SAP Master Data Governance 9.0 Consolidation. August 2016

Transcription

1 SAP Master Data Governance 9.0 Consolidation August 2016

2 Agenda 1. Overview and use cases 2. Consolidation process flow 3. General functions 2

3 SAP Master Data Governance Covering consolidation and central governance Consolidate master data from de-central sources Centrally govern and distribute master data LoB processes De-central IT landscapes SAP MDG On-premise systems Cloud applications Cloud 3 rd Party apps Other Mergers & acquisitions 3

4 SAP Master Data Governance Covering many use cases (consolidation optionally combined with central governance) Central governance only Ensure clean data at the point of creation or change Continuous consolidation for analytical purposes Ensure data consistency via consolidation for analytical use cases, e.g., global spend reporting 1 2 Consolidation for initial load before central governance Ensure data correctness and accuracy via consolidation run before starting central governance Consolidation for Mergers & Acquisitions (M&A) Ensure data consistency via consolidation runs every time it comes to M&A process while continuously running central governance Continued hybrid approach Deliberately keep some parts under local ownership with continuous consolidation and some parts under central governance 4

5 Consolidation with SAP MDG 9.0 Domain Coverage and Choice of Governance Domains Business Partner, incl. customer and vendor (*) Material Master (*) Custom Objects (**) Choice of Governance Option Can be used with or without central governance Choice: activation with change request Choice: use of MDG, central governance validations (*) for detailed information about the coverage on table-level, see IMG activity Configure Process Models. Extensibility is supported. (**) based on single database table, MDG active area (flex) not supported. 5

6 SAP Master Data Governance, consolidation Process Flow Data Load Open to SAP HANA services (Smart Data Integration), non-hana based ETL mechanisms from SAP, and non-sap ETL options Standardize Match Calculate best record Validate Activate Validate and enrich address data Possibility to connect to 3 rd party tools for standardization and enrichment Usage of BRF+ for standardization and enrichment Find duplicates based on customer specific matching rules Review Match result Create Best Records based on approved match groups BRF+ can be used for customer-specific Best Record Calculation Review Best Record Calculation result Validate best records against backend customizing to verify whether records can be activated Validate against Central Governance checks (BAdI, BRF+) Provide consolidated master data for analytical or operational use Option to activate directly, or indirectly triggering post processing using central governance 6

7 SAP Master Data Governance, consolidation Prerequisite: Data Load Data Load Open to SAP HANA services (Smart Data Integration), non-hana based SAP ETL, and non-sap ETL options SAP HANA In Memory Platform Services Smart Data Integration SAP HANA smart data integration provides HANA native real-time transactional replication, batch bulk ETL and transformations into SAP HANA from both SAP and non-sap application databases, on premise and Cloud Non HANA-based ETL options: Real Time Replication: SAP LT Replication Server Bulk/Batch ETL: SAP Data Services for all bulk batch ETL scenarios from both SAP and non-sap application sources (incl. transformation) 7

8 SAP Master Data Governance, consolidation Standardizing data Standardize Match Calculate best record Validate Activate SAP HANA In Memory Platform Services Smart Data Quality SAP HANA smart data quality (BP model only) transforms data to common format to enable matching. Includes out-of-the-box address validation and address standardization. Non HANA-based standardization option possible: SAP Data Services, called via BAS interface (BP model only) Standardization using BRF+ Process-step specific KPI s visualized 8

9 SAP Master Data Governance, consolidation Matching data Standardize Match Calculate best record Validate Activate SAP HANA In Memory Platform Services Smart Data Quality SAP HANA Fuzzy Search ensures high detection quality in search and matching based on customer specific rule sets SAP HANA smart data quality (BP model only) provides batch matching features to identify duplicate data Non HANA-based matching option possible: SAP Data Services, called via BAS interface (BP model only) Simple database matching (material model only) Process-step specific KPI s visualized 9

