Master Data Governance, Enterprise Edition. Gerhard Kwak, Product Management - Master Data Governance November 2013

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1 Master Data Governance, Enterprise Edition Gerhard Kwak, Product Management - Master Data Governance November 2013

2 Legal disclaimer The information in this presentation is confidential and proprietary to SAP and may not be disclosed without the permission of SAP. This presentation is not subject to your license agreement or any other service or subscription agreement with SAP. SAP has no obligation to pursue any course of business outlined in this document or any related presentation, or to develop or release any functionality mentioned therein. This document, or any related presentation and SAP's strategy and possible future developments, products and or platforms directions and functionality are all subject to change and may be changed by SAP at any time for any reason without notice. The information in this document is not a commitment, promise or legal obligation to deliver any material, code or functionality. 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. This document is for informational purposes and may not be incorporated into a contract. SAP assumes no responsibility for errors or omissions in this document, except if such damages were caused by SAP s willful misconduct or gross negligence. All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. Readers are cautioned not to place undue reliance on these forwardlooking statements, which speak only as of their dates, and they should not be relied upon in making purchasing decisions SAP AG. All rights reserved. 2

5 Data Cleansing Overview Identifying Duplicates Cleansing Case Merge Create Cleansing case out of Duplicate Check popup is planned for a future MDG 7.0 SP 2013 SAP AG. All rights reserved. Ramp-Up Knowledge Transfer Customer 5

Data Cleansing Identifying Duplicates Before creating a cleansing case and do the merging the data potential duplicates have to be identified.

6 Data Cleansing Identifying Duplicates Before creating a cleansing case and do the merging the data potential duplicates have to be identified. Within MDG duplicates can be identified during Search (within search result list) Single object maintenance (duplicate check) Outside MDG Hand over cleansing case from client system to MDG Hub Full data base scan (using external tools) Identified potential duplicates will be stored within a cleansing case for further processing 2013 SAP AG. All rights reserved. 6

duplicate records Identify one Target Record Identify one or more Potential Duplicates as

7 Data Cleansing Cleansing Case Create a new cleansing case, search and and assign potential duplicates Search cleansing case (also can be used as worklist) Check details of potential duplicate records Identify one Target Record Identify one or more Potential Duplicates as well as No Duplicates Start Cleansing and create a Change Request 2013 SAP AG. All rights reserved. 7

Hereby it s possible to copy the data including all dependant data (e.g. address including its communication data).

8 Data Cleansing Merge During the merge process all relevant data from Potential Duplicate records can be taken over to the Target Record. This can be done using the keep flag as well as using drag and drop functionalities. Hereby it s possible to copy the data including all dependant data (e.g. address including its communication data). In parallel it is also possible to edit data of Target Record directly. As result of the merge process a workflow process will be triggered 2013 SAP AG. All rights reserved. 8

9 Single Object Maintenance HANA Search / Duplicate Check All Business Partner data is stored within HANA MDG running on HANA MDG running on different DB connected side-by-side to HANA Hana based error tolerant search Hit List contains ranking and is sorted by ranking Search types Additional search provider within MDG with search fields / hit list Search via drill down search 2013 SAP AG. All rights reserved. 9

10 SAP HANA-based Search and Duplicate Check Search term and attribute-based Using a single term as free-style search against all attributes Search per attribute with dedicated thresholds Calculated similarity rank Sorted result weighted score across all attributes Powerful duplicate detection Integrated in process to prevent duplicates from being even created High detection quality using SAP HANA fuzzy search and matching Similarity score used to identify and sort potential duplicates Deployment Options SAP MDG 7.0 EhP6 or EhP7 for SAP ERP 6.0 Any Database Option 1: Side-by-Side replicate search Option 2: MDG on HANA SAP MDG 7.0 EhP7 for SAP ERP 6.0 SAP HANA SAP HANA 2013 SAP AG. All rights reserved. 10

Multi-attribute drill-down based on SAP HANA Using SAP HANA s columnar in memory

intrinsic structures in your master data Find attribute values that need

objects are displayed No need for guessing, you find what is there Combined with

11 Multi-attribute drill-down based on SAP HANA Using SAP HANA s columnar in memory storage for rapid access Slice & dice master data Filter and analyze the intrinsic structures in your master data Find attribute values that need companywide harmonization Find instead of search Only existing attributes and objects are displayed No need for guessing, you find what is there Combined with fuzzy search Search terms and drill-down can be used together 2013 SAP AG. All rights reserved. 11

13 SAP Roadmap for Enterprise Master Data Management

Overview of SAP road map for Enterprise MDM Systems under central governance Enterprise master data Create SAP IM (Information Management) on Hana SAP MDG, enterprise edition* Procurement Supply

