Business Redefined – Managing Information Explosion, Data Quality and Compliance

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, 2014 In 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 !  Data Warehouse Optimization using Hadoop !  Contacts

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Data Quality is not a one-time activity…

Evaluation Execution Creation Planning

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 8 9 0

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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-Quality-as-a-Service

Data Masking !  Data Warehouse Optimization using Hadoop !  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

Tran

sfor

mer

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

Dyn

amic

/On

the

fly

Mas

king

bas

ed o

n en

title

men

ts

Toke

niza

tion

of C

ard

deta

ils

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

Unm

aske

d D

ata

Prod

/U

AT

Dat

a M

aski

ng

Engi

ne

Mas

ked

Dat

a D

ev./

QA

Source Staging Area

Application Databases Files

ETL Repository

Analysis & Design Engine Repository

Informatica PowerCenter

ILM Suite

Messages

Files Application 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-Quality-as-a-Service !  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

Match Cleanse

Data A

rchive

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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-Quality-as-a-Service !  Data Masking !  Data Warehouse Optimization using Hadoop

Contacts

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Contact us to arrange a demonstration

Malay Baral

Head of Data Management CoE [email protected]

Srikant Kanthadai

Global Head of Data Management [email protected]

The information contained in this presentation is proprietary. Copyright © 2014 Capgemini. All rights reserved.

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.

Technology

Business Redefined – Managing Information Explosion, Data Quality and Compliance