10 SAP Master Data Governance, consolidation Matching data Standardize Match Calculate best record Validate Activate Match review to verify the correctness of identified duplicates and provide the appropriate match groups for subsequent calculation of best record. Approve or reject match group Delete or split single or multiple records 10

11 SAP Master Data Governance, consolidation Calculating the best record Standardize Match Calculate best record Validate Activate Create best record according to survivorship rules. These include e.g.: Survivorship rule types on table level: source system reliability, recency, BRF+ Survivorship rule types on field level: completeness 11

12 SAP Master Data Governance, consolidation Validating data Standardize Match Calculate best record Validate Activate Check correctness of new, best, and updated records Validation of records against backend customizing to verify whether records can be activated (in combination with central governance validation also against BAdI and BRF+ checks) Process-step specific KPI s visualized: status of new Single Records, new Best Records, and status of Updates 12

13 SAP Master Data Governance, consolidation Activating data Standardize Match Calculate best record Validate Activate Provide consolidated data for analytical or operational use, or initiate governance. Activation type can be flexibly configured Direct activation (typically for analytical use cases) Activation initiating central governance (with change request) 13

14 Worklist Overview of all processes in various states Navigation to process details Ability to create and delete processes Process monitoring, e.g. long running activation of process with high volume of data 14

15 Process UI to track the process Show the progress of a consolidation process See results for each process steps (chart or table) Drill-down into results 15

16 Show data of all tables Show content of all affected tables in each process step Navigate between tables using tabs 16

17 Show changes Show all changes of a record Drill-down into field level information Available for all related tables 17

18 Rollback Clear result data after a process step Rollback to any step in the process Re-run process steps (possibility to change settings for following steps) 18

19 Configuration of steps during runtime Step configuration during runtime Settings from process template can be adjusted 19

20 Remove records / split process If a process is stopped for review, you can Remove records from process with several options, e.g. records with errors into separate process for later processing Removal can be triggered from table view or using drill-down from chart view Also available as separate process step to automatically remove records in the background (Filter and Remove step type: FAR) 20

21 Edit capabilities Replace field values for selected records Clear field values for selected records 21

22 Show messages Show messages for each step Navigate into affected records 22

23 Audit Trail All activities on processlevel (e.g. change of configuration, continue the process, roll-back the process) are tracked Audit trail can be displayed in the process UI Drill-down into details (e.g. match review) 23

24 Fiori UI personalization Personalization for showing and hiding fields Define number of maximum hits in table view (performance relevant) Table views can be saved as variants 24

25 Filter and Remove (FAR adapter) Automatically removes records or move records into a new duplicate process After matching: move open match groups After best record calculation: move specific groups of records After validation: move records with warnings or errors Remaining records can be processed directly 25

26 Using service to trigger consolidation process (integration scenario) Client Systems Loyalty Program Service Center Social Media 3 rd party CRM Replicate data/key mapping back to client systems SAP C4C SAP CRM Other Systems Web Service (SOA) Out-of-the-box integration (Create and Change) Integration using Web Service call (Create and Change) SAP MDG, Consolidation Standardize Match Review for open Match Groups Match Calculate Best Record Validate Activate Approved Match Groups will be processed automatically MDG Central Master Data 26

27 Additional features 1/2 Review UI for Best Record Calculation Shows how a best record has been built (based on which rules) Possibility to edit calculated data Define upper threshold for Fuzzy matching and matching using BAS adapter Match groups with matches above upper threshold will be approved automatically Match groups with matches below upper threshold are open and have to be approved/rejected manually Records within open match groups will be processed separately (as single records) Integration of BRF+ Standardization Best Record Calculation Validation (Central Governance rules can be applied) Update step to change/enrich data (on table level) 27

28 Additional features 2/2 Retention time Possibility to keep the process data (for a specific time frame) after the last process step for verifications Key- and value mapping Standardization adapter to transform incoming source data using DRF mapping tables Enable 4-eyes principle Defines who is allowed to continue with the next process step (based on customizing) 28

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