https://www.youtube.com/watch?v=0qotVMX-J5s&feature=emb_rel_end https://www.youtube.com/watch?v=kBF6Bvth0zw&list=

PLOspHqNVtKABAVX4azqPIu6UfsPzSu2YN&index=7

https://www.youtube.com/watch?v=KTN_QBuDplo https://www.youtube.com/watch?v=YVTkfqUbkJY&feature=youtu.be

https://www.youtube.com/watch?v=cTPFwXsM2po

https://www.youtube.com/watch?v=aSrqRSk43lY&list=PLOspHqNVtKABAVX4azqPIu6UfsPzSu2YN&index=1

Why Containers and Kubernetes technology?

• Portability• Scalability• Modularity• High Availability• Open Source, Community• Eco-system• Efficient

Enables • Immutability• Reproducibility• Manageability• Microservices

Makes developers more productiveMakes systems more resilientMakes resource more efficientMakes processes more automated

Provides

75% Reduction in operations expense84% Increase in speed to market60% Increase in number of projects IT Admins can handle

Source: Ovum, Delivering Business Value through Transitioning from Managing VMs to Orchestrating Containers

ForIT

For the User

IBM Cloud / September 2019

Agenda

• The Journey to Cloud

• IBM Cloud Paks

• Cloud Pak for Data

• Demo

11

Build once. Deploy anywhere.

IBM + Red Hat - industry’s only true hybrid multi-cloud platform

Traditional workloads

AWS Microsoft GoogleIBM + Red Hat

Limitedfeature

support

Azure Stack GoogleAnthos

Limited feature

support

PublicCloud

PrivateCloud

Traditional on-premises

Limited connectivity in

storage/data movement

Connectivity confined to

Microsoft products

No connectivity 𝙓

Extensivemulticloud governance/mgmt.

↻

IBM Private Cloud

OpenShiftOpenShiftAWS Azure OpenShiftGoogleCloud

OpenShift AWS Outposts

IBM Public CloudOpenShift optimized

SaaSPaaSIaaS

+ IBM Cloud

Satellite

Cloud Paks – Pre-integrated for cloud use cases

IBM Cloud SystemsEdge Private

Cloud Pak for Security

DevOpsTools

Developer & DevOps Tools

ModernizationToolkit

Frameworks and Runtimes

Cloud Pak for Data

Organize Analyze

Collect

Cloud Pak for Integration

API Lifecycle

Messaging and Events

App and Data Integration

Cloud Pak for Automation

Workflow and Decisions

Operational Intelligence

Content

Cloud Pak for Multicloud Management

App and Infrastructure Hybrid Environment

Security and ComplianceManagement

Incident Response

Federated Search and

Investigation

Security Orchestration and Automation

AWS MS Azure Google Cloud

Open Hybrid Multicloud Kubernetes Platform

Cloud Paks – IBM certified and production-readySp

eed

to m

arke

t

Enterprise security

Containerizedsoftware alone

Cloud Paks

Containers AloneClient creates containersor receives software as standalone container(s)

IBM Cloud PaksComplete solutions

certified forenterprise use cases

Runs anywhere Yes Yes

Vulnerability scanned Yes Yes

Red Hat container certification Depends on product Yes

Complete solution w/ container platform No Yes

Flexible & modular: Pay for what you use No Yes

IBM certified/orchestrated for production(Built for Kubernetes by experts; certified against 250+ criteria)

No Yes

Multicloud validation No Yes

Integrated deployment experience No Yes

Full stack support by IBM(Base OS, software, and container platform) No Yes

License metering integration No Yes

Scalable and resilient No Yes

Encrypted secrets / limited privileges Do it yourself Yes

Management and operations Build your own Yes

Lifecycle Management Manage it yourself Yes

Use

Case

s

Discrete

Comprehensive

IBM Cloud / September 2019

Contents

• Journey to cloud

• Cloud Paks

• Cloud Pak for Data

• Demo

16

Ease of Use

One user experience that simplifies data management; versus integrating

many products

Data self-service with a unified customer experience customized

based on roles

Auto-Discovery at Enterprise Scale

Auto-discovery of data assets speeds time to value and makes any

organization a data organization

Solutions must be built to handle the data needs of any sized

organization

What the Market Demands for Data & AI

Governed & Secure

Built-in data governance to ensure the right data is always in the right hands

With public pressure around data privacy, data security and regulatory

compliance around data must be automatic

IBM Cloud

IBM Cloud provides the security and service the modern enterprise needs. Customers on the IBM Cloud can look to have their software fully managed.

