SAP BW in a Growing Landscape - Increasing the Benefit of Your BW Implementation - SAP NetWeaver Regional Implementation Group -BI SAP AG
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1 SAP in a Growing Landscape - Increasing the Benefit of Your Implementation - SAP NetWeaver Regional Implementation Group -BI SAP AG
2 Content Overview Content Extend the Reach of Integrate new Non-SAP data sources Distribute integrated data Set Standards for Flexibility and Reliability central template development Managing your data - Using Archiving SAP AG 2004, in a Growing Landscape, J. Haupt / 2
3 in a Growing Landscape Extract from Non-SAP Departmental Data Marts Acctg Central Marketing Templates ETL Finance Sales Distribute to Non-SAP DSS Applications CRM Changed Data Corporate Applications Staging Area local ODS Global ODS EDW Oper. Mart Granularity Manager Exploration warehouse/ data mining ecomm. Bus. Int. Cross media Storage Management Internet Dialogue Manager Cookie Cognition Preformatted dialogues Session Analysis Manage Volume: Archiving Web Logs Archives Near line Storage Source:Bill Inmon SAP AG 2004, in a Growing Landscape, J. Haupt / 3
4 Content Overview Content Extend the Reach of Integrate new Non-SAP data sources Distribute integrated data Set Standards for Flexibility and Reliability central template development Managing your data - Using Archiving SAP AG 2004, in a Growing Landscape, J. Haupt / 4
5 in a Growing Landscape: Consistent Distribution of Data Extract from Non-SAP Departmental Data Marts Acctg Finance Marketing ETL Sales DSS Applications CRM Changed Data Corporate Applications Staging Area local ODS Global ODS EDW Oper. Mart Granularity Manager Exploration warehouse/ data mining ecomm. Bus. Int. Cross media Storage Management Session Analysis Near line Storage Internet Dialogue Manager Cookie Cognition Preformatted dialogues Web Logs Archives Source:Bill Inmon SAP AG 2004, in a Growing Landscape, J. Haupt / 5
6 Open Extraction in a Growing Landscape A Broader View of Data Acquisition SAP Data Acquisition: Classic Data Warehousing ( pull Data) Near Real Time Data Warehousing ( push Data) - planned Service API BAPI DB Connect File Universal Data Connect Adaptors: 3.5 JDBC ODBO XMLA SAP ETL B C D E F Universal Data Connect Integrates data for analysis and enables a complete business view Normal data staging and storing in as well as real time access to original data location supported Java based Adaptors for different drivers, providers, and protocols available JDBC OLE DB for OLAP XML for Analysis SAP AG 2004, in a Growing Landscape, J. Haupt / 6
7 Universal Data Integration Universal Data Connect BI Java Connectors to provide access to any data (Relational, OLAP, SAP Query) Based on industry standards for interoperability (JDBC, XMLA, ODBO) Universal Data Connect to integrate data into platform BI Java SDK for custom built Java Applications 2. Universal Data Connect SAP Integration SAP non SAP SAP Query XMLA JDBC ODBO Universal Data Connect BI Java SDK Staging OLAP BEx Custom-built Applications SAP Enterprise Portal 1. BI Java Connectors JDBC, XMLA,ODBO, SAP Query 3. BI Java SDK Java API, Examples, Documentation SAP AG 2004, in a Growing Landscape, J. Haupt / 7
8 Scenarios using Universal Data Connect Integrating data sources without additional costs 1. Normal data extraction and staging into 2. Real time data integration via remote InfoCube feature -> support of real time operational reporting with integration e.g. Retail POS data are stored outside you want to report real time on today's outlet sales (Act-Quantity) and compare it with last year sales (Quantity) MultiProvider Outlet-Master RemoteCube Day Outlet Article Act-Quantity Article-Master Normal Cube Day Outlet Article Quantity real time access via Universal Data Connect Day Time Outlet Transaction Article Quantity external Source SAP AG 2004, in a Growing Landscape, J. Haupt / 8
9 Content Content Extend the Reach of Integrate new Non-SAP data sources Distribute integrated data Set Standards for Flexibility and Reliability central template development Managing your data - Using Archiving SAP AG 2004, in a Growing Landscape, J. Haupt / 9
