In-Memory Technologies and Applications S4HANA

Transcription

1 In-Memory Technologies and Applications S4HANA Ringvorlesung Frankfurt, May 21, 2015 Prof. Dr. Alexander Zeier Global Managing Director In-Memory Solutions (incl. SAP HANA) CTO PSG (Analytics, Database & Technology, Big Data, Mobility)

2 Confidentiality Notice The information set forth in this document shall be kept confidential. Accenture GmbH ( Accenture ) remains the owner and unlimited beneficiary of any and all material. This document contains business and trade secrets of Accenture and/or third parties who have authorised Accenture to use and disclose such information. This document and the information contained herein or any material associated therewith may only be disclosed to third parties with the prior written consent of Accenture. In addition, complete or partial copies or other reproductions of this document may only be made upon the prior written consent of Accenture. Use of this document shall be expressly limited to the purpose of evaluation by the customer. Any additional use of this document shall require Accenture s prior written consent and, in the case of a reproduction, the incorporation of a respective copyright note regarding Accenture or affected third persons. Any trademarks and service marks contained in this proposal including Accenture name and logos, are the property of respective owners and may not be used without their prior written permission. 2

3 In-Memory Technology of S4HANA Allows Combining Transactional and Analytical Applications in Real Time (April 2006: HANA) Data-centric architecture: In-Memory database serves as Single Source of Truth for Enterprise data Analyze Architecture based on distinct pillars Multi-Core computing In-Memory Column and Row Store Enables informed management decisions based on up-to-the-moment data through realtime combination of Transactional applications Analytical applications Execute Predict Enterprise Performance In-Memory Circle (EPIC)* * Plattner, Hasso; Zeier, Alexander: In-Memory Data Management. Technology and Applications. 2nd edn. Springer-Verlag Berlin (2012) 3

4 S4HANA Is the Successor of R/3-ERP after 23 Years Evolution next Generation ERP In-Memory R/2 Mainframe R/3 Client/Server S- Innovations Mobility One Platform TCO Reduction

5 4 th Generation of SAP Systems Called S4HANA - Announced Feb 3 rd, 2015 Degree of simplification 10 s-innovations Simple Finance Simple Logistics SAP Business Suite 4 on HANA S- Innovation 800 >2000 customers SAP Suite on HANA Real real-time - No more batch processes Open Platform - Big Data ready Fiori - Improved user front-end based on HTML5 for any device Smarter and HANA-enabled business processes Actionable Information Predict, recommend, simulate Consolidation on One Platform - TCO Reduction S-Innovations as add-ons Non-disruptive On-premise, in the cloud Default offering for new customers HANA is fastest growing SAP product ever today Source of Picture: SAP SAP Suite on anydb Mainstream maintenance until

6 S4HANA Roadmap SAP has announced a roadmap for S4HANA: Simple Finance (sfin) 1.0 ramp-up Feb 2014, 2.0 ramp-up Mar 2015 Simple Logistics (slog) will be launched in Q in private cloud With ECC6 EHP8 (Q4 2015) Simple Logistics will be available on-premise Innovations will be shipped quarter by quarter, with the objective of Cloud First Releases for on-premise are planned once a year FKOMs Jan 7-22 CeBIT Mar 2-5 SAPPHIRE May 5-7 TechEd Tbd Q Q Q Q S-Innovations Public Cloud Simple Professional Services S-Innovations Private Managed Cloud Simple Logistics S-Innovations on-premise (ECC6 EHP8) Release sfin 2.0 & Announcement ECC6 EHP8 Launch S-Innovations on-premise ECC6 EHP8 incl. sfin & slog 6

7 SAP Enterprise Architect Summit November 21 st -22 nd, 2013, Hamburg, Germany This Agenda shows: In-Memory/HANA, our Vision from 2006, is now reality and in productive use since 2013! 7

8 Enterprise Workloads are Read-Mostly and Often Process Ranges of Data Workload 100 % 90 % 80 % 70 % OLTP 83% OLAP 94% Delete Update Insert Range select Table scan Look up write read 60 % 50 % 40 % 30 % 20 % 10 % 0 % Plattner, Hasso; Zeier, Alexander: In-Memory Data Management. Technology and Applications. 2nd edn. Springer-Verlag Berlin (2012) 8

