SAP hana architecture ppt

sap hana cloud platform ppt and sap hana introduction ppt and sap hana overview ppt
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Prof.SteveBarros,United Kingdom,Teacher
Published Date:28-07-2017
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SAP NetWeaver BW Powered by SAP HANA and Future Roadmap Lothar Henkes April, 201㻟 Disclaimer This presentation outlines our general product direction and should not be relied on in making a purchase decision. This presentation is not subject to your license agreement or any other agreement with SAP. SAP has no obligation to pursue any course of business outlined in this presentation or to develop or release any functionality mentioned in this presentation. This presentation and SAP's strategy and possible future developments are subject to change and may be changed by SAP at any time for any reason without notice. 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 assumes no responsibility for errors or omissions in this document, except if such damages were caused by SAP intentionally or grossly negligent. © 2012 SAP AG. All rights reserved. 2 Agenda Introduction SAP NetWeaver BW‟s use of In Memory technology  SAP NetWeaver BW powered by SAP HANA  Customer results What‟s new with NetWeaver BW 7.3, SP8 Outlook- SAP NetWeaver BW 7.3 SP 9 and further Roadmap Agenda Introduction SAP NetWeaver BW‟s use of In Memory technology  SAP NetWeaver BW powered by SAP HANA  Customer results What‟s new with NetWeaver BW 7.3, SP8 Outlook- SAP NetWeaver BW 7.3 SP 9 and further Roadmap Unlock The Power of Your Data Across The Enterprise Enterprise Data Warehousing – the single point of truth  Enterprise Data Warehousing - why – Consolidate the data across the enterprise to get a consistent and agreed view on your data  "Having data is a waste of time when you can't agree on an interpretation." – Combine SAP and other sources together – Standardized data models on corporate information – Supporting decision making on all organizational levels  EDWs require a Database plus an EDW application  EDW with SAP NetWeaver BW - a flexible and scalable EDW application – Highly integrated tools for modeling, monitoring and managing the EDW – Open for SAP and non-SAP systems – Agile data modeling using BW workspaces – Runs on top of HANA and other RDBMS – Easy consumption of HANA Data Mart scenarios via virtualized data access  EDW with custom built application – High development and maintenance efforts – Variety of tools with lacking integration © 2012 SAP AG. All rights reserved. 5 Q1 13 Q4 12 Q3 12 Q2 12 Q1 12 Q4 11 Q3 11 Q2 11 Q1 11 Q4 10 Q3 10 Q2 10 Q1 10 Q4 09 Q3 09 Q2 09 Q1 09 SAP NetWeaver BW Adoption Productive SAP NetWeaver BW Systems – Constant Growth Stable Product, Large installed Base, 18.000 Constant Growth  Adoption of SAP NetWeaver BW constantly 17.000 growing  Unaffected by economic downturn in 2009 16.000  14.000 customers referring to 17.000 productive systems 15.000 14.000 Usage  Vast majority: Central DWH, harmonizing many 13.000 source systems  Minority: One-to-One to an ERP 12.000  Embedded into mission critical business processes © 2012 SAP AG. All rights reserved. 6 Agenda Introduction SAP NetWeaver BW‟s use of In Memory technology  SAP NetWeaver BW powered by SAP HANA  Customer results What‟s new with NetWeaver BW 7.3, SP8 Outlook- SAP NetWeaver BW 7.3 SP 9 and further Roadmap Customer Value of BW Powered by SAP HANA Speed and Accelerated performance  Excellent query performance for improved decision making  Performance boost for Data Load processes for decreased data latency  Accelerated In-Memory planning capabilities for faster planning scenarios New Business Insights  Self-Service BI – Data modeling with BW Workspaces  Flexible combine EDW with HANA-native data for better insights and decision making Streamline Landscape and simplify data management  Non-disruptive DB Migration with SAP standard tools and services  Data persistency layers are cut out and admin efforts reduced: No aggregates, indexes, rollups, statistics  Simplified data modeling and remodeling © 2012 SAP AG. All rights reserved. 8 SAP NetWeaver BW7.3 Powered by SAP HANA How Does BW 7.3 Running on HANA Differ from BW Running on xDB? BW Upgrade BW BW 7.3 7.0x Migration SAP NetWeaver BW 7.3 on HANA SAP NetWeaver BW 7.x on xDB  Standard DataStore Objects  SAP HANA-optimized DataStore Objects  Data Base server and SAP NetWeaver BWA  SAP HANA In-Memory platform  Standard InfoCubes  SAP HANA-optimized InfoCubes  BW Integrated Planning  In-Memory planning engine  HANA Data Marts running side-by-side BW Consumption of HANA artifacts created via HANA studio  BW staging from HANA Migration without reimplementation - no disruption of existing scenarios This presentation outlines our general product direction and should not be relied on in making a purchase decision. This presentation is not subject to your license agreement or any other agreement with SAP. SAP has no obligation to pursue any course of business outlined in this presentation or to develop or release any functionality mentioned in this presentation. This presentation and SAP's strategy and possible future developments are subject to change and may be changed by SAP at any time for any reason without notice. 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 assumes no responsibility for errors or omissions in this document, except if such damages were caused by SAP intentionally or grossly negligent. © 2012 SAP AG. All rights reserved. 