10 in a Growing Landscape: Consistent Distribution of Data Departmental Data Marts Acctg Finance Marketing Sales Distribute to Non-SAP DSS Applications ETL CRM Changed Data Corporate Applications Staging Area local ODS Global ODS EDW Oper. Mart Granularity Manager Exploration warehouse/ data mining ecomm. Bus. Int. Cross media Storage Management Session Analysis Near line Storage Internet Dialogue Manager Cookie Cognition Preformatted dialogues Web Logs Archives Source:Bill Inmon SAP AG 2004, in a Growing Landscape, J. Haupt / 10
11 Consistent Data Distribution to External Targets: Open Hub Service Controlled distribution of consistent data Target: file or DB table Central monitoring Select filter criteria and columns Scheduling Full or delta mode (Data + Metadata) ODS Objects SAP AG 2004, in a Growing Landscape, J. Haupt / 11
12 Open Hub Service and ETL Tool Integration: Automatic Forwarding of Consistent Data 3 rd party integration into Open Hub Service Scenario Integration of 3 rd party ETL tools (e.g., Ascential) into open hub service extraction (within process chains) ETL tool to load data from any complex Non-SAP data source and to distribute data out of to any target system Feature Description Integration of Monitoring including external status tracking Prevents second start before data has been collected by 3 rd party tool No data will be lost, if read from 3 rd party tool fails Sending notification to 3 rd party tool when open hub extraction is finished API s for meta data and runtime Certification planned SAP Process Chain SAP AG 2004, in a Growing Landscape, J. Haupt / Start Process Chain (optional) 3. Send notification 4. Read metadata for comparison 5. Read data (external API) 6. Set extract status 3 rd rd Party Tool
13 Open Hub Service Summary Openness to extract data from All data objects are supported for extraction Delta tracking for each target system Scheduling and central monitoring Automatic forwarding to any target via ETL Tool It is an important feature to introduce consistency in a heterogeneous information system landscape. It supports to serve as an enterprise information hub (edw). SAP AG 2004, in a Growing Landscape, J. Haupt / 13
14 Content Content Extend the Reach of Integrate new Non-SAP data sources Distribute integrated data Set Standards for Flexibility and Reliability central template development Managing your data - Using Archiving SAP AG 2004, in a Growing Landscape, J. Haupt / 14
15 in a Growing Landscape: Central Templates to Achieve Synergies and Reliability Departmental Data Marts ETL Marketing Acctg Finance Sales Central Templates DSS Applications CRM Changed Data Corporate Applications Staging Area local ODS Global ODS EDW Oper. Mart Granularity Manager Exploration warehouse/ data mining ecomm. Bus. Int. Cross media Storage Management Session Analysis Near line Storage Internet Dialogue Manager Cookie Cognition Preformatted dialogues Web Logs Archives Source:Bill Inmon SAP AG 2004, in a Growing Landscape, J. Haupt / 15
16 Concepts to Support a Central Development in a Multiple Landscape Central application (template) development to Reduce redundant scenarios Establish consistent structures with consistent data Enable comparability Reduce cost ( synergies) Source Local Central Application Development Source Local Source Local Source Source Local Source Local Source Local Source Source SAP AG 2004, in a Growing Landscape, J. Haupt / 16
17 Development Strategies- Central Templates Parameters of a development strategy: Role and degree of central development Role and degree of local development Local Central Application Development 1. No central development - only local development 2. No local development - only central development 3. Local & central development - I. no local modifications on delivered central scenarios (stable templates Standard development) II. III. central template scenarios serve as examples for local development (adaptable templates Customer Content development ) Mixed approach of I. & II. i.e. stable scenarios plus adaptable scenarios SAP AG 2004, in a Growing Landscape, J. Haupt / 17
18 Central Template Development Stable Templates Central development system Local target system M(odified) M(odified) A(ctive) A(ctive) create activate change Export (A Object) After import method Import change Stable template description: No local modifications on delivered scenarios Local query creation on delivered scenarios MultiProviders to combine local with central structures Standard environment for template development Dedicated instance to perform localizations? Transport of A-versions Stable templates a pragmatic approach to establish reliability. SAP AG 2004, in a Growing Landscape, J. Haupt / 18
