Rudolf Hennecke SAP NetWeaver RIG, SAP AG

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1 Data Quality Management in SAP NetWeaver BI Rudolf Hennecke SAP NetWeaver RIG, SAP AG

2 First-Hand Information In this presentation, we will examine the following topics: Definition of Data Quality Management in respect to data warehousing in SAP NetWeaver BI Overview of tools SAP NetWeaver BI provides in order to support data quality initiatives Presentation of new features in the area of Data Quality Management in SAP NetWeaver 2004s SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 2

3 Agenda Overview Data Quality Management Data Validation Error Handling Error Resolution SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 3

4 Definition of Data Quality Integrity Between objects / systems Timeliness Is data up to date? Relevance Comprehensibility Meaningfulness Data Quality criteria: have to be defined by business and IT Completeness Between objects / systems On record level Consistency Plausibility Redundancy Accuracy Uniformity Uniqueness Certainty Correctness have to be regarded on technical and semantic level SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 4

5 Data Quality Process in SAP NetWeaver BI Data Validation Define data quality and define necessary checks Use automated checks in SAP NetWeaver BI and implement customer checks where necessary Consider data quality in your Enterprise Data Warehouse design Error Resolution Resolve data quality issues after data loading This can involve deletion, repairing and reloading of data This should also include periodic analysis of the data in your BI objects including repair options Error Handling Define reaction on errors during data loading Retain invalid data for manual or automated correction and subsequent updating to InfoProviders Get detailed information on type of error and place where it occurred SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 5

6 Agenda Overview Data Quality Management Data Validation Error Handling Error Resolution SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 6

7 Data Validation - Scope Data validation in SAP NetWeaver BI answers the following questions: check what? Technical quality Semantic quality (Business rules) What? check where and when? During data loading In source system, in data transfer, in transformation, in InfoProvider update On persistent data On PSA data, on InfoProvider data Where? check how? Built-in in data transfer (automatic checks) Implemented in transformation (business rule based) Scheduled How? SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 7

8 Data Validation Checks in SAP NetWeaver BI Field level Record level Table level Technical Data type & conversion exits Codepage Technical consistency in respect to BI technology (RSRV) Records sent = records updated, no aggregation allowed Semantic Plausibility (empty field, plausible value,..) Referential integrity & Master data check (SID) Plausibility on correlation between characteristics and key figures Plausibility on aggregation and calculation of multiple data records Technical consistency of data contained in BI Objects (RSRV) Reconciliation Duplicate records in PSA Duplicate master data records Built-in To be implemented SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 8

9 Data Validation Built-In Checks Semantic checks (based on business rules) SAP NetWeaver BI SAP NetWeaver 2004s Completeness InfoProvider Transformation InfoSource Transformation Update Rules SAP BW 3.x InfoSource Transfer Rules Duplicates on master data Referential Integrity Completeness BI Service API DataSource Others Data Type & Conversion Exits Duplicates in transaction data New! Technical checks Codepages Enhanced! Source system Source system SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 9

10 Focus area: Checking Data Types and Conversion Exits In SAP NetWeaver 2004s, checks on Data Type and Conversion Exits can be enabled per field of the DataSource. plausible date fields plausible time fields character values in data type NUMC fields and compliance with the ALPHA conversion routine. SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 10

11 Data Validation Checks to be implemented SAP NetWeaver BI Semantic checks (based on business rules) Reconciliation & Audit Trace SAP NetWeaver 2004s Reconciliation & Audit Trace Data Marts Data Warehouse (Integration Layer) Transformation InfoSource Transformation Customer -defined checks Update Rules InfoSource Transfer Rules Data Warehouse (Data Acquisition Layer) Operational Reporting SAP BW 3.x Data Integrity PSA Technical checks BI Service API DataSource Others Custom check points Source system Source system SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 11

12 Focus area: Implement semantic checks I Implement semantic checks in customer transformations (SAP BW 3.x: in the update or transfer rules). These checks can call the monitor and therefore the Error Handling) From update rules (BW 3.x) append to table MONITOR or See How To Create monitor entries from an update routine From transfer rules (BW 3.x) append to table G_T_ERRORLOG process single record using field RECORD From transformations append table MONITOR (for monitoring only) and / or raise an exception (for storage in the error stack) Process single record using field RECORD To skip records from processing, raise exception cx_rsrout_skip_record. You can abort the whole data package by raising exception cx_rsrout_abort. Check on master data completeness Master Data completeness (on attributes and / or texts) can be checked using Transformations / DTPs (SAP BW 3.x: Export DataSources) SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 12

