Managing Data Quality, Masking and Warehouse Optimization

In collaboration with
Business redefined – managing
information explosion, data quality
and compliance
Malay Baral, Lead Data Management CoE, Capgemini
Informatica World – May 13, 2014

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Copyright © 2014 Capgemini. All rights reserved.
Informatica Solutions leveraging the power of Cloud | Malay Baral | May 13, 2014In collaboration with
TABLE OF CONTENTS
Introduction
!  Data-Quality-as-a-Service
!  Data Masking
!  Data Warehouse Optimization using Hadoop
!  Contacts

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Overview
We strengthen our Informatica partnership with new data management solutions:
Capgemini and Informatica offer a data quality service that gives you the benefits of SaaS yet is
completely customizable.
Data-Quality-as-a-Service
Making your data masking implementation scalable and repeatable across the enterprise –
completely safe and highly cost-effective.
Data Masking:
DWO optimizes the ratio between the value of data and storage costs, making it easy to take
advantage of new big data technologies.
Data Warehouse Optimization using Hadoop

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TABLE OF CONTENTS
!  Introduction
Data-Quality-as-a-Service
!  Data Masking
!  Contacts

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Data Quality is not a one-time activity…
EvaluationExecutionCreationPlanning
Organizations on average run 2 to 4 promotional
campaigns a month.
However the Customer Data used for the
campaign is plagued with Data Quality issues –
poor names data, poor address / contact
information.

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Ranking of Barriers to Adoption of
Data Quality
Organizations feel constrained in solving the Data Quality
conundrum…
High cost of dedicated Infrastructure
Pricing Model may
not be viable
Lack of Skills or
Costly Resources
Organizations feel that either the program is
going to be too expensive or they lack skills to
execute such a program or both
Source: The State of Data Quality Revisited April 2013 Information Difference Research Study
20%
20%
22%
22%
We do not have the right
skill sets
It would be too expensive
2013 2009
Constraints
For every cycle customer data goes through the repeatable quality process of – Select, Profile,
Cleanse, Prepare.

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What if there was a viable option…
Use of the scale of cost
Tap into Rightshore®
Resourcing Model
Pay for what
you use

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Organizations will find it seamless to work with…

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What we offer is something unique…
Industrialized Delivery Process
T-shirt sized pricing model
Multi-tenant
Cloud architecture
Basic and
Premium Service
Catalogue
Industry Leading Data
Quality Tools
Security as good as on premise
solution
Get High Quality data the way you want

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TABLE OF CONTENTS
!  Introduction
Data Masking
!  Contacts

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Data Security Scenario: eCommerce Business
“ I am an Ecommerce
customer and often wonder
about the privacy & security
of my personal & card
details which I
furnish online…”
“ I am an Ecommerce
IT manager involved in an
software upgrade project for
which I need realistic
customer data
for testing …”
Customer IT/ Ecommerce Manager
Concerns…
!  Are my personal information like name, SSN, Address,
phone number & email address safe and secure?
!  Is my credit card information safe?
!  Is there a chance of any of the above information being
stolen or misused?
Concerns…
!  I would want to have access to realistic customer data
for testing without compromising compliance
!  I want an integrated view of test data across
applications to simulate production scenarios
!  I need to maintain my customer’s faith & confidence on
security of their personal information.

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Capgemini POV: Data Masking Solution in an Ecommerce
Landscape
Masked Environment
Ecommerce Website
Business
Applications
I hope I am safe while
providing my card &
personal details online
Transformer
DM Request
Profiler
Metadata
Analyzer
Management
Reports
Reference
Data
Dev QA
Centralized
Masking DB
IT/ Ecommerce Manager
Production Environment
Capgemini’s DM Solution
Direct Load
Centralized Load
Customer
I have access to masked
data…so no fear of
theft or misuse.
I can shop without
any fear of data theft
Capgemini’s DM solution enables organizations
to have realistic operational data without risking
data theft & non compliance
Dynamic/Onthefly
Maskingbasedon
entitlements
TokenizationofCard
details
Customer

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Detailed Solution: Data Masking Solution Architecture
Capgemini’s Data Masking Solution can provide a cost effective & efficient solution for business applications
like Ecommerce where customers share sensitive information online & there is a threat to the data security.
Target Staging Area
Development and Runtime Components
DM Engine – ETL Suite Metadata Engine
Unmasked
DataProd/
UAT
DataMasking
Engine
Masked
DataDev./
QA
Source Staging Area
Application Databases Files
ETL Repository
Analysis & Design
Engine Repository
Informatica
PowerCenter
ILM Suite
Messages
FilesApplication Databases Messages
Production
Metadata Operations Engine
Masking
Algorithms
Data
Dictionaries
Metadata
Database
Profiler Test Data Generator Job Scheduler
Reusable components

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Capgemini Data Masking Solution Highlights & Key Benefits
Our thought leadership on driving data masking via a metadata based approach vis-à-vis traditional tool
based approach.
Save…
!  Cost savings ~ 40% via the use of ETL
tool vis-à-vis off-the-shelf masking tools
!  Reduced effort ~ 25% by using
Capgemini developed metadata and
related accelerators.
Solution
Highlights
Accelerate…
Transform…
!  Establish Data Masking as a shared service
across business functions
!  Ensuring Central execution via CoE brings in
cost and effort savings
!  Establishing an independent in-house
business charge-back function for ease on-
boarding and maintenance.
!  Standardized delivery across each phase of SLDC
!  Leverage repository of 8+ ready to
plug and play tools
!  100+ man years of expertise
on global delivery.

