Providing real-time, built-in analytics with S/4HANA. Jürgen Thielemans, SAP Enterprise Architect SAP Belgium&Luxembourg

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1 Providing real-time, built-in analytics with S/4HANA Jürgen Thielemans, SAP Enterprise Architect SAP Belgium&Luxembourg

2 SAP HANA Analytics Vision

3 Situation today: OLTP and OLAP separated, one-way streets only OLTP- System of Records: Information in only OLAP - System of Engagement: Information out only No real-time reporting Semantic Wall No write-back Relational table design Data replication: Usually not real-time, long-running ETL-Jobs (Extraction- Transfer-Load) Redundant data storage OLAP 2015 SAP SE or an SAP affiliate company. All rights reserved. 3

4 Combining transactions and analytics on a single in-memory platform Decisions and Actions on Old Data Multiple Copies of the Data ETL and Batch Processing Efforts and Costs Instant Insight to Action on Live Data One Copy of the Data No ETL and Batch Processing 2015 SAP SE or an SAP affiliate company. All rights reserved. 4

5 Virtual Data Modelling

6 Types of Analytics Data Warehouse / Data Marts Types of reporting access scenarios Data Marts / Data Warehouse Information needs Real Time Visibility Consolidated view Ad-Hoc Self- Service BI Archive Analysis Predictive Analysis Sentiment Analysis Architecture Real Time Data Mart Operational Data Mart Data Warehouse/ EDW Agile Data Marts Data Marts (Audit / SOX) Predictive Data Marts Unstructured Data Marts Access method to source data Streams / Feeds Direct / Database Replication ETL / ELT / Replication ETL / ELT/ Replication Federated Queries / ETL ETL / ELT/ Replication Federation of Data & Query Event Machine Transactional System of Record Transactional Analytical Systems of Record & Engagement Archived Information All sources Social Source of information High variety of information sources Extensive information needs Different kinds of Data Marts for various Use Cases 2015 SAP SE or an SAP affiliate company. All rights reserved. 6

7 SAP HANA Information Views Virtual Data Modeling approach as a key SAP HANA concept 2015 SAP SE or an SAP affiliate company. All rights reserved. 7

8 Types of Analytics Data Warehouse / Data Marts Specific Operational Data Marts: Virtual Data Models Visibility UI s BI Application Operational Data Mart Direct / Database Replication Transactional system View Transactional System of Record Virtual Data Model View View View View View Database Layer, e.g. SAP HANA Physical Tables 2015 SAP SE or an SAP affiliate company. All rights reserved. 8

9 SAP Business Suite real-time analytics architecture (SAP HANA Live) No latency No data duplication Ready-to-use content Integration scenarios with SAP BW SAP Business Suite Application Hybrid Transactional and Analytical Applications e.g. SAP Smart Business cockpits Analytical Apps and BI Clients e.g. SAP BusinessObjects BI HANA Database Layer Virtual Data Model on Physical Tables Atomic Instantaneous Pre-defined 2015 SAP SE or an SAP affiliate company. All rights reserved. 9

10 A new concept for S/4HANA

11 Today transactions and analytics are handled separately but in reality, business processes are often a sequence of transaction analysis transaction Enter Order Check Customer Churn Probability Adjust discount percentage Create new employee salary data Analyze yield and scrap of plants Check updated salary projection for cost centers Send to all plant managers above/below certain thresholds 2015 SAP SE or an SAP affiliate company. All rights reserved. 11

12 Built-in Analytics Imagine, one day we will have Bi-directionally embedded Analytics in a transaction screen Purchase Request: 4711 Material : Supplier : Default Discount : Embedded multidimensional report shows suppliers for the entered Material No. and their Delivery Performance + trading volume : : A supplier is selected in the report, and its ID and other relevant data is transferred to the corresponding fields in the Activity. 2 Supplier Overview for Material 515 Current month Supplier 1 Delivery Performance Personalize Trading Volume Last Year 3 Navigate to a full screen version of the report and perform multidimensional analysis, personalize report and share data % 550 K % K % 270 K 2015 SAP SE or an SAP affiliate company. All rights reserved. 12