14 Overview of SAP road map for Enterprise MDM Systems under central governance Enterprise master data Create SAP IM (Information Management) on Hana SAP MDG, enterprise edition* Procurement Supply Chain Consolidate SAP MDG SAP MDG Customer Enterprise Master Data Management PLM Systems not under central governance SAP NW MDM SAP NW MDM Finance Manufacturing Solution today Planned innovations Future direction 2012 SAP AG. All rights reserved. Internal 14

Enterprise master data landscape Systems under

LoB Finance LoB PLM Other LoB Consolidate master

Enterprise master data Create master data based

Reporting and analytics Business networks Cloud

15 Enterprise master data landscape Systems under central governance LoB Customer LoB Procurement LoB Finance LoB PLM Other LoB Consolidate master data Systems not under central governance Enterprise master data Create master data based in-line with business processes Legacy systems Reporting and analytics Business networks Cloud Solution today 2012 SAP AG. All rights reserved. Internal 15

16 Overview of SAP road map for Enterprise MDM Systems under central governance Enterprise master data Create SAP IM (Information Management) on Hana SAP MDG, enterprise edition* Procurement Supply Chain Consolidate SAP MDG SAP MDG Customer Enterprise Master Data Management PLM Systems not under central governance SAP NW MDM SAP NW MDM Finance Manufacturing Solution today Planned innovations Future direction * Not yet officially named 2012 SAP AG. All rights reserved. Internal 16

17 Portfolio of planned innovations Overview SAP IM (Information Management) on Hana Embed capabilities from IM on Hana as a set of master data services Extend SAP MDG for consolidation and co-existence powered by SAP HANA SAP MDG, enterprise edition SAP MDG SAP NW MDM Continue to innovate SAP MDG for central creation stand-alone use case on any DB Continuous enhancements in line with Customer Connection program Planned innovations SAP MDG SAP NW MDM 2012 SAP AG. All rights reserved. Internal 17

Planned innovations for SAP MDG, Enterprise Edition Enhanced capabilities of MDG built on the SAP HANA

Business Networks Distributed Creation Vendor, Supplier Not Under Central Governance Information

Analytics Central Creation Multiple Domains Consolidation Multiple Domains Central Creation Multiple

18 Planned innovations for SAP MDG, Enterprise Edition Enhanced capabilities of MDG built on the SAP HANA platform Under Central Governance SaaS Distributed Creation Customer CRM Distributed Creation Customer Business Networks Distributed Creation Vendor, Supplier Not Under Central Governance Information Provider High Volume Consolidation Multiple Domains MDGee High Volume Consolidation Multi-domain Analytics Central Creation Multiple Domains Consolidation Multiple Domains Central Creation Multiple Domains SAP ERP Non-SAP ERP SAP ERP Non-SAP ERP Planned innovations 2012 SAP AG. All rights reserved. Internal 18

19 Extending SAP MDG for Big Data and multi-vector MDM SAP MDG, enterprise edition Governance and stewardship processes and business logic Consolidate Govern Distribute SAP HANA Master data services (IM on Hana) Standardization Match / Match Review Validation Enrichment Best Record Calculation Fuzzy Search Monitoring Multi domain Repository Planned innovations 2012 SAP AG. All rights reserved. Internal 19

20 Overview of SAP road map for Enterprise MDM Systems under central governance Enterprise master data Create SAP IM (Information Management) on Hana SAP MDG, enterprise edition* Procurement Supply Chain Consolidate SAP MDG SAP MDG Customer Enterprise Master Data Management PLM Systems not under central governance SAP NW MDM SAP NW MDM Finance Manufacturing Solution today Planned innovations Future direction 2012 SAP AG. All rights reserved. Internal 20

21 Future direction Governance of master data integrated into Line of Business processes and Big Data analytics (e.g., Product 360 integration; Retail store consolidation for Big Data analytics) Cloud Bridge master data across cloud and on-premise applications and services (e.g., on-demand CRM/on-premise ERP; enrichment services) Procurement Supply Chain Mobile Customer Enterprise Master Data Management PLM Business Networks Trusted master data for mobile apps (e.g., trusted product master data for mobile scanning apps, social CRM integration) Finance Manufacturing Seamless exchange of trusted master data with business partners (e.g., Ariba integration, GDS) Social Networks Bridge insight from social and enterprise master data (e.g., social CRM/Customer 360 integration) Future direction 2012 SAP AG. All rights reserved. Internal 21

