Bi207- SAP Business Suite Operational Analytics Integrating In-Memory Technology
Upcoming SlideShare
Loading in...5
×

Like this? Share it with your network

Share
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads

Views

Total Views
2,408
On Slideshare
2,393
From Embeds
15
Number of Embeds
1

Actions

Shares
Downloads
92
Comments
0
Likes
0

Embeds 15

http://www.erp-bi.com 15

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 1. BI 207SAP Business Suite Operational AnalyticsIntegrating In-Memory TechnologyDr. Christian Dressler / TIP In-Memory Platform BW
  • 2. DisclaimerThis presentation outlines our general product direction and should not be relied on in making apurchase decision. This presentation is not subject to your license agreement or any other agreementwith SAP. SAP has no obligation to pursue any course of business outlined in this presentation or todevelop or release any functionality mentioned in this presentation. This presentation and SAPsstrategy and possible future developments are subject to change and may be changed by SAP at anytime for any reason without notice. This document is provided without a warranty of any kind, eitherexpress or implied, including but not limited to, the implied warranties of merchantability, fitness for aparticular purpose, or non-infringement. SAP assumes no responsibility for errors or omissions in thisdocument, except if such damages were caused by SAP intentionally or grossly negligent.© 2011 SAP AG. All rights reserved. 2
  • 3. AgendaNext Generation Operational AnalyticsIntroduction into technological aspects of Operational Data Provisioning What are Operational Data Providers BWA acceleration ‚out of the box‘ Integration with NW Enterprise SearchDemo based on BS7i2011 business contentOutlook – mobile consumption and evolution towards SAP HANA© 2011 SAP AG. All rights reserved. 3
  • 4. Next Generation Operational Analytics –Operational Data Provisioning Operational Analytics directly in the Backend Application >500 ODPs Real Time Data Access – no latency in FIN, Operational HCM, SD, MM, SRM, Delivery Analytics Enable any type of analytical UI (state of SNC, Goals BS7i2011 Oil&Gas, the art BOBJ frontends) MDG Implement one interface independent of Technology consumption ODP framework Easy scale out to in-memory technology NW 7.03 Be prepared for mobile consumption© 2011 SAP AG. All rights reserved. 4
  • 5. Operational Analytics Architecture in BS7i2011Frontends Data List Interactive Formatted Dash- Ad-hocAnalytics& Search Search Charting Browsing Reporting Analysis Reporting boarding Reporting BEx / Search BOBJ List Report Crystal Xcelsius Web Chart UIBB Advanced Result List Explorer UIBB Report Dashboard Intelligence AnalysisData Provisioning Search Analytical Request/ Response Analytic Query Services SOA, REST consumers Other BWA (TREX) Operational Data Provider (ODP) Search & ETL Analytics Data Provisioning for Search and Analytics DataSource Consumers Model © 2011 SAP AG. All rights reserved. 5
  • 6. Operational Analytics Architecture in BS7i2011Frontends Data List Interactive Formatted Dash- Ad-hocAnalytics& Search Search Charting Browsing Reporting Analysis Reporting boarding Reporting BEx / Search BOBJ List Report Crystal Xcelsius Web Chart UIBB Advanced Result List Explorer UIBB Report Dashboard Intelligence AnalysisData Provisioning Search Analytical Request/ Response Analytic Query Services SOA, REST consumers Other BWA (TREX) Operational Data Provider (ODP) Search & ETL Analytics Data Provisioning for Search and Analytics DataSource Consumers Model © 2011 SAP AG. All rights reserved. 6