13 Continue with Supplier Overview for Material 515 Current month Personalize Integration into SAP Smart Business Supplier Delivery Performance Trading Volume Last Year % 550 K % K % 270 K More concepts? Visualize using SAP BI Search/Fact Sheets 2015 SAP SE or an SAP affiliate company. All rights reserved. 13

14 The new Built-in Analytics Vision Generic SAP BI clients and Analytical Apps e.g. SAP BusinessObjects Analysis for Office, SAP BusinessObjects Design Studio, Smart Business cockpits Built-In Analytics: Hybrid Transactional and Analytical Applications e.g. SAP Embedded BI or SAP Smart Business cockpits Extraction to SAP BW* Enabler for Read-access for Fact Sheets Search Virtual Data Model Specific Analytics Models Virtual Data Model for Search, operational and analytical processing Customer Extensions Customer Extensions HANA Platform SAP HANA Platform Application Tables *This way SAP enables existing BW extractors to also support Simple Finance and other Innovations in SAP S/4HANA External Sources / IOT 2015 SAP SE or an SAP affiliate company. All rights reserved. 14

15 SAP S/4HANA real time analytics architecture No latency No data duplication Ready-to-use content Integration scenarios with SAP BW SAP S/4HANA Application Hybrid Transactional and Analytical Applications e.g. SAP Smart Business cockpits Analytical Apps and BI Clients e.g. SAP BusinessObjects BI Full ABAP Lifecycle Integration Supporting ERP authorizations Supporting ERP hierarchies Part of the general Extensibility concept Supporting more business cases (analytics, search, fact sheets, planning, ) ABAP Layer Virtual Data Model, based on Core Data Services (CDS) Transient BEx Queries HANA Database Layer SQL-Runtime-Views on Physical Tables Atomic Instantaneous Pre-defined 2015 SAP SE or an SAP affiliate company. All rights reserved. 15

16 Types of Analytics Data Warehouse / Data Marts Virtual Data Models as part of transactional systems Example: SAP S/4HANA UI s BI Smart Business Transactional Fiori SAP S/4 HANA View Finance Virtual Data Model (based on open CDS) View View View View View Business Transactions Logistics Etc. Database Layer, e.g. SAP HANA Physical Tables 2015 SAP SE or an SAP affiliate company. All rights reserved. 16

17 Demo

18 To Datawarehouse or not to Datawarehouse?

19 SAP S/4HANA Analytics + SAP Business Warehouse Comprehensive operational + historical analytics and planning powered by SAP HANA Multi-channel Unified User Experience SAP S/4HANA (incl. Virtual Data Model) SAP NetWeaver SAP NetWeaver BW SAP HANA PLATFORM Application Services New SAP Apps Partner Apps SAP Business Warehouse on SAP HANA Strategic and tactical Integration, harmonization, crosssystem consistency Consumption Planning Multi-sourced data Preconfigured content Data lifecycle Data governance Full-blown analytical suite Database Services (include SAP HANA Views) Synchronizations Services SAP S/4HANA Analytics Operational data Real-time Lightweight modeling and consumption Extensible Uniform Basis for multiple embedded use cases Model reuse in analytical applications All analytics requirements fulfilled with one unified solution Data Integration Scenarios are possible in multiple hybrid system setups 2015 SAP SE or an SAP affiliate company. All rights reserved. 19

20 Summary

21 Key Takeaways SAP Business Suite 4 SAP HANA provides enhanced analytical capabilities due to the architecture based on SAP HANA the value proposition gets enhanced by the unique possibilities given with the new architecture, including reimagined simplified business processes, user experience and business decisions The new concept of one semantic layer for search, operational and analytical processing using open CDS views optimized for SAP HANA technology and infrastructure, allows real-time operational reporting and will be rolled out in all deployments of S/4HANA, cloud and on premise S/4HANA Analytics complements and does not replace SAP Business Warehouse (powered by SAP HANA) With SAP Smart Business our latest generation of decision supporting applications powered by S/4HANA and SAP Fiori combining new working models with a consumer-grade, multi-channel user experience SAP SE or an SAP affiliate company. All rights reserved. 21

22 Thank you Contact information: F name MI. L name Title Address Phone number

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