23 Outlook SAP Master Data Governance, Enterprise Edition (SAP MDGee) Consolidation + Central Create

24 SAP MDGee One integrated end-to-end MDM solution The goal of SAP MDGee is to become one integrated end-to-end MDM solution for Consolidation, Central Governance, and Analytics on one box running on SAP HANA. What does integrated solution mean? Harmonized Synchronized Integrated Process steps relevant for Consolidation and Central Governance behave the same way, e.g. Load Data Data Standardization / Data Enrichment Match / Match Review / Best Record Calculation Refinement Data relevant for Consolidation and Central Governance is always in sync, e.g. Active data of objects under governance Offer integrated end2end scenarios with steps in Consolidation and Central Governance Integrate new source system and put data under Governance 2012 SAP AG. All rights reserved. Internal 24

25 Process Flow: Consolidate / Govern new source system MDG Enterprise Edition on HANA S O U R C E Load Consolidation Governance Refine Govern Replicate Consolidate Synchronize 2012 SAP AG. All rights reserved. Internal 25

26 Process Flow: Load Load Support loading into Buffer Tables from SAP systems Non-SAP systems Out-of-the-box loading of ERP Customer Master from SAP ERP systems SAP Business Partner from SAP CRM, SAP SRM, SAP ERP, etc SAP AG. All rights reserved. Internal 26

27 Process Flow, Consolidate: Overview Consolidate The consolidation process consists of Data Standardization Matching / Match Review Calculate Best Record Refinement 2012 SAP AG. All rights reserved. Internal 27

28 Process Flow, Consolidate: Data Standardization & Matching Consolidate Data Standardization - bring data to common format to enable matching Name standardization Address validation and standardization Matching duplicate detection Multiple out of the box matching strategies Name and Address Name and Phone Identification Numbers Exact match (telephone) and fuzzy match (name) Multi-level multi-valued matching, e.g. match between multiple addresses Creating a match group containing possible matched records Support matching in different languages 2012 SAP AG. All rights reserved. Internal 28

29 Process Flow, Consolidate: Best Record Calculation Consolidate Calculate a Best Record - retrieve match group and create Best Record according to survivorship rules Record level and field group level survivorship rules Field level rule overwrites record level rule Survivorship rule types Completeness Source system reliability Longest text Recency Assign rule types per Record Field group 2012 SAP AG. All rights reserved. Internal 29

30 Process Flow, Consolidate: Refinement Refine Refinement: Ability to manually correct data issues & and refine the consolidation results Ad-Hoc Refinement: manual multi-records data refinement to fix data issues & complete missing data Auto refinement Automatic data correction based on previous manual user refinement actions Becomes part of subsequent consolidation processes Best Record Re-clustering: remove or add source records from the best record cluster 2012 SAP AG. All rights reserved. Internal 30

31 Process Flow: Govern, Initiate Governance Govern Filter on multiple different criteria Result list Display customer list Visualize important customer information via charts Select records to be governed Create change request in MDG (single / multiple customers) Put customers directly to MDG Active Area (mass data, e.g. load all customers of a new source system) Process is mass enabled Erroneous customers will be put into a change request 2012 SAP AG. All rights reserved. Internal 31

Process Flow: Replicate Replicate Replication To SAP

User Replication Techniques Process ALE for SAP

service for SAP systems (new SAP releases) and non

System Replication Features Flexibility to replicate

defining filters or replicating manually Support of

client systems Support of different customizing keys

32 Process Flow: Replicate Replicate Replication To SAP System is delivered out-of-the-box To non SAP systems User Replication Techniques Process ALE for SAP systems (including older SAP releases) new SOA service for SAP systems (new SAP releases) and non SAP systems Data replication Non-SAP System SAP System Replication Features Flexibility to replicate selected data only to a specific client system by defining filters or replicating manually Support of different supplier and customer Ids between hub and client systems Support of different customizing keys between hub and client systems 2012 SAP AG. All rights reserved. Internal 32

33 Process Flow: Synchronize Synchronize Synchronize consolidation with each new / changed customer within Governance Synchronize data as well as key mapping Single records synchronized nearly real time Mass data synchronized via special report Synchronize governed records Adding new source system and selecting many records to be put under governance Re-synchronize data no more being in sync (e.g. due to system break down, program error etc.) 2012 SAP AG. All rights reserved. Internal 33

34 Questions & Answers

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Will S/4HANA and ARIBA change our procurement landscape?

Will S/4HANA and ARIBA change our procurement landscape? Procurement Master Class 15th of March 2018 Linda Braspenning (SAP) Lionel Barette (Aptys Consulting) Legal disclaimer The information in this presentation