9 Combination of Hardware and Software Innovations Advances in Hardware Multi-Core Architecture (8 x 10core X86 Intel CPU per server, 8 x 18core in 2015 Haswell CPU, available by 12 HANA vendors 2014) Parallel scaling across blades One blade ~$ = 1 Enterprise Class Server A 64bit address space 4/6TB in current servers Up to 24TB in 2014 on each server with Ivy-Bridge (Intel latest CPUs) 100GB/s data throughput Dramatic decline in price/ performance Advances in Software SQL Row and Column Store Compression Partitioning No Aggregate Tables On-the-fly extensibility SQL interface on columns & rows Plattner, Hasso; Zeier, Alexander: In-Memory Data Management. Technology and Applications. 2nd edn. Springer-Verlag Berlin (2012) 9

10 HANA & Column Store are Best Suited for Enterprise Queries + Combined column and row store Accessing Enterprise Data in OLTP Systems is also mainly via OLAP-Style Queries SELECT * FROM Sales Orders WHERE Document Number = (OLTP-style query) SELECT SUM (Order Value) FROM Sales Orders WHERE Document Date > (OLAP-style query) Row Store Row 1 Row 2 Row 3 Row 4 Row 1 Row 2 Column Store Doc Num Date Doc So T o l d - V alue St a t u s Sa O rg l e s Doc Num Date Doc So T o l d - V alue St a t u s Sa O rg l e s Enterprise applications perform set processing (items for an order, orders for a customer) Bring application logic closer to the storage layer using Business Function Libraries (BFL) in HANA Row 3 Row 4 Plattner, Hasso, Zeier, Alexander: In-Memory Data Management. Technology and Applications. 2nd edn. Springer-Verlag Berlin (2012), p

11 Read Event Repositories Verification Services to read t notifications er second up to Overview: Elements of In-Memory / SAP HANA requests per second Discovery Service + Combined column and row store Minimal projections Any attribute as index Insert only for time travel Bulk load Multi-core/ parallelization Price/performance of memory A P Active/passive data store SAP HANA P A Partitioning Lightweight Compression Dynamic multithreading within nodes t Analytics on historical data SQL SQL interface on columns & rows No aggregate tables Group Key X X Reduction of layers On-the-fly extensibility Object to relational mapping Single and multi-tenancy T Text Retrieval and EXploration Plattner, Hasso; Zeier, Alexander: In-Memory Data Management. Technology and Applications. 2nd edn. Springer-Verlag Berlin (2012) 11

12 Example: Financials Dunning Run Accounting Document Header Base Tables Accounting Document Items Reporting Cubes Indices Change History Changes General Ledger Items Sales Ledger Items General Ledger Sales Ledger Accounts Payable Items Tax Ledger Items Accounts Payable Tax Ledger Accounts Receivable Items Fixed Asset Items Accounts Receivable Fixed Asset Material Ledger Items Cash Ledger Items Material Ledger Cash Ledger Dunning Payments Materialized Aggregates Materialized View 12

13 Simplified Financials as Target Accounting Document Header Base Tables Accounting Document Items Indices Only base tables, algorithms, and some indices 13

14 Result: Dunning Run in 1.5 Seconds Dunning run determines all open and due invoices Customer defined queries on 250M records Current system: 20 min New logic: 1.5 sec In-Memory column store Parallelized stored procedures Simplified financials 14

15 Simple Finance (sfin) as First S-Innovation on S4HANA TCO Savings in Finance Cockpits for process execution and monitoring Logical Document FI CO CO-PA Line item level integration Direct Integration to FI & CO data on HANA from Excel Reduction of Time-to-Close Further harmonization of financials and controlling Simplified and reduced reconciliation effort Reduction of Time-to-Report Agile reporting Highest granularity with zero latency Full extensibility and scalability Integrated Business Planning No separate planning systems necessary like BW-IP End-to-end simulation e.g. from sales to P&L Central Finance Reporting backbone for concern-wide harmonization Universal Journal (sfin 2.0) Single Source of Truth by architecture reconciled by design Ramp-up Mar 2015 One line item table with full detail for all components 15

16 Simple Finance Simplification Pioneer of S4HANA SAP ERP FI/CO Simple Finance 1.0 Simple Finance 2.0 Classic GL BKPF BSEG GLT0 NewGL BKPF FAGLFLEXA FAGLFLEXT CO-OM COBK COEP Classic GL BKPF BSEG GLT0 NewGL BKPF FAGLFLEXA FAGLFLEXT CO-OM COBK COEP SAP Accounting Powered by SAP HANA BKPF CO-PA FI-AA COSS CO-PA FI-AA COSS ACDOCA CE1* ANEK COSP CE1* ANEK COSP CE3* ANEP CE3* ANEP Every financial application has its proprietary: document ledger header and line item table(s) totals table(s) allocation/posting engine Totals tables in FI and CO-OM removed Requests for aggregated data are directed to line item tables Universal Journal: One line item table for all applications single Source of Truth for financial and management accounting; no totals tables Single master data object for GL accounts no Cost Elements anymore Single allocation engine 16

