• Save
Accelerating big data value across enterprise
Upcoming SlideShare
Loading in...5
×
 

Accelerating big data value across enterprise

on

  • 1,396 views

 

Statistics

Views

Total Views
1,396
Views on SlideShare
1,342
Embed Views
54

Actions

Likes
0
Downloads
0
Comments
0

2 Embeds 54

http://eventifier.co 42
http://eventifier.com 12

Accessibility

Categories

Upload Details

Uploaded via as Adobe PDF

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Accelerating big data value across enterprise Accelerating big data value across enterprise Presentation Transcript

  • Safe Harbor StatementThe information in this presentation is confidential and proprietary to SAP and may not be disclosed withoutthe permission of SAP. This presentation is not subject to your license agreement or any other service orsubscription agreement with SAP. SAP has no obligation to pursue any course of business outlined in thisdocument or any related presentation, or to develop or release any functionality mentioned therein. Thisdocument, or any related presentation and SAPs strategy and possible future developments, products andor platforms directions and functionality are all subject to change and may be changed by SAP at any timefor any reason without notice. The information on this document is not a commitment, promise or legalobligation to deliver any material, code or functionality. This document is provided without a warranty of anykind, either express or implied, including but not limited to, the implied warranties of merchantability, fitnessfor a particular purpose, or non-infringement. This document is for informational purposes and may not beincorporated into a contract. SAP assumes no responsibility for errors or omissions in this document, exceptif such damages were caused by SAP intentionally or grossly negligent.All forward-looking statements are subject to various risks and uncertainties that could cause actual resultsto differ materially from expectations. Readers are cautioned not to place undue reliance on these forward-looking statements, which speak only as of their dates, and they should not be relied upon in makingpurchasing decisions.© 2012 SAP AG. All rights reserved. 1
  • Session AbstractAs enterprises race to embrace Hadoop in its next-generation data foundation layer,IT organizations are reexamining their current service-level commitments andlooking for ways to achieve similar levels of service with Hadoop-based landscapes.As enterprises across industries move forward into the Hadoop led scale-firstsystem landscapes, SAP is also examining some fundamental must-haves that candrive the adoption of Hadoop in the enterprise. This presentation will discuss thedominant 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 Hadoopand big data management through a broad portfolio from SAP /Sybase thatencompasses SAP HANA, Sybase IQ, SAP BusinessObjects EIM, SAPBusinessObjects BI and other relevant products. It is important to recognize thatthere is more work to be done to accelerate the adoption of Hadoop and big datatechnologies into the traditional enterprises, and this presentation concludes withsome directions that are worth pondering further.© 2012 SAP AG. All rights reserved. 2
  • Accelerating Big Data Value Across aTraditional EnterpriseNon-disruptive Innovation for Enterprise ITYuvaraj Athur RaghuvirDirector, SAP HANA & DW Solution Management
  • 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
  • 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
  • # Reality 3: Integration Cost of Hadoop Like Systems Log Files In-Memory DB Hadoop Enterprise PortalsMulti-structured Data Sources Data Warehouses 1 3 MobileMedia and Other Files Structured Data 2 Disk Dashboard/ Report On DemandEnterprise 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
  • 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
  • Rezoning at San FranciscoNEARLY 25% OF SAN FRANCISCO IS UP FOR REZONINGAugust 21, 2008 on 10:29 am | In Fascinating Information, Government, Historic Properties, Investment Opportunities, NewDevelopments, Trends, Uncategorized | 10 CommentsNEARLY 25% OF SAN FRANCISCO IS UP FOR REZONINGIn a bold move to accommodate San Francisco’s changing needs, the city is looking to rezone + gentrify four eastsidedistricts Plan. Do. Check. Act.http://www.socalofficerealestateblog.com/?p=239http://www.architectmagazine.com/planning/san-francisco-digital-context-analysis-model.aspx© 2011 SAP AG. All rights reserved. Confidential 8
  • 1. Build the Bridge Use integration techniques to share data and queryData Layer Integration Query Federation at Client SideQuery federation at Server Side Direct Client Connectivity Balance between Feature First & Scale First Systems© 2011 SAP AG. All rights reserved. Confidential 9
  • 2. Reach the Enterprise User Contextualize to start assimilating the innovationsDiscover , 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
  • 3. Converge the Best Practices Democratize UseUp-level data flow to modeling paradigms. Seamless experience for various enterprise personas Create a Sustainable Future© 2011 SAP AG. All rights reserved. Confidential 11
  • Complementarity and Co-Evolution VALUE ERP / Operations Apps Analytics Data + Processing Platform MPP “NoSQL”: Extending on SQL / MDX / Extensions / Engines Frameworks SQLModeling 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
  • 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
  • Big Data Enterprise Solution Events / sec ERP / Apps Analytics Operations Big Data Data + Processing Platform SQL / MDX / Extensions / MPP FW “NoSQL”: Extending Engines on SQLEnterprise O( f(n) ) Modeling Structured DataIT 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
  • 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
  • Thank You!SAP HANA & SAP DW Solution Management:Yuvaraj Athur Raghuviryuvaraj.athur.raghuvir@sap.com