With security and management in hand, working with data and AI is

more automated than ever.

Azure

Deploying on Azure brings the worldwide flexibility and resiliency to ensure your data rests exactly

where you want and accelerate your journey to AI.

Utilizing IBM services on Azure would kickstart your AI

development.

…And, it has to work on any cloud

AWS

With AWS high-performance and scalability building AI would be easier

than ever using Watson.

Bringing applications to the data would ease a lot of pain moving data and greatly accelerate the AI journey.

And, it has to work on any cloud

https://ibm.biz/Bdfjdg

https://ibm.biz/Bdfjdh

https://ibm.biz/BdfjdJ

Cloud Pak for Data

A true hybrid multicloud

strategy

Managed by IBM/Vendor

Managed by Client

Collect & Connect– Data virtualization

– Provision SQL and NoSQL databases

– Event ingestion

– Streaming Analytics

– Apache Spark

IBM Cloud Pak for Data

The AI Ladder

Analyze and Infuse– Business reporting

– Data science and visualization

– AI lifecycle automation

– AI Apps

– Industry accelerators

App Developers and SREs| Business Partners | Data Engineers | Data Stewards | Data Scientists | Business Users

Extensible: APIs, partner ecosystem, accelerators, and solutions

Integrated User Experience

Core services – User access management– Security contexts and RBAC– Volume management– Monitoring and metering

– Service provisioning– Operators– Diagnostics– Backup and migrate

IBM Cloud | Amazon Web Services | Microsoft Azure | Google Cloud | Hyperconverged system

Red Hat OpenShift

Infuse

Analyze

Organize

Collect

Organize– Data transformation,

integration & lineage– Data quality and

classification

– Policies and rules

– Data cataloging

– Self-service discovery & search

Understand and Prepare Data for Analysis

Build Descriptive, Predictive, and Prescriptive Models

Model Management and Deployment

Create Analytics Applications

Govern, Search, and Find Data

Collect, Connect, and Access Data

Connect and discover content from multiple data sources across your organization.

Provision databasesand virtualize data access.

Understand, cleanse and prepare your data to create data preparation pipelines visually.

Use popular open source libraries to prepare structured and unstructured data.

Create machine learning, optimization, and other advanced mathematical models.

Design your models programmatically or visually with popular open source toolingand IBM frameworks.

Train at scale with support for distributedcompute and GPUs.

Manage your models across non-prod and prod.

Deploy your models and scale automaticallyfor online, batch or streaming use cases with SLAs.

Monitor model performance and automatically trigger retraining and redeployment as rolling upgrades.

Incorporate trusted and governed models into applications, dashboards, and operational systems.

Grant user access and enforce business policies.

Index for search, visualize consumers and producers of assets with lineage, metrics, and quality profiles.

Find data and analytics assets in the enterprise catalog.

IBM Cloud Pak for Data

AppDeployment

Data

New Requirements& Engagement

DevelopmentTest

Monitoring &Retraining

Data Access

Acquiring Data &Self Service

Model Design & Deployment

RefiningData

Continuous Deliveryof Applications

Continuous Deliveryof Data & AI

Transforming the Delivery of Data & AI to the End Users

> Hybrid Multicloud > Quality User Experience> Security & Governance

IBM Cloud / September 2019

Contents

• Journey to cloud

• Cloud Paks

• Cloud Pak for Data

• Demo

25

Demo:CPD – Administration – User Management

26

Demo:CPD – Administration – Services Catalog

Demo:CPD – Collect & Connect – Platform Connections

28

Demo:CPD – Govern – Discovery & Data Quality

Demo:CPD – Govern – DataStage Flow Editor

Demo:CPD – Analyze – Watson Studio Notebooks

Demo:CPD – Analyze – AutoAI Experiment

Demo:CPD – Infuse – Watson Assistant powered Bankbot

https://ibm.biz/Bdfjde