  • 7. Structural elements for Analytic Query consumption Master Data Attributes Master Data Texts Transactional Data / Facts Hierarchy© 2011 SAP AG. All rights reserved. 7
  • 8. The SAP NetWeaver BW picture InfoObject (Characteristic) Master Data Attributes InfoProvider Master Data Texts InfoCube or InfoSet or … Hierarchy© 2011 SAP AG. All rights reserved. 8
  • 9. The Operational Analytics picture based onOperational Data Providers (ODP) Transient InfoObject (Characteristic) Master Data ODP Transient InfoProvider Texts ODP Transactional ODP or Master Data ODP or ODP View Hierarchy ODP© 2011 SAP AG. All rights reserved. 9
  • 10. Customer Texts KUNNR Customer Chart of accounts Number Customer Number TXTMD KTOPL Chart of accounts KUNNR Customer attribute Texts Number KKTPL Group Chart of Accts ADRNR Address Customer Balances ANRED Title Master Data KTOPL Chart of accounts … attribute Master Data AKONT G/L Account G/L Account Number Number KUNNR Customer Number KTOPL Chart of accounts BUKRS Company code attribute CURTYPE Currency type SAKNR G/L Account Number G/L Account Texts FISCPER Period/year BILKT Group Account LANGU Language Code FISCVAR Fiscal year variant Number KTOPL Chart of accounts GJAHR Fiscal Year GVTYP P&L Statement attribute Account Type PERIO Period SAKNR G/L Account … Number CURRENCY Currency Key Master Data TXTSH Short Text Company Code UM01H Total credit TXTLG Long Text postingsCompany Code Texts BUKRS Company Texts Code UM01K Accumulated BUKRS Company balance Code LAND1 Country UM01S Total debit postings TXTMD WAERS Currency Key UM01U Sales of the period Texts G/L Account Hierachy … Transaction Data/Facts Master Data
  • 11. Data Provisioning for ODPs based onExtractors – single point of business logic implementation Data Provisioning for Search & Analytics ODPs business documents Extractors ESH data sources BW DataSources ODP Business Logic Modeling master data transactional data master data attributes master data text master data hierarchy© 2011 SAP AG. All rights reserved. 11
  • 12. ODP Interface "ODP SQL" ↔ ODP APISELECT I_ODPNAME 0OPS_11_ITM matnr I_MAXIMUM_ROWS 4 vbtyp meins I_NO_AGGREGATION False SUM( klmeng ) AS sum_klmeng IT_FIELD_AGGREGATIONS COUNT( * ) FIELDNAME COMPONENT AGGREGATION_FUNCTIONFROM 0ops_11_itm UP TO 4 ROWS MATNRWHERE matnr LIKE SD10% VBTYP AND vbtyp IN (C,H) MEINSGROUP BY KLMENG SUM_KLMENG SUM matnr C Orders H Returns * COUNT vbtyp meins IR_SELECTION_SET {O:nnn*CLASS=CL_RSMDS_...SET}ORDER BY IT_SORT_DESCRIPTIONS matnr sum_klmeng DESCENDING FIELDNAME DESCENDING MATNR False SUM_KLMENG True© 2011 SAP AG. All rights reserved. 12
  • 13. ODP Interface "ODP SQL" ↔ ODP APISELECT I_ODPNAME 0OPS_11_ITM matnr I_MAXIMUM_ROWS 4 vbtyp meins I_NO_AGGREGATION False SUM( klmeng ) AS sum_klmeng IT_FIELD_AGGREGATIONS COUNT( * ) FIELDNAME COMPONENT AGGREGATION_FUNCTIONFROM 0ops_11_itm UP TO 4 ROWS MATNRWHERE matnr LIKE SD10% VBTYP AND vbtyp IN (C,H) MEINSGROUP BY KLMENG SUM_KLMENG SUM matnr C Orders vbtyp H Returns Result * COUNT meins IR_SELECTION_SET {O:nnn*CLASS=CL_RSMDS_...SET}ORDER BY IT_SORT_DESCRIPTIONS matnr sum_klmeng DESCENDING FIELDNAME DESCENDING MATNR False SUM_KLMENG True© 2011 SAP AG. All rights reserved. 13
