In this age of big data, new technologies and methods have evolved and matured to the point where organizations are able to store and exploit the increasing volume, variety, and velocity of data and achieve true actionable intelligence to increase profits, enhance operational efficiency, and gain a competitive edge in the marketplace. Today’s business leaders are increasingly demanding integration with external sources such as social media, the Internet of Things, and data provided by third parties, in order to derive these meaningful and actionable insights. Capgemini has a proven track record of assisting our customers exploit emerging technologies (such as Hadoop) together with their existing investments in advanced, in memory data platforms (such as SAP HANA) to create an optimized Big Data Environment that helps the organization achieve significant additional value from their data in return for relatively modest additional capital investment. By optimizing the environment and leveraging new technologies to compliment and extend the reach and capability of existing solutions, we help extend the value, reach, and capability of these existing investments and provide our customers with a richer analytical experience. Join Capgemini to learn how we can assist SAP customers design and implement a robust reporting and analytics infrastructure that will transform big data into intelligence and intelligence into action. Presented at SAPPHIRE NOW 2014.

1. Proprietary & Confidential
Optimizing your Big Data environment
to maximize your SAP investment
The information contained in this document is proprietary.
Copyright © 2014 Capgemini. All rights reserved.
Steve Stone – Capgemini Advanced Solutions Leader (NA
Business Information Management)
Scott Schlesinger – Senior Vice President; NA Business
Information Management Leader

2. 2The information contained in this document is proprietary. Copyright © 2014 Capgemini. All rights reserved.
What is transpiring in the market?
Exclusive Research
from CIO magazine JANUARY 2014
2014 State of the CIO
SURVEY
1

3. 3The information contained in this document is proprietary. Copyright © 2014 Capgemini. All rights reserved.
Customer
Value
Information DeliveryInformation Supply & Integration
Project-­‐Marts
Project
Data
Project
Data
Project
Data
EDW
Supplier
Product
Customer
Finance
Subject
Area
Data
Other
Other
Sandbox
TransAct
Data
Staging
&
PSA
ODS
Information Management
Program & Data Governance Master Data Management Data Quality Framework
CRMERPHROther
Mobile
Self-­‐Service
Social
Media
Volume
Variety
Velocity
Sources
Internet
Cloud
Identify Organize ActAcquire
Use Case
Analyze
Information Landscape Transformation
The “New Normal” facing today’s data driven Organizations

4. 4The information contained in this document is proprietary. Copyright © 2014 Capgemini. All rights reserved.
What is the driving force for this New Normal?
Data explosion - creating opportunities to leverage Hadoop to offload data:
Increased costs to store and use large volumes of data (structured, semi-structured,
and unstructured)
• Wal-Mart handles more than 1 million customer transactions every hour,
which is imported into databases estimated to contain more than 2.5 Petabytes of data.
• More than 5 billion people are calling, texting, tweeting and browsing on mobile
phones worldwide
• 100 terabytes of data uploaded daily to Facebook
• According to Twitter's own research in early 2012, it sees roughly 175 million tweets
every day, and has more than 465 million accounts.
Desire (inability) to look forward - creating opportunities to use new data leveraging
Advanced Analytics
• Life Sciences organizations want to reduce the time to market of new, effective, safe drugs.
However, clinical trial data, drug efficacy data, and market data is generally stored in
various formats in various systems challenging their ability to make valid data correlation
and effective, predictive results
• Retailers want to understand and predict how a new product will sell in a new market.
However, all too often there is no efficient means to organize distributed social media data
and couple with sales and demographic data to predict product performance

5. 5The information contained in this document is proprietary. Copyright © 2014 Capgemini. All rights reserved.
What does a truly Optimized Environment offer?
Efficiency of
data storage
Reduced investment in
simply storing data
Increased Analytics
and insights
Moving data to online
storage where it is
accessible in its various
forms
Offloading select data
from legacy storage
mediums and platforms to
low-cost, commodity
hardware
Combining structured and
unstructured data to drive
innovation thru analytics
Benefits
! Substantial Data Storage Cost Reduction freeing up funds to use for high value Analytics (self funding projects)
! Remove data from cold storage (tape) and make available for analysis
! Significant performance gains to your legacy environment
! Ability to perform analytical functions that were previously impossible leveraging existing and newly captured data
! Unlock significant untapped Business Value
Data
Optimization