13 Focus area: Implement semantic checks II Use custom check points during extraction Write check point data to separate table and use this for validation. See How To... Perform Data Load Consistency Checks in BW Build Audit Trace in Data Modeling Audit Traces (source, timestamp, ) allow for trace back to source system. You only use them on objects in the Data Warehouse Layer for simplified integrity checks against source systems. Data Integrity Checks on Data Packages in PSA Can be achieved using available APIs on PSA Build Reconciliation procedure Dependent on the scenario this can include checking the technical data transfer only or additional check on semantics (aggregation, calculation in extraction). See How To Validate Data In the InfoCube By Comparing to Data In the PSA and How To Reconcile data between SAP source systems and SAP NetWeaver BI SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 13

14 Focus area: Data Reconciliation in SAP NetWeaver BI SAP NetWeaver BI DataStore Object no customer defined transformations! Multi Provider VirtualProvider Generic DataSource Original DataSource with direct access Reconciliation DataSource in Business Content First DataSources have been shipped in Business Content for SAP NetWeaver 2004s BI Original DataSource SAP Source system Reconciliation DataSource New in SAP NetWeaver 2004s! * Can be enhanced by customer specific exception sending proactive alerts when data quality issue occurs SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 14

15 Agenda Overview Data Quality Management Data Validation Error Handling Error Resolution SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 15

16 Error Handling in SAP NetWeaver BI Error Handling in SAP NetWeaver BI consists of: What to do in case of errors? Abort data loading or continue data loading on valid data Report or do not report on valid data Configure up to which threshold invalid data is acceptable Termination after a certain number of errors How to monitor invalid data? Show error status in original requests in PSA and in separate error stack How to correct the invalid data? Manual correction or automated correction (to be implemented) of invalid data in error stack (in SAP BW 3.x: error request) More complex error resolution scenario involving the source system or PSA or other objects in your Data Warehouse See more details in next chapter Error Resolution Recommendation: Correct errors as early as possible in the data flow! SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 16

17 Error Handling in SAP BW 3.x InfoProvider Corrected records Update Rules PSA Manual or automated correction Error Request Original Request Invalid records InfoSource Transfer Rules DataSource Valid records InfoPackage Source system SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 17

18 Error Handling in SAP NetWeaver 2004s - I Error DTP Corrected records Valid records InfoProvider Data Transfer Process Manual or automated correction Error Stack Invalid records DTP Transformation InfoSource Transformation All records No error handling available in InfoPackages Invalid data can be written to error stack Termination after certain number of errors can be configured (like in SAP BW 3.x) DataSource Source system SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 18

19 Error Handling in SAP NetWeaver 2004s - II Maintenance of Error Stack key in Data Transfer Process Semantic key can be defined More key fields = potentially less records in error stack If Data Store Objects are connected, their key is taken as initial default Error Stack New records with the same key will be filtered out. In the same request and in subsequent requests Once a request is deleted in the InfoProvider, the related data records in error stack are automatically deleted. Error DTP Add. KEY DataSource Data Store Object Data Transfer Process SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 19

20 Focus Area: Data Transfer Process and Temporary Storage Configure automatic deletion of temporary storage Activate temporary storage for each sub-step of the Data Transfer Process Identify the detail level of temporary storage Temporary storage in the data transfer process for Efficient restart of data transfer process in case of error Temporary storage is used for restart in case of complete abort of process Reloading of corrected records from Error Stack is done using the Error DTP Easy monitoring of invalid data records SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 20

21 Error Handling Error Handling Summary Check table for the impact of the error handling settings for erroneous records No Error handling (InfoPackage) No update, no reporting Update valid records, no reporting Update valid records, reporting possible Monitor entry X X X X Abort of update X X Upd. valid records X X Marked in tem. storage X X X Update into Error Stack X X Color of Request red red red green SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 21

22 Agenda Overview Data Quality Management Data Validation Error Handling Error Resolution SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 22

23 Error Resolution in SAP NetWeaver BI SAP NetWeaver BI offers the following error resolution options: During data load Error Handling After data load Automated correction of invalid data during data loading and transformation (to be implemented) Retain invalid data records in error stack (error request) and correct them manually (or automatically) and subsequent transfer of corrected data records from the error stack to the InfoProvider using the Error DTP functionality (created automatically within the DTP maintenance) Correction of invalid data without deletion by scheduling a (Full) repair request against Overwriting Data Store Objects of your Data Warehouse Layer by loading (additive) cancellation records to relevant InfoProviders (Selective) Deletion of invalid data and reconstruct (corrected) data from source tables (full upload) and reconstruct data from the delta queue (repeat delta update) and reconstruct (corrected) data from PSA and reconstruct (corrected) data from your Data Warehouse Layer Analysis and Repair of BI Objects (RSRV) SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 23

