EDW Positioning Based on the SAP Real-Time Data Platform. July, 2013

Transcription

1 EDW Positioning Based on the SAP Real-Time Data Platform July, 2013

2 Typical needs in a Enterprise world Introduction

3 Types Analytics & Data Marts Different Analytical needs and the consequences in IT architectures 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 Near-line 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 Complex architecture landscapes including different kind of Data Marts, Data Warehouses and EDWs 2013 SAP AG. All rights reserved. 3

4 Different Needs Different Types of Data Marts for Reporting A data mart is a collection of data coming from subject areas organized for decision support based on the needs of a given domain / group of users. Characteristics of Data Marts: Maximum flexibility for LOBs in data modeling and integration of LOB specific data (Agile) Supporting local business execution Support strategic decision making in LOBs Independently of, or sourced from the centralized corporate EDW layers Reporting on large volumes of granular, transactional data Data latency determined by business requirements batch to real time High Volume Unevenly structured data (Big Data) Predictive Analysis Event and Streaming sources 2013 SAP AG. All rights reserved. 4

5 Examples of Different Types of Data Marts Business Intelligence Tools Operational Data Marts: Real Time Data Reporting on large volumes of granular, transactional data Supporting local business execution ERP Data Operational DataMart Operational Real-time replication and ETL Supplier Data Agile DataMart EDW ETL Other Agile Data Marts: Independently of the highly governed centralized corporate EDW layers Maximum flexibility for LOBS in data modeling and integration of LOB specific data Support strategic decision making in LOBs 2013 SAP AG. All rights reserved. 5

6 Unlock The Power of Your Data Across The Enterprise Enterprise Data Warehousing the single point of truth EDW * characteristics: Consolidate the data across the enterprise to get a consistent and agreed view on your data Combine SAP and other sources together Standardized data model on corporate information Supporting decision making on all organizational levels * EDW and DW are often used interchangebly. For the remainder of this presentation only the term EDW will be used. EDWs require a database plus EDW orchestration tools: EDW orchestration tools are used to manage, model and run the Enterprise Data Warehouse EDW orchestration tools can be shipped as an integrated EDW application Custom built EDWs are based on loosely coupled orchestration tools e.g. ETL tools, Data Modeling tools, Monitoring tools etc SAP AG. All rights reserved. 6

7 Example of a Customer Enterprise Data Warehousing landscape local regional global Master Data Management Master Data Business Intelligence Tools DataMart DataMart Data Warehouse Single Point of Truth DataMart Transactional Data ERP Data Supplier Data Customer Data Other feeding external systems Planning & Forecast Example for global EDW implementation: Architecture to provide the base for entire commercial business intelligence solutions: Local, regional, global Data Marts in addition to global Data Warehouse necessary to meet business users need Data Warehouse as single point of truth with harmonized master data to feed departmental Data Marts and external systems with cleansed data Depending on users requirements reporting on departmental Data Mart or Data Warehouse is possible 2013 SAP AG. All rights reserved. 7

8 Different Approaches What approach is right for you? Different approaches to implement an analytical data foundation Using an Integrated EDW application Model-driven pre-packaged Data Warehouse application as a central component Prebuilt Information and process content Out of the box tool set for modeling, managing, operating, and governing an EDW and its data marts Custom Built Enterprise Data Warehouse Loosely coupled orchestration tools Higher efforts for development and maintenance High flexibility to build custom data models and processes with little enforced governance Open environment to easily import industry models 2013 SAP AG. All rights reserved. 8

9 Different Approaches What approach is right for you? Custom built data marts without EDW integration layer Maximum flexibility for custom data marts specifically built for isolated use cases Easy to build and fast realization time Low level of integration among different data marts Combination of approaches Grow from custom built DMs to an EDW Combine custom built DMs or EDW with integrated EDW application 2013 SAP AG. All rights reserved. 9

10 data volume Data Volume and Complexity considerations Enterprise Data Warehouse, Data Marts huge Very large Data Marts Internet scale business process (e.g. Ebay, Amazon, ) generating huge amounts of (sensor) data Fairly modest challenges regarding semantics, consolidation, harmonization, integration with other data Extreme large EDW Extremely high number of scenarios and combinations of scenarios Extremely high data volumes Data Mart Few data sources Data mart type of setup or operational (OLTP) analytics Moderate number of tables Moderate (need for) integrations between data models EDW Mix of scenarios with small and large amounts of data Many (100s to 10000s) of data models Many ( s) different data sources moderate Complexity: number of scenarios, data models, sources, huge 2013 SAP AG. All rights reserved. 10

11 How does SAP address the needs?

12 SAP Real-Time Data Platform Addressing the architectural needs Business Suite Business Warehouse Business Intelligence Mobile & Embedded Custom Apps SAP RTDP addresses the needs for a packaged EDW framework with SAP BW, as well as custom built EDW and Data Marts SAP NetWeaver BW as strategic offering for packaged EDW frameworks SAP HANA as an in-memory foundation for custom built solutions and in-memory database platform for BW SAP Sybase IQ as disk-based database for custom built petabyte scale EDW and cost effective near-line storage solution (NLS) for BW on HANA 2013 SAP AG. All rights reserved. 12

13 SAP HANA, BW on HANA, Sybase IQ Strong individual solutions SAP HANA SAP HANA Data Platform for business- or mission-critical enterprise applications In-Memory database for transactional and analytic workloads More than 1000 customers with standalone, BW or Business Suite scenarios BW on HANA SAP NetWeaver BW More than customers referring to > productive systems Vast majority: Central EDW, harmonizing many source systems Embedded into mission critical business processes Sybase IQ Sybase IQ Recognized leader in EDW market by Gartner and Forrester Group Industry leading performance and scale benchmarks with installations in 2150 accounts Greater than 96% customer satisfaction rates - consistently 2013 SAP AG. All rights reserved. 13

