Watch full webinar here: https://bit.ly/38uCCUB Banking, Financial Services and Insurance (BFSI) organizations are globally accelerating their digital journey, making rapid strides with their digitization efforts, and adding key capabilities to adapt and innovate in the new normal. Many companies find digital transformation challenging as they rely on established systems that are often not only poorly integrated, but also highly resistant to modernization without downtime. Hear how the BFSI industry is leveraging data virtualization that facilitates digital transformation via a modern data integration / data delivery approach to gain greater agility, flexibility, and efficiency. In this joint live webinar session from Denodo and Wipro, you will learn: - Industry key trends and challenges driving the digital transformation mandate and platform modernization initiatives - Key concepts of Data Virtualization, and how it can enable BFSI customers to develop critical capabilities for real-time / near real-time data integration - Success Stories on organizations who already use data virtualization to differentiate themselves from the competition - Wipro’s role in helping enterprises define the business case, end-to-end services and operating model for the successful data virtualization implementations Schedule a Discovery Session to learn more about Wipro and Denodo joint solutions for Banking, Financial Services, and Insurance.

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Data Virtualization
Webinar – Accelerate digital transformation with data virtualization

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Speakers today
Jeevan Jambhulkar
Director,
Data, Analytics & AI,
Wipro
Paul Moxon
SVP Data Architectures &
Chief Evangelist,
Denodo

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Post-COVID Priorities for Banks
Revenue Generation
• Omnichannel integration for
360° view of customer
• Frictionless digital on-boarding
• Open Banking for all-encompassing
approach to customer engagement
Cost Management
• Increased use of AI for
decision making
• Operational efficiencies
through digitalization
Regulatory Compliance
• Managing regulatory
compliance costs

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COVID-19 – Accelerating the Trends
Digital transactions increased by 20%
• Mobile and online
• Accelerating ongoing changes in
banking distribution channels
Physical branches – Essential
services, but…
• Reduced hours and visits by
appointment
Multichannel integration and
cross-channel CX is critical
• Customers need and use all channels
• Mobile, online, branch, call center, etc.

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The Need for Agile
• Black Swan or not…the pandemic has highlighted many
challenges e.g.
• Employee access to needed data when working
remotely
• Small business loan programs overwhelmed systems
• UK Job Retention Scheme (Furlough Scheme)
• US Paycheck Protection Program
• Manual processing ‘broken’ due to staff shortages
• Need for unified multichannel engagement
with customers
• Breaking down silos between products

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Technology Trends – The ‘New Normal’
1 Delivering multichannel experience
to customer
• Integrating the customer data
across product silos
• Customer 360, KYC, etc.
2 Increased use of Robotic Process
Automation (RPA)
• Automating manual processing
• Exceptions escalated to person for analysis
3 Universal data access layer – Data Fabric
• Access from anywhere…to anything
(with security)
4 Dynamic data access – no code/low code

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Technology Trends – The ‘New Normal’
Governance
Empower employees within parameters to
protect the organization from risk
Mandate
Broker and orchestration with focus on innovation
Process
Fluid and iterative assemble-to-
order approach
Architecture
Secure integration fabric
with architectural guardrails
and guidance
Mandate
broker of services
Mandate
broker of services
IDEATE ASSEMBLE CONSUME
INTEGRATION FABRIC
Robotics process automation
End user Computing
Traditional data center Applications
CYBERSECURITY
Organization
Professional services organization with
versatile generalists
Private
Managed
Public
Cloud
API H H H
Source: Financial Services Technology 2020 and Beyond: Embracing Disruption, PwC

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Data Virtualization – A Data Fabric Layer
“Data virtualization
integrates
disparate data
sources in real
time or near-real
time to meet
demands for
analytics and
transactional
data.”
– Create a Road Map
For A Real-time, Agile,
Self-Service Data Platform,
Forrester Research,
Dec 16, 2015
Consume
in business applications
Enterprise Applications, Reporting, BI, Portals, ESB, Mobile, Web, Users
DATA CONSUMERSAnalytical Operational
Multiple Protocols,
Formats
Query, Search,
Browse
Request/Reply,
Event Driven
Secure
Delivery
Combine
related data into views
CONSUME
Share, Deliver, Publish,
Govern, Collaborate
COMBINE
Discover, Transform, Prepare,
Improve Quality, Integrate
CONNECT
Normalized views of
disparate data
SQL,
MDX
Web
Services
Big Data
APIs
Web Automation
and Indexing
Connect
to disparate data sources
Databases & Warehouses, Cloud/Saas Applications, Big Data, NoSQL, Web, XML, Excel, PDF, Word...
DISPARATE DATA SOURCESMore Structured Less Structured
3
2
1