9 DataStore Objects in SAP NetWeaver BW 7.3 Overview and Challenge DataStore Objects are fundamental building blocks Delta upload Query for a Data Warehouse architecture Change Log Active Data Table  They are used to create consistent delta information from various sources  Reporting can be done on a detailed level  In today‟s RDBMS-based implementation, the activation and querying operations are extremely Activation performance-critical Activation Queue Parallel Upload © 2012 SAP AG. All rights reserved. 10 DataStore Objects in SAP NetWeaver BW 7.3 Creation of Consistent Delta Information Current architecture Active Data Table Change Log  Activation algorithm calculates the changes of each record and creates heavy load on the DBMS Calculate Lookup Update Delta  Delta calculation performed on the application server, too complex to push it down to the DBMS as SQL/Stored Procedure Data Packages  Roundtrips to application server needed for delta calculation Sorted Full Table Scan Activation Queue © 2012 SAP AG. All rights reserved. 11 SAP HANA-Optimized DataStore Objects Accelerated Data Loads SAP HANA-optimized DSOs  Delta calculation completely integrated in HANA User interface User interface  Using in-memory optimized data structures for Layer Layer Presentation Presentation faster access SAP NW BW SAP NW BW  No roundtrips to application server needed  Process of SID generation highly optimized for DSO Objects Application Application DSO Objects HANA Optimized DSOs  low impact on staging Layer Layer performance Activation SAP NW BW SAP NW BW  Speeding up data staging to DSOs by factor 5-10  Avoids storage of redundant data Database Activation Database Layer Layer  After the upgrade to BW on HANA all DSOs Data remain unchanged SAP HANA Data xDB  Tool support for converting standard DSOs into SAP HANA-optimized DSOs No changes of Data Flows required This presentation outlines our general product direction and should not be relied on in making a purchase decision. This presentation is not subject to your license agreement or any other agreement with SAP. SAP has no obligation to pursue any course of business outlined in this presentation or to develop or release any functionality mentioned in this presentation. This presentation and SAP's strategy and possible future developments are subject to change and may be changed by SAP at any time for any reason without notice. 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 assumes no responsibility for errors or omissions in this document, except if such damages were caused by SAP intentionally or grossly negligent. © 2012 SAP AG. All rights reserved. 12 SAP HANA-Optimized InfoCubes Faster Data Loads and Easier Modeling MD MD Traditional InfoCubes tailored to a relational DB consist D E of 2 Fact Tables and the according Dimension tables F Facts SAP HANA-optimized InfoCubes represent “flat” structures without Dimension tables and E tables: D  Up to 5 times faster data loads MD MD  Creation of DIM Ids no longer required Conversion/New  Simplified Data modeling  Faster remodeling of structural changes MD MD  After the upgrade to BW7.3, SP5 all InfoCubes remain unchanged  Tool support for converting standard InfoCubes F  Preliminary lab result: 250 Million records in 4 minutes Facts No changes of processes, MultiProvider, Queries required MD MD Tables for compressed data This presentation outlines our general product direction and should not be relied on in making a purchase decision. This presentation is not subject to your license agreement or any other agreement with SAP. SAP has no obligation to pursue any course of business outlined in this presentation or to develop or release any functionality mentioned in this presentation. This presentation and SAP's strategy and possible future developments are subject to change and may be changed by SAP at any time for any reason without notice. 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 assumes no responsibility for errors or omissions in this document, except if such damages were caused by SAP intentionally or grossly negligent. © 2012 SAP AG. All rights reserved. 13 Query Performance Query Performance at Least as Good as with BWA Query acceleration on BW InfoCubes SAP NW BW  Leverage column store and In-Memory Calculation Query on Engine for query acceleration Query on InfoCube, DSO(with SIDs),  No replication – fast query access directly on primary MultiProvider, Masterdata DSO(w/o SIDs), BW InfoSet AnalyticIndex, CompositeProvider data persistence  Indexes on InfoCubes and InfoObjects no longer required  No Rollups, Change runs SAP HANA SQL Engine Query acceleration on BW DataStore Objects Calc Engine  Leverage column store and In-Memory Calculation Aggregation Engine on In-Memory data Engine for query acceleration  SID generation during DSO activation to be enabled  Result: Same kind of excellent query performance on DSOs  Process of SID generation highly optimized for HANA Optimized DSOs  low impact on staging performance No changes of processes, MultiProvider, Queries required This presentation outlines our general product direction and should not be relied on in making a purchase decision. This presentation is not subject to your license agreement or any other agreement with SAP. SAP has no obligation to pursue any course of business outlined in this presentation or to develop or release any functionality mentioned in this presentation. This presentation and SAP's strategy and possible future developments are subject to change and may be changed by SAP at any time for any reason without notice. 