19 Central Template Development Adaptable Templates using Customer Content Central Customer Content Development System M(odified) Local system M(odified) A(ctive) A(ctive) D(elivery) D(elivery) create activate change Content activation change Export (D Object) import Adaptable template description: Creation of Customer Content (like Business Content at SAP) development instance defined as Customer Content System Template objects created as D-version Transport of D-versions to local sites Central template scenarios serve as example for local development Customer Content may be used or be not used Usage can only be controlled using guidelines SAP AG 2004, in a Growing Landscape, J. Haupt / 19
20 Central Template Development Support of Namespace Concepts Customer namespaces A proper namespace concept is important to distribute central templates smoothly! offers customers and partners the possibility to register a world wide unique namespace e.g. /ABC/ The namespaces can be reserved via the service marketplace: All central objects are created in this namespace (e.g. InfoCube /ABC/IC01), please check the documentation An additional namespace must be reserved for generated DDIC objects (e.g. /B123/), please check the documentation It is also possible to use the standard customer namespace (A-Z) Then the customer has to make sure that central objects and local objects of the recipients lie in different namespaces SAP AG 2004, in a Growing Landscape, J. Haupt / 20
21 Content Content Extend the Reach of Integrate new Non-SAP data sources Distribute integrated data Set Standards for Flexibility and Reliability central template development Managing your data - Using Archiving SAP AG 2004, in a Growing Landscape, J. Haupt / 21
22 in a Growing Landscape: Manage Your Data using Archiving Departmental Data Marts Acctg Finance Marketing Sales DSS Applications ETL CRM Changed Data Corporate Applications Staging Area local ODS Global ODS EDW Oper. Mart Granularity Manager Exploration warehouse/ data mining ecomm. Bus. Int. Cross media Storage Management Internet Dialogue Manager Cookie Cognition Preformatted dialogues Session Analysis Manage Volume: Archiving Web Logs Archives Near line Storage Source:Bill Inmon SAP AG 2004, in a Growing Landscape, J. Haupt / 22
23 Motivation to Archive : Benefits Costs storage, cpu, memory Access frequency Data availability faster rollups, change runs, etc System availability less downtime for backups, upgrades, etc Performance Faster load times Faster query times reads Archiving with SAP Data age See also "Scalability with SAP Business Information Warehouse at Legal Requirements SAP AG 2004, in a Growing Landscape, J. Haupt / 23
24 Technical Architecture: Process overview InfoCube ODS Object DataManager activates reads deletes Repository Archiving Object Write Delete generates Schedules Read Manually or automatically started Verifies data written Deletes Data according to selection criteria Unlocks DataTarget Archive Administration (SARA) Export DataSource Locks DataTarget Selects data according to selection criteria Writes data to archive file(s) ADK File system, CMS, HSM Reads archive data from selected archive files Maps data to current DataTarget structure Filters data according to InfoPackage selections SAP AG 2004, in a Growing Landscape, J. Haupt / 24
25 data archiving technology : Write process Time slot archiving for selection of transactional data based on time criteria. ODS Object Sep 2002 Oct 2002 Nov 2002 Dec 2002 Jan 2003 Feb 2003 Mar 2003 Current Date: Mar 2003 Time slot archiving: Archive complete Years 2002 & 2003 Only complete fiscal years Exclude Nov 2002 Protect archive areas Archive file Sep 2002 Oct 2002 Dec 2002 New Data loads Dec 2002 Mar 2003 Pros: Complex time selection options with protection of archive areas Restriction: Time selections only SAP AG 2004, in a Growing Landscape, J. Haupt / 25
26 data archiving technology : Write process Characteristic value selection archiving for free selection of transactional data based on any criteria: ODS Object comp 10 Oct 2002 comp 10 Nov 2002 comp 20 Nov 2002 comp 10 Dec 2002 comp 20 Jan 2003 comp 20 Feb 2003 comp 20 Mar 2003 Current Date: Mar 2003 Data selection archiving: Archive Years 2002 & 2003 Company 10 only Archive file comp 10 Oct 2002 comp 10 Nov 2002 comp 10 Dec 2002 Pros: Flexible data selection Restriction: No protected archiving areas New Data loads Comp 10 Dec 2002 Comp 20 Mar 2003 SAP AG 2004, in a Growing Landscape, J. Haupt / 26
