1 / 20

BW on HANA

BW on HANA. SAP-internal & confidential. Thomas Zurek VP for R&D – SAP Business Warehouse February 2011. Disclaimer.

xannon
Download Presentation

BW on HANA

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. BW on HANA SAP-internal& confidential Thomas Zurek VP for R&D – SAP Business Warehouse February 2011

  2. 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.

  3. Agenda HANA Scenarios What HANA means for BW ORANGE Scope Highlights Examples for " X Y" Q & A

  4. BOBJ / Excel ERP BW X DB X DB BWA BOBJ / Excel ERP BW X DB X DB BWA HANA Scenarios Overview ERP BW operational data marts agile data marts BOBJ / Excel ERP BOBJ / Excel side-by-side BW real time X DB HANA 1.0 ETL X DB BWA HANA 1.0 OLTP + operational analytics EDW + architected data marts BOBJ / Excel ERP BOBJ / Excel on-top BW HANA 2.0 HANA 1.5

  5. HANA as BWA BOBJ / Excel BW BW on HANA X DB HANA BOBJ / Excel BW HANA as DM HANA BOBJ / Excel BW ETL X DB BWA HANA new This color indicates that a new version (upgrade or SP) is mandatory to support this scenario.  BW today  BOBJ / Excel BW   X DB BWA : • install HANA • rebuild all BWA indexes (= schedule one program in BW) : • standard DB migration

  6. Agenda HANA Scenarios What HANA means for BW ORANGE Scope Highlights Examples for " X Y" Q & A

  7. RDBMS – Data Warehousing – In-MemoryThe "EDW Equations" • Today:EDW = RDBMS + Xe.g. with X = BW • Now:RDBMS  HANAHANA≈ {SQL, MDX, in-memory} • Thus:EDW = HANA+ Y with Y = new BW • This means: • HANAreplaces RDBMS, not BW • HANAcomplements & renovates BW • for more details see SDN blog: http://tinyurl.com/sapbw730

  8. BW on HANA – Overview

  9. Agenda HANA Scenarios What HANA means for BW ORANGEScope Highlights Examples for " X Y" Q & A

  10. Planning Engine Evolving In-Memory Footprint in SAP BWOverview Data Modeling Data Persistency and Runtime BW 7.0 DB + BWA 7.0 BW 7.3 DB + BWA 7.2 BW 7.3 on HANA (and beyond) Enterprise Data Warehouse and Data Mart Modeling with SAP NetWeaver BW in-memory planning engine Analytic Engine first calculation scenarios in BWA additional calculations in-memory Data Manager filter + aggregation MultiProvider handling and flexible joins InfoCubes BWA instead of aggregates BWA-only InfoCubes DataStore Objects BWA reporting for DSOs reporting + activation for DSOs in-memory EDW Processes first EDW processing in-memory

  11. ORANGE Scope Highlights new (flat) infocube BWA-based functionality remains available DB migration in-memory based DSO in-memory based BW-IP (incl. TPM-related requirements) integrate free-style artifacts (e.g. created via HANA studio) BW workspaces HANA-specific properties in BW meta data(e.g. hot – cold data)

  12. Layered Scalable Architecture – Real World Example Provide data End-user access / Presentation Project Governance Reporting Data Mart ODS Harmonization Data Propagation Main Service : Make data available for reporting tools Transform : Application specific/(dis-)aggregate/lookup Content : Application specific History : Application specific Store : IC,DSO, Info Set, Virtual Provider, Multi Provider. Data Acquisition Data Warehouse Corp. Memory ETR Governance Main Service : Spot for apps/Delta to app/App recovery Transform : Enriched || General Business logic Content : Data source || Business domain specific History : Determined by rebuild requirements of apps Store : DSO(can be logical partitioned) Business transform Main Service : Integrated, harmonized Transform : Harmonize quality assure (in flow|| lookup) Content : Defined fields History : Short or not at all || Long term Store : Info source || IO/DSO/Z-table Main Service : Decouple, Fast load and distribute Transform : 1:1 Content : 1 data source, All fields History : 4 weeks Store : PSA, DSO-WO. Source 1 Source 2 Source 3 Source 4 Source 5

  13. Agenda HANA Scenarios What HANA means for BW ORANGE Scope Highlights Examples for " X Y" Q & A

  14. BW on (DB + BWA) 2 "DB" servers 2 "DB" licenses move data to BWA to achieve fast reporting some redundancy DB + BWA physical data movements pro: data layers decoupled via servers, e.g. no conflict data load ↔ query ACID properties only in DB not in BWA  planning / write-back BW on HANA 1 DB server 1 DB license no special effort to guarantee fast reporting on any DB object(s) no redundancy opportunity to use logical data mappings instead of physical data movements full ACID support in ICE DB + BWA  ICE

  15. Traditional Approach Determine the delta  +50 Disaggregate (in appl. server) per week (52) per branch (500)  26000 combinations / values Send 26000 values to DB to save HANA-Based Approach Determine the delta  +50 Send 1 value to DB + instruction to disaggregate and how Disaggregate (in DB engine) per week (52) per branch (500)  create + save 26000 values user changes a plan value In-Memory PlanningSimple Disaggregation Example

  16. Traditional Approach Determine the delta  +50 Disaggregate (in appl. server) per week (52) per branch (500)  26000 combinations / values Send 26000 values to DB to save HANA-Based Approach Determine the delta  +50 Send 1 value to DB + instruction to disaggregate and how Disaggregate (in DB engine) per week (52) per branch (500)  create + save 26000 values user changes a plan value In-Memory PlanningSimple Disaggregation Example

  17. Today's Data Store Object (DSO) querying delta upload • Data Store Objects (DSOs) are fundamental building blocks for a DW architecture. • There are 4 operations on a DSO: • upload (of new data) • activate (future image  current image) • querying (the current image) • delta upload (for delta feeds) • In today's RDBMS-based implementation, the activate and querying operations are extremely performance-critical. • These can be highly optimized in ICE. Current Image Delta Image activate Future Image DSO On an RDBMS, each "image" corresponds to a table. upload

  18. In-Memory Based DSO index-read (snapshot) delta-read (snapshot1, snapshot2) • The DSO in HANA is a closed objects with the options to • index-read (a snapshot of the data) • delta-read (delta btw 2 snapshots) • upload • activate • The 4 DSO operations are mapped: • upload • activate • querying =index-read(current snapshot) • delta upload = delta-read(snapshot1, snapshot2) • Fundamental advantages: • excellent querying performance • highly optimized activation Main Index Delta Index move mapping log move activate History Index Insert- Only Index New DSO upload

  19. Agenda HANA Scenarios What HANA means for BW ORANGE Scope Highlights Examples for " X Y" Q & A

  20. Thank You!

More Related