1. Safe Harbor Statement
The information in this presentation is confidential and proprietary to SAP and may not be disclosed without
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All forward-looking statements are subject to various risks and uncertainties that could cause actual results
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© 2012 SAP AG. All rights reserved. 1

2. Session Abstract
As enterprises race to embrace Hadoop in its next-generation data foundation layer,
IT organizations are reexamining their current service-level commitments and
looking for ways to achieve similar levels of service with Hadoop-based landscapes.
As enterprises across industries move forward into the Hadoop led scale-first
system landscapes, SAP is also examining some fundamental must-haves that can
drive the adoption of Hadoop in the enterprise. This presentation will discuss the
dominant drivers of big data that need to be addressed in a comprehensive way.
Furthermore, this session will illustrate how SAP is bringing the value of Hadoop
and big data management through a broad portfolio from SAP /Sybase that
encompasses SAP HANA, Sybase IQ, SAP BusinessObjects EIM, SAP
BusinessObjects BI and other relevant products. It is important to recognize that
there is more work to be done to accelerate the adoption of Hadoop and big data
technologies into the traditional enterprises, and this presentation concludes with
some directions that are worth pondering further.
© 2012 SAP AG. All rights reserved. 2

3. Accelerating Big Data Value Across a
Traditional Enterprise
Non-disruptive Innovation for Enterprise IT
Yuvaraj Athur Raghuvir
Director, SAP HANA & DW Solution Management

4. Reality #1: “Yotta” Digital Universe
Yotta
Rules!
1000000000000000000000000
Yotta Zeta Exa Peta Tera Giga Mega Kilo
There is an interesting confluence of private and public data leading to
augmented reality based applications.
Source: IDC 2011 Report on Digital Universe Decade
© 2011 SAP AG. All rights reserved. 4

5. Reality #2: IT Challenges
1.5x IT Staff
will manage
Cost-effective
? ??
Hard to Answer
75x “files” Management of Questions Quickly
Large Data from Big Data
Volumes
…in the next decade1.
Indirect Link to Business
Operation
Enterprises have to gear up to manage ultra large data volumes with wafer thin
IT staff to support agile business.
1 Source: IDC 2011 Report on Digital Universe Decade
© 2011 SAP AG. All rights reserved. 5

6. # Reality 3: Integration Cost of Hadoop Like Systems
Log Files
In-Memory DB
Hadoop Enterprise
Portals
Multi-structured
Data Sources Data Warehouses
1 3 Mobile
Media and Other
Files Structured Data
2
Disk Dashboard/ Report
On Demand
Enterprise Infrastructure Services
3 Cost to Integrate &
Consume
2 Cost to Analyze &
Process
1 Cost to Collect & Store
© 2011 SAP AG. All rights reserved. Confidential 6

7. Metaphor: Contrasting Communities
Mousgoum Village, San Francisco City,
Cameroon, Africa California, USA
Teleukhas - a perfect fusion Buildings shaded according to
of form and function in an their recorded land use – a
unselfconscious culture. model for planning in self-
conscious cultures
Adoption requires insight into both communities
© 2011 SAP AG. All rights reserved. Confidential 7

8. Rezoning at San Francisco
NEARLY 25% OF SAN FRANCISCO IS UP FOR REZONING
August 21, 2008 on 10:29 am | In Fascinating Information, Government, Historic Properties, Investment Opportunities, New
Developments, Trends, Uncategorized | 10 Comments
NEARLY 25% OF SAN FRANCISCO IS UP FOR REZONING
In a bold move to accommodate San Francisco’s changing needs, the city is looking to rezone + gentrify four eastside
districts
Plan. Do. Check. Act.
http://www.socalofficerealestateblog.com/?p=239
http://www.architectmagazine.com/planning/san-francisco-digital-context-analysis-model.aspx
© 2011 SAP AG. All rights reserved. Confidential 8

9. 1. Build the Bridge
Use integration techniques to share data and query
Data Layer Integration Query Federation at Client Side
Query federation at Server Side Direct Client Connectivity
Balance between Feature First & Scale First Systems
© 2011 SAP AG. All rights reserved. Confidential 9

10. 2. Reach the Enterprise User
Contextualize to start assimilating the innovations
Discover , build and deliver the new capabilities Seek architectures that deliver scalable
value in real-time
Deliver and deploy within the Enterprise
Infrastructure
Enrich the User Experience
© 2011 SAP AG. All rights reserved. Confidential 10

11. 3. Converge the Best Practices
Democratize Use
Up-level data flow to modeling paradigms. Seamless experience for various
enterprise personas
Create a Sustainable Future
© 2011 SAP AG. All rights reserved. Confidential 11

12. Complementarity and Co-Evolution
VALUE
ERP / Operations Apps Analytics
Data + Processing Platform
MPP “NoSQL”: Extending on
SQL / MDX / Extensions / Engines Frameworks SQL
Modeling
Data Warehouses
Structured Data
Unstructured
Disk
• Feeds • Sensor Data
• Media • Others…
Data Movement / CEP / Data Quality & Governance
Non-disruptive Innovations that renovates the landscape
© 2012 SAP AG. All rights reserved. 12

13. Enterprise Systems need more…
Application Lifecycle Management
Common Programming Model
Cross-Stack Debugging
ERP /
Apps Analytics
Operations
Data + Processing Platform
SQL / MDX / Extensions / MPP FW
“NoSQL”: Extending
Engines on SQL
Modeling
Structured Data
Data Warehouses
Disk
Unstructured
Data Movement / CEP / Data Quality & Governance
Data Center Design
Business Continuity and Sustainable Innovation are a must
© 2012 SAP AG. All rights reserved. 13

14. Big Data Enterprise Solution
Events / sec
ERP /
Apps Analytics
Operations
Big Data
Data + Processing Platform
SQL / MDX / Extensions / MPP FW
“NoSQL”: Extending
Engines on SQL
Enterprise O( f(n) )
Modeling
Structured Data
IT Data Warehouses
Disk
Unstructured
Data Movement / CEP / Data Quality & Governance
10n Giga Bytes
The road from technology to business value has been laid.
© 2012 SAP AG. All rights reserved. 14

15. 3 Scenarios for Big Data Implementation
Scheduled Data Mart Big Data EDW
reports Data Warehouse
Reporting / Analytics Reporting / Analytics Reporting / Analytics
ETL / Move
ETL / Push Down EDW
Transformations
Advanced Advanced
Advanced
Analytics Analytics
Analytics
HADOOP HADOOP HADOOP
Hadoop Distributions | OS + Hardware
© 2012 SAP AG. All rights reserved. 15

16. Thank You!
SAP HANA & SAP DW Solution Management:
Yuvaraj Athur Raghuvir
yuvaraj.athur.raghuvir@sap.com