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TABLE OF CONTENTS
!  Introduction
!  Data Masking
Data Warehouse Optimization
using Hadoop
!  Contacts

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Business Case: Managing the explosion of data within the
enterprise and outside
!  Need for better customer data insights which
goes well beyond the present data set to include
historical data.
!  Need to have a consolidated view of customer
information which includes:
•  Structured data
•  Unstructured data
!  Need to optimize use of Data Warehouse
environment.
!  Major challenge for a data manager to ensure
data is archived properly
!  Need to ensure how quickly the customer data
can be retrieved for analysis
!  Need to manage unstructured or semi-structured
customer data from various sources e.g. social
data, geospatial data.
CIO Data Manager
My marketing manager
is not happy with the
limited view of customer
information
The business demands
accurate reporting &
intelligence on extended
customer data
My Total Cost of
Ownership for the Data
Warehouse environment
has now exceeding my
allocated budget
I have huge volumes of
customer data to manage.
Can I archive it properly for
future retrieval?
How do I manage
customer data from
multiple social applications
& external data sources?

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Our approach to Data Warehouse optimization using Hadoop
Virtual
Layer
/
IDS

Offload ETL
to Hadoop
Customer Data
Source: CRM,
Social Data and
other Customer
touch points
Business Intelligence
Cloudera’s complete, tested and
widely deployed open source
distribution of Apache Hadoop makes it
available for mainstream adoption
DW
Marketing
Manager
Data Manager
Appfluent Visibility Reports
Data Archive / Restore
Efficient Data
Archiving Process
Able to store large volume
of Customer data (social
data, historical data etc.)
Customer insight from
present as well as
archived data
What to archive?
Data Archive
Big Data
Appfluent Visibility to identify dormant
data to be archived by monitoring data
usage and analyzing activities.
Informatica ILM
Archive to archive
data on Hadoop with
compression.
Informatica Data Services to
build virtualized data objects
combining data from DW
Appliance & Hadoop
Informatica BigData edition to create
ETL/ELT (including complex
transformation, DQ Rules, Profiling,
Parsing & Matching) framework and
push all heavy lifting ETL/ELT
processing to Hadoop environment.

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Our Solution: Data Warehouse Optimization (DWO)
Business
Intelligence
Layer
Semantic
Layer
Data Sources
DB Files
Data Warehouse Layer
Data Warehouse
Data Services
ETL/ELT
Together with Informatica, Cloudera and Appfluent, Capgemini has developed an integrated solution
that allows OLTP systems and DWs to serve their primary functions efficiently and cost-effectively.
!  Informatica ILM Archive to
archive data on Hadoop with
compression
!  Informatica Data Services to build
virtualized data objects combining
data from Teradata & Hadoop
!  Informatica BigData edition to
execute data integration
transformations, data quality rules,
profiling, parsing, and matching all
natively on Hadoop
!  Appfluent Visibility to identify
dormant data to be archived and
ETL/ELT processes to be offloaded
by monitoring data usage and
analyzing activities
!  Cloudera’s complete, tested and
widely deployed open source
distribution of Apache Hadoop,
makes it available for mainstream
adoption
Big Data Edition
ET/ELTL
Life Cycle
Management
Enterprise Data
Hub
Profile Parse ETL
MatchCleanse
DataArchive

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Key Value Propositions
DWO with ILM enables clients to take full advantage of big data technologies to optimize the ratio between
the value of data and its storage costs, while also gaining extended capabilities to handle complex data and
providing users with a richer analytical experience.
Save…
!  Infrastructure costs ~ Commodity
hardware and software is used for archived
data, lowering infrastructure costs
!  License costs ~ License costs for existing
data warehouses are reduced because less
data needs to be stored there.
Solution
Highlights
Accelerate…
Transform…
!  Build on the technology you already have,
rather than replacing or recreating it
!  A single abstract layer – supports any future BI
visualization tools, makes it easy to add
information in future
!  No change to the business definitions and
programming logic of the existing BI structure.
!  Unstructured and structured data combined for
inclusion in report
!  Better data security and governance.
!  Optimum performance by
Intelligent archiving.

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TABLE OF CONTENTS
!  Introduction
!  Data Masking
Contacts

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Contact us to arrange a demonstration
Malay Baral
Head of Data Management CoE
malay.baral@capgemini.com
Srikant Kanthadai
Global Head of Data Management
srikant.kanthadai@capgemini.com

The information contained in this presentation is proprietary.
Rightshore® is a trademark belonging to Capgemini.
www.capgemini.com/bim
About Capgemini
With more than 130,000 people in over 40 countries, Capgemini
is one of the world's foremost providers of consulting, technology
and outsourcing services. The Group reported 2013 global
revenues of EUR 10.1 billion.
Together with its clients, Capgemini creates and delivers
business and technology solutions that fit their needs and drive
the results they want. A deeply multicultural organization,
Capgemini has developed its own way of working, the
Collaborative Business Experience™, and draws on Rightshore®,
its worldwide delivery model.

Managing Data Quality, Masking and Warehouse Optimization

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