  • 14. Operational Analytics Architecture in BS7i2011Frontends Data List Interactive Formatted Dash- Ad-hocAnalytics& Search Search Charting Browsing Reporting Analysis Reporting boarding Reporting BEx / Search BOBJ List Report Crystal Xcelsius Web Chart UIBB Advanced Result List Explorer UIBB Report Dashboard Intelligence AnalysisData Provisioning Search Analytical Request/ Response Analytic Query Services SOA, REST consumers Other BWA (TREX) Operational Data Provider (ODP) Search & ETL Analytics Data Provisioning for Search and Analytics DataSource Consumers Model © 2011 SAP AG. All rights reserved. 14
  • 15. Data replication – BWA acceleration ‚out of the box‘ Data Provisioning for Search & Analytics business documents ESH data sources Indexing BWA Process (TREX) Extractors BW DataSources Business Logic master data transactional data master data attributes Operational ODP data Delta replication Queue API (ETL) master data text master data hierarchy© 2011 SAP AG. All rights reserved. 15
  • 16. Integration with NW Enterprise SearchCommon design time for Search and Analytics Modeler for Search and AnalyticsmodelsImport of BW DataSourcesODP properties and associations between ODPsExtensibility of Business ContentCommon administration of BWA indexing Administration CockpitPeriodical job schedulingNear real-time data replication Data latency < 1 min can be achievedShared BWA persistency (physical indices) within BWA 7.20© 2011 SAP AG. All rights reserved. 16
  • 17. ODP Content Overview SAP Business Suite 7 Innovations 2011 Area Topic HCM E-Recruiting, Learning Solution, Time Management FIN Cost Center Accounting, Accounts Receivable, Accounts Payables, G/L, Product Costing, ... Sales Documents (e.g. Quotations, Sales Orders), Deliveries, Billing Documents (e.g. Invoices, Credit SD and Debit Memos) MM Purchasing Analysis, Inventory Analysis CRM Opportunity, Sales Order SRM Purchasing Documents, Procurement Efficiency SCM (SNC) Supply-Base Performance Analysis, Direct Performance Analysis MDG Master Data Governance (Process Monitoring PMA & Analytics) Business Process Performance Management OPM (Oil & Gas) Production Volumes, Downtime, Measurements & Well Tests (Healthcare IS-H Country Version CN) Patient Case, Patient Movement type / Diagnosis / Procedure, Bed Information© 2011 SAP AG. All rights reserved. 17
  • 18. Demo
  • 19. Demo© 2011 SAP AG. All rights reserved. 19
  • 20. List GUIBB for Customer balances reporting leveragingSAP Crystal Reports formatting© 2011 SAP AG. All rights reserved. 20
  • 21. Modeler for Search and Analytics© 2011 SAP AG. All rights reserved. 21
  • 22. Sales: Manage my work / Sales Pipeline – in a dashboard© 2011 SAP AG. All rights reserved. 22
  • 23. Scheduling of BWA Indexing© 2011 SAP AG. All rights reserved. 23
  • 24. SAP Business Objects Analysis on BWA© 2011 SAP AG. All rights reserved. 24
  • 25. Enterprise Search on indexed data© 2011 SAP AG. All rights reserved. 25
  • 26. ODP Join – a special join pattern Example: CRM ODP model with 1:n and cross BO relations Opportunity Opp. Item Opportunity Sales Order O1 I1 O1 S1 I2 O2 S2 O2 S3 O3 I3 O3© 2011 SAP AG. All rights reserved. 26