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How Does It Work?
Development
Lifecycle Mgmt
Monitoring
& Audit
Governance
Security
Development
Tools and SDK
Scheduled Tasks
Data Caching
Query Optimizer
Mobile, Web, UsersEnterprise application, ESB Reporting, BI, Portals
Databases &
warehouses
Enterprise
applications
Cloud/SaaS
applications
XML, Excel,
Flat Files
Big data
NoSQL
Collaboration
Web 2.0
PDF, Docs,
Index, Email
Base
View
Base
View
Base
View
Base
View
Base
View
Base
View
Abstraction
Base
View
Data Source Layer
Derived
View
Derived
View
Unified
View
Unified
View
Unified
View
Unified
View
Customer360
View
Data Mart
View
Application Layer
Business Layer
Transformation
& Cleansing
J
J J
S J
A
JU
JDBC/ODBC/ADO.Net SOAP/REST WS

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Data Virtualization Connects the Users to the Data That
They Need
Data Virtualization allows you to connect to (almost) any data source
You can combine and transform that data into the format needed by the consumer
The data can be exposed to the consumers in a format and interface that is usable by them
• Typically consumers use the tools that they already use – they don’t have to learn new tools and
skills to access the data
All of this can be done without copying or moving the data
• The data stays in the original sources (databases, applications, files, etc.) and is retrieved, in
real-time, on demand

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Example Use Cases
Apps/API
Sales HR
Marketing
Data Science
AI/ML
Executive
DATA VIRTUALIZATION LAYER
Data Consumption
Self-Service
Analytics
Real-time
Decisions
Data Science
(ML & AI)
Data
Marketplace
K.Y.C.
(Customer 360)
Compliance
(IFRS17, GRC)
Mergers &
Acquisitions
Apps
(Mobile & web)
Data Governance, Manipulation & Access
Agility
& Simplicity
Semantic
Layer
Data
Abstraction
Real-time
Delivery
Zero
Replication
Sophisticated
Optimizations
Data
Governance
Data
Security
Data Storage & Management
Data
Integration
Logical Data
Warehouse
Hybrid
Data Fabric
Enterprise
Data Fabric
Cloud
Modernization
APIfication
(& SQLification)
Refactoring &
Replatforming
From Data Storage & Management, to Data Consumers, going through Data Governance & Security

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Poll Question: Which of the following is closest and most relevant to your current
data integration, analytical and business operation needs?
Hybrid & multi-cloud use cases : real-time data integration and access across the enterprise
landscape for analytics purpose
Logical Data Warehouse : Data integration, access from the traditional data warehouses and new
age data warehouses / data lakes across the enterprise
Real-time integration of internal and external data sources and systems for business consumption
applications / BI Tools
Real-time integrated view of enterprise data across multiple source systems / OLTP systems for
business operations
Mergers and Acquisitions initiative : Real-time data integration to build single view of business
data from business entities/companies (or) Data integration and access from multiple
transactional apps due to acquisitions or group companies
1
2
3
4
5

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A Glimpse of how we helped our Customers with successful Data
virtualization Implementation
Success Story - For a leading medical device manufacturer in US
Business & IT drivers:
• Daily company wide sales report delayed by 24 to
48 hours & Delayed management reporting
• Business & customer data stored in multiple
ERP, CRM systems and legacy applications
• Integrating data from different sources
(on premise and cloud)
• Providing ad-hoc access to the data
lake for business users
How Wipro Helped:
• Build data fabric using Denodo to link
machine learning, ad-hoc analytics and
visualization to source data systems
• Data delivered through the fabric, to
consumers, by web services
• Data from different system harmonized
in Denodo with canonical models
• Unified data platform ensures visibility to
CRM and ERP systems & integrated
reporting/analytics capability
Solution highlights:
• Denodo enabled unified data platform across multiple
CRM & DB’s
• Near real time access (< 2 hours) to data
• Finance could publish consolidated sales reports to
management on same business day
• Centralized data governance
and security through the unified
layer of Denodo
• 50%-time savings over
traditional ETL projects

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Success Story – Architecture Roadmap
End-to-end
Business Processes
Source Systems
Map to Business
Functions
Data Virtualization
Unified Data
Platform
Data Catalog
Data Governance
Data Access
Data Fabric/Business
Semantic Layer
Product Lifecycle
Management
Hire to Retire
Record to Report
Source to Pay
IT Strategy to
Operations
Market to
Opportunity
Quote to Cash
Plan to Forecast
Plan to Deliver

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Data Virtualization - Lessons Learned
Best Fit Use-cases
• Real time data access
• Self-service data exploration
• Real-time query optimization
• Read and write back
• Data Blending
• Data Federation
• Data Masking & Data Quality
• Data Governance
• On-Premise to Cloud
Pitfalls
• Not an ETL replacement
• Not ideal for multi-pass
data cleansing
• Need customization for
Marketplace use cases
Misconceptions
• It is not ETL
• It is not Data Visualization
• It is not a physical database