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 assumes no responsibility for errors or omissions in this document, except if such damages were caused by SAP intentionally or grossly negligent. © 2012 SAP AG. All rights reserved. 14 Query Performance Are InfoCubes Still Required ? Info Cubes required for Query Aggregates  Non-disruptive approach or BWA when migrating to BW on HANA index Rollup  Non-cumulative Key Figures  Complex business logic(report specific)  BW Integrated Planning InfoCube InfoCube  External write-interface(RSDRI) DTP DTP Conversion Conversion Conclusion  There are scenarios where the InfoCube DataStore Object layer becomes obsolete DataStore Object DataStore Object (w SID generation)  Less materialized data and simplification BW 7.x on BW on SAP BW on SAP RDBMS HANA HANA  Decision to be made scenario by scenario: Business and Performance needs InfoCube can be removed when used for query performance only © 2012 SAP AG. All rights reserved. 15 SAP NetWeaver BW – SAP HANA Interoperability Consumption of SAP HANA data models in BW TransientProvider based on HANA Model Query Query Query SAP BW  For ad hoc scenarios on HANA  Generated not modeled, no InfoObjects required Composite Provider  Full BEx Query support  Can be included in a CompositeProvider to combine with TransientProvider InfoCube Virtual Provider other BW InfoProviders VirtualProvider based on HANA Model  For a flexible integration of HANA data with BW managed metadata (e.g. lifecycle) HANA Analytical View  Security handled by BW SAP BW Schema SAP HANA Schema(s)  Full BEx Query support SAP HANA  Can be included to Composite- and MultiProvider to combine with other BW InfoProviders © 2012 SAP AG. All rights reserved. 16 BW In-Memory Planning Accelerated Planning Functions Traditional Planning runs planning User interface User interface functions in the App. Server Layer Layer Presentation Presentation SAP NW BW SAP NW In-memory Planning runs all planning BW functions in the SAP HANA platform Orchestration Orchestration Application Application Layer Layer  Performance boost for planning Calculation SAP NW BW SAP NW BW capabilities like:  Aggregation, Disaggregation Database Calculation Database Layer  Conversions, Revaluation Layer Data  Copy, Delete, Set value, Repost, FOX SAP HANA Data xDB  Performance boost for plan/actual analysis No changes of planning models, planning processes, MultiProvider, Queries required This presentation outlines our general product direction and should not be relied on in making a purchase decision. This presentation is not subject to your license agreement or any other agreement with SAP. SAP has no obligation to pursue any course of business outlined in this presentation or to develop or release any functionality mentioned in this presentation. This presentation and SAP's strategy and possible future developments are subject to change and may be changed by SAP at any time for any reason without notice. 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 assumes no responsibility for errors or omissions in this document, except if such damages were caused by SAP intentionally or grossly negligent. © 2012 SAP AG. All rights reserved. 17 SAP NetWeaver BW – Post-Copy Automation (BW PCA) Easier and faster migration to SAP NetWeaver BW on SAP HANA Automated migration of SAP NetWeaver BW on RDBMS to SAP NetWeaver BW on SAP HANA using BW PCA  Optimized downtime for SAP NetWeaver BW source system  Automated delta-queue cloning/synchronization – Enables easy operation of original + new system in parallel  Automated clean up of target system  Automated post-copy configuration © 2012 SAP AG. All rights reserved. 19 Agenda Introduction SAP NetWeaver BW‟s use of In Memory technology  SAP NetWeaver BW powered by SAP HANA  Customer results What‟s new with NetWeaver BW 7.3, SP8 Outlook- SAP NetWeaver BW 7.3 SP 9 and further Roadmap SAP NetWeaver BW on SAP HANA Asian Paints Project scope and Asian Paints, the biggest paint manufacturing company in India with very strong brand equity is business scenario seen as the early adopter of cutting edge IT solutions, and is widely regarded in the SAP customer community as very prolific user of SAP BI. In late 2011, Asian Paints decided to implement HANA for their growing analytical needs for the large volume ERP and BW implementations, and with the help of SAP Consulting implemented SAP HANA running under SAP BW in only 3 weeks. Performance and  Data volume compression savings of 6:1 moving from BW/Oracle to BW/HANA benefits  Significant improvement in the query performance: average query performance improvement was15 x with maximum improvement 266x times.  Certain queries, for analyzing orders and billing that could not run in the past on BW-Oracle, are returning the results with an impressive query response time of 15-20 secs with BW-HANA.  Data load time reduced by an average of 95% with some of the delta data load completing in 2 minutes in BW-HANA, paving the way for near real-time data extraction and analysis, compared to more than 35-40 minutes it used to take in BW-Oracle. © 2012 SAP AG. All rights reserved. 22

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