Optimizing Your Big Data Environment to Maximize Your SAP Investment

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 The 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


Customer Value

Information Delivery Information 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

CR

M

ER

P

HR

O

ther

Mobile

Self-‐Service

Social Media

Volume Variety Velocity Sources

Internet

Cloud

Identify Organize Act Acquire

Use Case Analyze

Information Landscape Transformation The “New Normal” facing today’s data driven Organizations


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


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


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

DATA V

OLU

ME

PE

RFO

RM

AN

CE

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


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


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 .


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

Date post:	08-Sep-2014
Category:	Technology
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Optimizing Your Big Data Environment to Maximize Your SAP Investment

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