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• Extensive usage for
Regression test
execution facilitating
DevOps, CICD
methodologies
• 100% Data validation
with complete
coverage on Test
cases, test execution,
data
• Batch execution –
Scheduler to trigger
test execution with no
manual intervention
Wipro’s transformation
tool
• Identification of
Integration patterns to
automate Integration
creation in bulk
• Provides UI to
configure & operate
• Design pattern based
approach to automate
the development
• Analysis & migration
• Reference
Architecture
• Implementation
approaches
• Review check list
• Learnings, Possible
mitigation options
• Common problems,
solutions
• Re-usable frameworks
Customer 360
• Leveraged Banking
Customer Data Model
• Leverage
Communication
Customer Data Model
Asset 360
• Leverage Asset Data
Model
Leverage Wipro’s in-house accelerators and frameworks for
speed up delivery
NextGen DI™ Cook BookUnified Framework Smart Data Validation

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Data Landscape Modernisation – Wipro’s experience and capabilities
Appliances, Data Warehouse
ERP based BW Modernization
Data Marts & Enterprise Data Warehouses
Third Normal or De normalized EDWs
ERP Based Business Warehouses
CDRS SmartPro NextGen DI IQNxt Compiler Works IntelliProc BD2DB
Wipro can help you
unshackle and achieve
“Data Modernization”
by focusing on
3 key areas
Migrating from as-is
state to to-be state
leveraging Wipro tools
and accelerators
As-is State
To be State
Accelerators
Upgrade to on-
premise databases
Cloud selection –
IaaS, SaaS, PaaS
Database
Freedom
OLTP Application DBs
Structured data Metadata: Tables,
Views, Schemas etc.
Digital Database
Modernization
NoSQL, Grab DB
Metadata: Tables, Views,
Schemas etc.
Reduction in Data
Centers and IT
Services up to
80%
Build new business
functionality FASTER
3-5x
Annual OPEX
reduction up-to
80%
Increase in
speed by
2-3x
3 year TCO cost
saving up-to
92%

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Multi-Cloud Integration with Data Virtualization
BigQuery
Google Cloud
Storage
Snowflake
Amazon RDS
Amazon
Elastic
Amazon
Redshift
S3 Azure SQL
HDInsights
On-Prem
Data Centre
Manage cloud and on-premises security from
a single point
Track cloud usage by department or individual.
Enable migrations from on-premises to cloud
sources, with no impact on day-to-day operations
Scale the solution only as needed, to hold down costs
Integrate data from silos within data lakes, from
cloud and on-premises sources simultaneously,
from SaaS applications, and other sources,
without replication, in real time
Reduce the inherent latency of accessing data
from network sources

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Data Marketplace - Context
Data Marketplace is a “shopping interface” where data services are presented which can be used by data users, to find best-fit
data that meet their needs. It enables better business and technology collaboration
Simple platform that obtains data
from across the Ecosystem
Curation: it selects and qualifies data sets,
describes each data set, and collects and
manages metadata about the collection
and each individual data set
Creating a faster, easier way to
find and access data
Categorization: It organizes the marketplace
to simplify browsing. Example, a researcher
seeking health data doesn't need to browse
through unrelated data sets about customers,
employees, or other data
Cataloguing: It exposes data sets for data
shoppers, including descriptions and metadata.
It is a view into the inventory of curated data
sets. Rich metadata and powerful search are
important catalogue features
Confidentiality: Data consumers actively
participate in reporting any anomalies in
cataloguing, curating, and categorizing
data. It continuously improves the quality
and value of the available data
Solution principles
• Design-led Agile Approach
• User based Designed UX/UI
• Accurate, Relevant Data-sets
• Designed Data Flows, Info Architectures
• Metadata tagged Data
• Relevant Search
• Crowdsourced Insights
User & business driven service design
• Intuitive Searches
• Platform that leverages APIs and
Microservices Toolkits
• Data Security and Access
Management Rules
• Interfacing with Multiple Tools
Data & platform Underpinning
• Business Analyst
• Data Science Experts
• User-driven Collaboration
Community

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Data Marketplace - Architecture
Data Consumers
Data Marketplace
PortalSources
Database,
Enterprise Data
Warehouse
Enterprise
Application Data
DV Layer
Publish Data Services
Combine Transform, Mashup
Data Catalog
Governance
Optimizer
Cache
Metadata
Schedule
Security
Views Data catalog
Enterprise datasets
Data viewing
Access management
Collaboration, sharing
End Users
Business Analysts
Reports / dashboards

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Q A

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Thank you for your time.
Denodo Datafest was a great Success.
Embed intelligence within your organizations with our
joint solution offering. Reach out to below address to
schedule a demo and discovery session
Ask.analytics@wipro.com