  • 27. ODP Join – key figure semantic Opportunity Opp. Item Sales Order Expected Product Number of Number of Native Revenue Value Opportunities Successor Sales Orders Join O1 I1 S1 10.000 € 4.500 € 1 1 O1 I2 S1 10.000 € 5.000 € 1 1 O2 I3 S2 2.000 € 1.900 € 1 1 O2 I3 S3 2.000 € 1.900 € 1 1 O3 I4 # 7.000 € 7.000 € 1 0 Result 31.000 € 20.300 € 5 4 Opportunity Opp. Item Sales Order Expected Product Opportunity to Sales Number of Number of Revenue Value Order Conversion Rate Opportunities Successor Sales Orders ODP Join O1 # S1 0 € 0 € 0% 0 1 I1 # 0 € 4.500 € 0% 0 0 pattern I2 # 0 € 5.000 € 0% 0 0 # # 10.000 € 0 € 0% 1 0 Result 10.000 € 9.500 € 100% 1 1 O2 # S2 0 € 0 € 0% 0 1 S3 0 € 0 € 0% 0 1 I3 # 0 € 1.900 € 0% 0 0 # # 2.000 € 0 € 0% 1 0 Result 2.000 € 1.900 € 100% 1 2 O3 I4 # 0 € 7.000 € 0% 0 0 # # 7.000 € 0 € 0% 0 0 Result 7.000 € 7.000 € 0% 1 0 Result 19.000 € 18.400 € 66% 3 3© 2011 SAP AG. All rights reserved. 27
  • 28. ODP Join – demo© 2011 SAP AG. All rights reserved. 28
  • 29. Easy consumption of Analytic Queries ‚Gateway‘ (REST) Gadget ‚Easy Query‘ ABAP BICS Analytic Query© 2011 SAP AG. All rights reserved. 29
  • 30. Operational Analytics evolution in the context of SAP HANA SAP HANA SAP HANA SAP HANA as operational data mart in addition for in addition as database (first evaluation) ODP indexing for new applications Analytical Analytical Analytical Frontends* Frontends* Frontends* ERP Analytical ERP with Analytical ERP with Analytical ERP with Analytical New Apps Frontends* ODP Frontends* ODP Frontends* ODP Frontends* X SAP X SAP X SAP X SAP BWA DB HANA DB HANA DB HANA DB HANA  No ODP technology  BWA and HANA used  ODP using HANA  New Applications can also use available side by side infrastructure for structured data provided by ODP performance acceleration Up to BS 7i2010 (NW 7.02) As of BS 7i2011 (NW 7.03) No ODP technology ODP technology available* Available analytical frontends depend on release and underlying technology© 2011 SAP AG. All rights reserved. 30
  • 31. Next Generation Operational Analytics –Summary and Outlook  Operational Analytics directly in the Summary Backend  With NW 7.03 and Suite 7i2011 ODP is the established framework for Real Time Data Access – no latency  operational analytics Outlook  Enable any type of analytical UI (state of Goals  Minute range latency for BWA/HANA the art BOBJ frontends) (Real time indexing)  Implement one interface independent of  Productize Mobile Analytics consumption  Easy Scale out to BW  Easy scale out to in-memory technology  Deliver analytical packages including BOBJ content as Rapid Deployment Solutions (RDS) Be prepared for mobile consumption © 2011 SAP AG. All rights reserved. 31
  • 32. Further InformationSAP Public Web:SAP Developer Network (SDN): www.sdn.sap.comBusiness Process Expert (BPX) Community: www.bpx.sap.comRelated Workshops/Lectures at SAP TechEd 2011BI 102, Insight to Action: Empowering Your Business Suite Users with Analytics, Lecture 1hCD 203, Configuration and Adaptation of Applications with the Floorplan Manager, Lecture 2h© 2011 SAP AG. All rights reserved. 32
  • 33. FeedbackPlease complete your session evaluation.Be courteous — deposit your trash,and do not take the handouts for the following session.
  • 34. Thank You!Contact information:Dr. Christian DresslerDevelopment ManagerSAP AG, Dietmar-Hopp-Allee 16 69190 Walldorf, Germanychristian.dressler@sap.com+49 6227 762108
  • 35. Appendix
  • 36. ODP properties for Analytic Query consumption Characteristics vs. Key FiguresTransactional ODP or Aggregation of Key Figures Master Data ODP or Selection fields ODP View Special semantics, e.g. fisc per, month Authorization Key (obligatory) Master Data ODP Navigation attributes (slice and dice) Opt. time dependent, temporal join Projections / Roles Key (obligatory) Texts ODP Opt. time dependent Special semantics language, text© 2011 SAP AG. All rights reserved. 36