27 SAP Data Archiving Technology: Extraction/Reloading InfoCube ODS object InfoCube ODS Object Update Rules Export DataSource InfoPackage Archive Files Extractors and Export DataSources are Archive enabled InfoPackage is extended by an option 'archive selection Full extraction Selection options for available archive sessions and files Archive files are read with selection criteria of the request Reload to original Data Target is possible but not recommended Reload Recommendation: Extract to a copy of original DataTarget instead Use MultiProvider to combine remaining data with reloaded data SAP AG 2004, in a Growing Landscape, J. Haupt / 27
28 in a Growing Landscape: Online-Access to Historical, High Volume, Granular Data Departmental Data Marts Acctg Finance Marketing Sales DSS Applications ETL CRM Changed Data Corporate Applications Staging Area local ODS Global ODS EDW Oper. Mart Granularity Manager Exploration warehouse/ data mining ecomm. Bus. Int. Cross media Storage Management Internet Dialogue Manager Cookie Cognition Preformatted dialogues Session Analysis Manage Volume: Archiving Web Logs Archives Near line Storage Source:Bill Inmon SAP AG 2004, in a Growing Landscape, J. Haupt / 28
29 Limits of Archiving and Near-line Storage Access frequency Access frequency Archiving ( 3.X) Near-line Storage reads reads ( 7.X planned *) Archiving with SAP Near Line Storage SAP AG 2004, in a Growing Landscape, J. Haupt / 29 Data age support of Near-Line Storage (planned) Data age * Pilot project possible for 3.X Separating frequently used (kept in database) and infrequently used data (stored in Near-line Storage) Transparent access to "non-archived" and "archived" data for queries Intelligent Data Access Openness
30 SAP Open Solution for Near-line Storage Support (Planned) Query InfoCube/ODS Object with Near-line Services Data Flow Control Flow Split and Dispatch Union High level index DB Interface Archive/ Restore Near-line Storage Adapter Data Base Near-line Storage Partner Solution High speed disk Low level index Data Manager Robotic Tape Libraries NAS or Low-Cost Disk Optical Jukeboxes SAP AG 2004, in a Growing Landscape, J. Haupt / 30
31 Further Information Public Web: > Solutions > SAP NetWeaver SAPNet: Use ALIAS: / SAP Service Marketplace: InfoIndex Data Modelling InfoIndex Enterprise Data Warehousing InfoIndex ODS Functions SAP AG 2004, in a Growing Landscape, J. Haupt / 31
32 Copyright 2004 SAP AG. All Rights Reserved No part of this publication may be reproduced or transmitted in any form or for any purpose without the express permission of SAP AG. The information contained herein may be changed without prior notice. Some software products marketed by SAP AG and its distributors contain proprietary software components of other software vendors. Microsoft, WINDOWS, NT, EXCEL, Word, PowerPoint and SQL Server are registered trademarks of Microsoft Corporation. IBM, DB2, DB2 Universal Database, OS/2, Parallel Sysplex, MVS/ESA, AIX, S/390, AS/400, OS/390, OS/400, iseries, pseries, xseries, zseries, z/os, AFP, Intelligent Miner, WebSphere, Netfinity, Tivoli, Informix and Informix Dynamic ServerTM are trademarks of IBM Corporation in USA and/or other countries. ORACLE is a registered trademark of ORACLE Corporation. UNIX, X/Open, OSF/1, and Motif are registered trademarks of the Open Group. Citrix, the Citrix logo, ICA, Program Neighborhood, MetaFrame, WinFrame, VideoFrame, MultiWin and other Citrix product names referenced herein are trademarks of Citrix Systems, Inc. HTML, DHTML, XML, XHTML are trademarks or registered trademarks of W3C, World Wide Web Consortium, Massachusetts Institute of Technology. JAVA is a registered trademark of Sun Microsystems, Inc. JAVASCRIPT is a registered trademark of Sun Microsystems, Inc., used under license for technology invented and implemented by Netscape. MarketSet and Enterprise Buyer are jointly owned trademarks of SAP AG and Commerce One. SAP, SAP Logo, R/2, R/3, mysap, mysap.com and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP AG in Germany and in several other countries all over the world. All other product and service names mentioned are trademarks of their respective companies. SAP AG 2004, in a Growing Landscape, J. Haupt / 32
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