6. 6The information contained in this document is proprietary. Copyright © 2014 Capgemini. All rights reserved.
HANA is a key Component of an Optimized Data Strategy
HOT
• Data is read and/or written frequently
• In-Memory
• All HANA features can be leveraged
• Recent Postings, Real Time
Analytics, Management
Reports, etc
WARM
• In-frequent access
• No need to keep in memory all the time
• All HANA features can be leveraged
• Older content - prior year
Management Reports, yearly
or quarterly data
COLD
• Sporadic access
• Data stored outside HANA – NLS
storage
• Features limited by NLS capabilities
• Sporadically accessed video
content, data archived for
older years etc
DATAVOLUME
PERFORMANCE
As
an
extension
of
a
BI
Strategy,
this
approach
allows
for
the
inclusion
of
unstructured
data,
leveraging
technologies
such
as
Hadoop
and
HANA
as
the
In-­‐Memory
platform
for
most
of
the
critical
analytics,
while
less
expensive
platforms
could
be
leveraged
for
“colder”
data
and
analytics.
Examples

7. 7The information contained in this document is proprietary. Copyright © 2014 Capgemini. All rights reserved.
Utilities/Energy
Companies:
" Looking to move from
Smart Meter to Smart
Charging for load
balancing. Time & Load
based charging &
notification
" Proactive Customer
Intervention based on
load prediction to reduce
need to turn on “peakers “
" Predictive Asset tracking
and management
Business Use Cases Across Various Sectors
Organizations of all types and of all sizes are thirsting for knowledge and need new means
to acquire, store, organize, optimize data
Telecommunication
Companies:
" Analyzing call data records
in real time to identify
fraudulent behavior as well
as Churn triggers
immediately
" Tailoring marketing
campaigns to individual
customers using location-
based and social
networking technologies
" Using insights into
customer behavior and
usage to develop new
products and services
Life Sciences
Organizations:
" Desire to reduce the
time to market of new,
effective, safe drugs.
However, clinical trial
data, drug efficacy data,
and market data is
generally stored in
various formats in
various systems
challenging their ability
to make valid data
correlation and effective,
predictive results
Retailers:
" Desire to understand and
predict how a new product
will sell in a new market.
However, all too often
there is no efficient means
to organize distributed
social media data
and couple with sales and
demographic data to
predict product
performance
SAP HANA
0.0 sec
Instant Results
+ =
HADOOP
Infinite Storage
Real Time Business
Results from Big Data

8. 8The information contained in this document is proprietary. Copyright © 2014 Capgemini. All rights reserved.
HANA Use Cases – Ask yourself: What could make a difference?
SAP
HANA
• Sales Analysis
• Channel Performance
• Segmentation
• Product Launch
• Market Intelligence
• Contract & Revenue Mgmt.
Commercial
Analytics
Big
Data
and
Analytics
• Predictive Asset Maintenance
• Trade Analytics
• Sentiment Analysis
• Products Online
• Personalization
Supply
Chain
• Collaborative demand
reconciliation
• Multi-level inventory optimization
(SmartOps)
• Increased forecast/planning
frequency
• Scheduling simulations/modeling
• Sales & Operations Planning
Finance
• Order to cash
• Minimum margin notifications
• DSO by product or service
• Profitability/margin (COPA)
• Financial close
• Management Reporting
• Forecasting / Planning
Quality
• Complaint tracking
• Product/material analysis
• Supplier performance
• Scrap Cost Management
• Yield Analytics
HANA
can
provide
the
central
platform
capability
to
support
new
as
well
as
complex
analytics
.

9. 9The information contained in this document is proprietary. Copyright © 2014 Capgemini. All rights reserved.
Amazon Cloud
Dashboard &
Analytics tools
Source ERP/
Datawarehouse
Solution
Mobile Apps &
Enablement
In-memory
Analytics
Accelerator
(HANA)
Data
Loading &
Integration
AWS S3
File
System
Datamart
Capgemini’s Elastic Analytics is an end-to-end cloud
solution that enables you to benefit from advanced
analytics via Amazon Web Services (AWS).
Get Immediate Business Insights – from Strategy to Execution in minutes
using a Cloud based solution to quickly see “the art of the possible”
Benefits:
" Can be made available
within minutes
" Robust enterprise-ready platform
" Pay only for time used, no
infrastructure costs, and no lead-
times
" Supports many leading
BI software solutions
and so can have same
look and feel as your
own data center
" Completely scalable to
meet the demands of
the business