  • 37. Full support of complex hierarchies  Hierarchy ODP at runtime derived as a composition from nodes (hierarchy segments) that are associated to Master Data ODPs Hierarchy ODP – Header – Header Texts – Elements – Folder Texts (for folder-like Elements) – Optional element extension for intervals  Opt. time and version dependent  Caching of Hierarchies by the Analytic Engine if update timestamp is supplied by the Hierarchy Header© 2011 SAP AG. All rights reserved. 37
  • 38. © 2011 SAP AG. All rights reserved. ®No part of this publication may be reproduced or transmitted in any form or for any purpose HTML, XML, XHTML and W3C are trademarks or registered trademarks of W3C , Worldwithout the express permission of SAP AG. The information contained herein may be Wide Web Consortium, Massachusetts Institute of Technology.changed without prior notice. SAP, R/3, SAP NetWeaver, Duet, PartnerEdge, ByDesign, SAP BusinessObjects Explorer,Some software products marketed by SAP AG and its distributors contain proprietary StreamWork, and other SAP products and services mentioned herein as well as theirsoftware components of other software vendors. respective logos are trademarks or registered trademarks of SAP AG in Germany and otherMicrosoft, Windows, Excel, Outlook, and PowerPoint are registered trademarks of Microsoft countries.Corporation. Business Objects and the Business Objects logo, BusinessObjects, Crystal Reports,IBM, DB2, DB2 Universal Database, System i, System i5, System p, System p5, System x, Crystal Decisions, Web Intelligence, Xcelsius, and other Business Objects products andSystem z, System z10, System z9, z10, z9, iSeries, pSeries, xSeries, zSeries, eServer, services mentioned herein as well as their respective logos are trademarks or registeredz/VM, z/OS, i5/OS, S/390, OS/390, OS/400, AS/400, S/390 Parallel Enterprise Server, trademarks of Business Objects Software Ltd. Business Objects is anPowerVM, Power Architecture, POWER6+, POWER6, POWER5+, POWER5, POWER, SAP company.OpenPower, PowerPC, BatchPipes, BladeCenter, System Storage, GPFS, HACMP, Sybase and Adaptive Server, iAnywhere, Sybase 365, SQL Anywhere, and other SybaseRETAIN, DB2 Connect, RACF, Redbooks, OS/2, Parallel Sysplex, MVS/ESA, AIX, products and services mentioned herein as well as their respective logos are trademarks orIntelligent Miner, WebSphere, Netfinity, Tivoli and Informix are trademarks or registered registered trademarks of Sybase, Inc. Sybase is an SAP company.trademarks of IBM Corporation.Linux is the registered trademark of Linus Torvalds in the U.S. and other countries. All other product and service names mentioned are the trademarks of their respective companies. Data contained in this document serves informational purposes only. NationalAdobe, the Adobe logo, Acrobat, PostScript, and Reader are either trademarks or product specifications may vary.registered trademarks of Adobe Systems Incorporated in the United States and/or othercountries. The information in this document is proprietary to SAP. No part of this document may be reproduced, copied, or transmitted in any form or for any purpose without the express priorOracle and Java are registered trademarks of Oracle and/or its affiliates. written permission of SAP AG.UNIX, X/Open, OSF/1, and Motif are registered trademarks of the Open Group.Citrix, ICA, Program Neighborhood, MetaFrame, WinFrame, VideoFrame, and MultiWin aretrademarks or registered trademarks of Citrix Systems, Inc. © 2011 SAP AG. All rights reserved. 38