24 Focus area: Overwrite data in SAP NetWeaver 2004s Data in DataStore Object (Aggregation type = Overwrite ) Data in DataSource / PSA Order Status Quantity 719 C 12 KG 720 C 10 KG 721 O 5 KG Order Status Quantity 720 C 8 KG Invalid data gets overwritten! DTP Delta Update Data in source system Order Status Quantity 719 C 12 KG 720 C 8 KG 721 O 5 KG InfoPackage Full Update SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 24

25 Focus area: Analysis and Repair of BI Objects Transaction RSRV Checks the consistency of data and objects stored in SAP NetWeaver BI Some tests are capable to repair inconsistencies and errors Individual test packages can be created combining different elementary tests Test Packages can be scheduled periodically using program RSRV_JOB_RUNNER in process chains Examples for tests: Unauthorized characters in characteristic values Check characteristic values with conversion exit Consistency of the time dimension for an InfoCube PSA Duplicate Record Check Analysis of texts of BEx Objects for codepage errors SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 25

26 Summary Data Quality in Data Warehousing consists of several technical and semantic criteria. It has to be defined on project basis by business and IT department. SAP NetWeaver BI offers various tools for Data Validation & Error Handling that will assist you to easily detect and correct invalid data. Your Enterprise Data Warehouse design plays an important role in providing a reliable Data Warehouse Layer for efficient Data Quality Management. Some situations require more complex error resolution scenarios. If so, choose the appropriate error resolution measure by correcting the error as early as possible in your data flow. SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 26

27 Outlook Integrate the existing BI based solution capabilities by Addressing IQ management integrated into process platform based on the Enterprise Information Management approach to avoid and, if necessary, correct problems as early as possible in the information lifecycle. Providing one IQ design time enabling ESA integrated model driven approach and make IQ models shareable/reusable in ALL application domains (process platform, application development etc. ). Consolidate this way all existing solutions in the platform in one framework. Offer IQM as an integrated solution, supporting the complete information control loop by providing necessary: models processes technical capabilities ( own / partners ) tight application integration SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 27

28 Copyright 2006 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, Outlook, and PowerPoint 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, System i, System i5, System p, System p5, System x, System z, System z9, z/os, AFP, Intelligent Miner, WebSphere, Netfinity, Tivoli, Informix, i5/os, POWER, POWER5, POWER5+, OpenPower and PowerPC are trademarks or registered trademarks of IBM Corporation. Adobe, the Adobe logo, Acrobat, PostScript, and Reader are either trademarks or registered trademarks of Adobe Systems Incorporated in the United States 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, ICA, Program Neighborhood, MetaFrame, WinFrame, VideoFrame, and MultiWin are trademarks or registered trademarks of Citrix Systems, Inc. HTML, XML, XHTML and W3C 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. MaxDB is a trademark of MySQL AB, Sweden. SAP, R/3, mysap, mysap.com, xapps, xapp, SAP NetWeaver, 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 the trademarks of their respective companies. Data contained in this document serves informational purposes only. National product specifications may vary. 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 prior written permission of SAP AG. This document is a preliminary version and not subject to your license agreement or any other agreement with SAP. This document contains only intended strategies, developments, and functionalities of the SAP product and is not intended to be binding upon SAP to any particular course of business, product strategy, and/or development. Please note that this document is subject to change and may be changed by SAP at any time without notice. SAP assumes no responsibility for errors or omissions in this document. SAP does not warrant the accuracy or completeness of the information, text, graphics, links, or other items contained within this material. This document is provided without a warranty of any kind, either express or implied, including but not limited to the implied warranties of merchantability, fitness for a particular purpose, or non-infringement. SAP shall have no liability for damages of any kind including without limitation direct, special, indirect, or consequential damages that may result from the use of these materials. This limitation shall not apply in cases of intent or gross negligence. The statutory liability for personal injury and defective products is not affected. SAP has no control over the information that you may access through the use of hot links contained in these materials and does not endorse your use of third-party Web pages nor provide any warranty whatsoever relating to third-party Web pages. SAP AG 2006, Data Quality Management in SAP NetWeaver BI / 28

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