14 EDW with SAP BW on HANA Data Modeling Layered scalable EDW model Tight integration with native HANA Data Marts In-Memory based OLAP features and Planning engine Agile Data Marts with BW Workspaces Scheduling & Monitoring Process Chains enable workload management for data load processes across systems Rich monitoring capabilities via Admin Cockpit Support of 3rd party tools such as UC4, Tivoli Supportability, Traceability Easy extensible BADI framework for data staging, reporting and authorization Access statistics including Identity handling Possibility to trace on application logic, database access and effect of authorizations Reliable Data Acquisition Open for SAP and non SAP systems Embedded ETL and Streamlined In-Memory Data Staging processes Sophisticated Error Handling Incremental Data Provisioning capabilities Lifecycle Management & Security Hot- / Cold data handling for optimized resource usage Compliant NLS and Archiving Fine-grained security model with mass handling capabilities Business Content Enables fast implementation Leverages SAP s proven knowledge in business applications and industries Model-driven approach 2013 SAP AG. All rights reserved. 14

15 EDW with SAP HANA Data Modeling Entity-Relationship models Procedural extensions for complex views Support for planning operations on views Real-time transformation 3NF to analytic view Scheduling & Monitoring DB level monitoring in SAP HANA Studio Explain plans for SQL statements No scheduling capabilities, requires additional tools such as SAP Business Objects Data Services Reliable Data Acquisition Support for virtually any kind of data Support for SAP or 3 rd party ETL tools Real time replication and event stream connection Lifecycle Management & Security Repository for design time artifacts Database security with user and role concept Privilege concept for design time and runtime Content lifecycle management Supportability, Traceability Technical tracing of database kernel operations Alerting for vital database parameters Integration with SAP Solution Manager Business Content Business Suite data models available as content packages (SAP HANA Live, RDS) Application content available as delivery units 2013 SAP AG. All rights reserved. 15

16 EDW with SAP Sybase IQ Data Modeling Leading open modeling tool: PowerDesigner High flexibility in schema definition Ad-Hoc SQL, structured and unstructured data support, and integrated full text search In-database analytics, MapReduce API, Hadoop and R-Integration Scheduling & Monitoring Web-based SAP Sybase Control Center as DB administration & monitoring tool ETL scheduling with DataServices Open and certified support for 3rd party monitoring solutions Supportability, Traceability Database auditing: logins, data update timestamps, and administrative actions Support of multiple trace and debug levels Extensive set of system stored procedures for diagnostics Reliable Data Acquisition Open for SAP and non SAP systems Data Services as powerful, approved ETL tool Open and certified support for 3 rd party ETL solutions Real Time Data Loading via ESP and SRS Lifecycle Management & Security Built-in disk based Information Lifecycle Management Role-based access control, LDAP authentication, strong database, column, and transport layer encryption (FIPS certified) New generation petabyte-scale store Resilient Multiplex grid architecture Business Content Prebuilt vertical Industry Warehouse Solutions Open and certified support for many 3 rd party applications 2013 SAP AG. All rights reserved. 16

17 SAP HANA, BW on HANA, Sybase IQ - Integration scenarios Integration scenarios: Sybase IQ Custom built EDW Petabyte scenarios Smart Data Access Sybase IQ as NLS for BW Sweet Spot for Mature EDW SAP HANA Custom built EDW BW on HANA Packaged EDW framework Tight Integration between BW on HANA and SAP HANA Tight integration between BW on HANA and native HANA scenarios combines the strengths of both worlds Consumption of BW data models in HANA and consumption of HANA models in BW Data staging from HANA to BW and from BW to HANA IQ supports NLS (multi temperature Data) for BW on HANA and remote data access from HANA for smart query processing Lower TCO by reduced data volumes in HANA and shortened backup time frames Cost and Performance optimized EDW Mature EDWs will leverage the capabilities of all three components where appropriate 2013 SAP AG. All rights reserved. 17

18 Conclusions Isolated view SAP HANA Customer requires standalone Data Marts HANA provides maximum agility for custom built data marts With increasing BI maturity* customers are able to grow from HANA based Data Marts to an EDW on HANA Customer requires operational analytics directly on the original transactional data SAP HANA Live for SAP Business Suite (see appendix for more details) BW on HANA Customer requires an EDW BW on HANA is SAP s strategic EDW solution and should be considered as a cornerstone for customers EDW strategy Sybase IQ Customer requires an EDW for very large data volumes Sybase IQ recommended for Petabyte scale Customer requires an NLS solution Sybase IQ provides very low TCO for advanced data lifecycle management capabilities, e.g. NLS * TDWI BI Maturity Model 2013 SAP AG. All rights reserved. 18

19 Conclusion The HANA EDW Combining the strengths of the different worlds SAP HANA BW on HANA The HANA EDW SAP HANA, BW on HANA + IQ NLS BW on HANA and HANA Agile Data Mart scenarios perfectly address the needs of Central EDWs and Data Marts IQ is SAP s native NLS for BW on HANA and is capable of storing terabytes to petabytes of structured & unstructured data Sybase IQ Mature customer architectures will leverage the capabilities of all three components where appropriate 2013 SAP AG. All rights reserved. 19

20 Thank you Contact information: Product Management: Lothar Henkes, Courtney Claussen, Brian Wood Solution Management: Daniel Rutschmann Consulting: Andreas Scholl COE: Lars Jakob CSA: Rudolf Hennecke

21 Further Information Find additional information Real-Time Data Platform landing page: SAP NetWeaver Business Warehouse 7.4: BW on HANA FAQ: Roadmaps: Link to EDW Positioning presentation: SAP AG. All rights reserved. 21

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