17 First Results of Customers Using SAP HANA 1,000x Faster: Many (Dunning, Aging, ) 10,000x Faster: Essar Group, SAP IT, Cornell, Charmer Sunbelt 100,000x Faster: NongFu Spring, YodoBashi, MKI 1mio x Faster Ferrero (COPA Reporting) Or 24+ Hours to 3.8s: Food and Beverage / Distribution - Logistics 15+ Hours To 4.8s: Project Management / Services, Profitability, Performance 30 Days to 28s: Manufacturing Order to Cash 3 Days to 2s: Retail / Insurance Incentives SAP Business Suite on HANA since May 15, 2013 general available, and SAP S4HANA the official successor available since Feb. 3, 2015 NOW! 17

18 All Findings are Summarized in the Book In-Memory Data Management This book is the culmination of six years worth of in-memory research and development PART I An Inflection Point for Enterprise Applications Overview of our vision of how in-memory technology will change enterprise applications PART II A Single Source of Truth through In-Memory Technical foundations of in-memory data management In-depth description of how we intend to realize our vision PART III How In-Memory Changes the Game Resulting implications on the development and capabilities of enterprise applications è Book launched at Cebit 2011, SAP Product HANA is general available since June è New extented Book Edition In-Memory Data Management -Technology and Applications focusing on Application Development available since Summer è Chinese Edition The genuine memory data management, published by Tsinghua University Press

19 In-Memory/HANA Book Launch on Cebit 2011 with Vice-President of the European Commission Neelie Kroes SAP/HPI won the German Innovation Award 2012 for In-Memory/SAP HANA This book presents an excellent overview of the issues and challenges related to in-memory data, and is highly recommended for anyone wishing to learn about this important area. Prof. Hector Garcia-Molina (Stanford University and Member of Oracle Board of Directors) The book In-Memory Data Management Technology and Applications by Hasso Plattner and Alexander Zeier describes a revolutionary database technology and many implementation examples for business intelligence and operations Prof. David Simchi-Levi (Massachusetts Institute of Technology) 19

20 Accenture & HANA Fast Facts: 200 HANA projects completed and 450 ongoing / discussion 2,500+ HANA trained resources HANA as platform of choice for 10 new Business Services First HANA Business Application for CMO: Marketing Performance Solution (MPS) Offerings include: Analytics on HANA ERP on HANA CRM on HANA HANA Agile Lifecycle Optimization Business Services on HANA (e.g. MPS) Accenture is SAP s #1 partner in HANA overall (Marty Mrugal SAP) Accenture and SAP to Launch New Business Solutions Group to Accelerate Time to Value for Client- and Industry-Specific Cloud-Based Solutions March 10, 2014 Accenture and SAP to Launch New Business Solutions Group to Accelerate Time to Value for Client- and Industry-Specific Cloud-Based Solutions NEW YORK and WALLDORF, Germany; Mar. 10, 2014 Accenture (NYSE: ACN) and SAP AG (NYSE: SAP) today announced the creation of a new business group focused on rapidly accelerating the time it takes to jointly develop and deliver new industry-specific solutions based on cloud and other digital technologies. The Accenture and SAP Business Solutions Group brings together the companies respective co-innovation, joint solution development and go-to-market teams in an effort to focus on significantly increasing time to value for clients globally. The Accenture and SAP Business Solutions Group helps facilitate a combination of Accenture s intellectual property and industry expertise with innovative solutions that are powered by the SAP HANA Cloud Platform to more rapidly enable customers to harness the benefits of digital technologies including cloud, analytics and enterprise mobility. ( ) 20

21 Accenture Extensive Skills and Assets Founded on Partnership with SAP 50+ HANA client credentials 200+ HANA projects with our first HANA implementation over 3 years ago 450+ HANA projects in discussion, 25+ Suite on HANA projects in discussion 2,500+ professionals trained in HANA 200+ HANA use cases identified for business functions and industries Accenture HANA implementation tools and accelerators e.g. Business Value Insights for HANA (Business Case Calculation, ROI) Global HANA Center of Excellence in Kronberg Proof-of-concept and pilot projects Define and execute road maps 17 Accenture Innovation Centers for SAP showcase HANA capabilities in industry day-in-the-life scenarios, technology demos HANA Solution Factory in our India Delivery Center Accenture Advanced Enterprise Solution (AAES) on HANA: fully configured industry-specific SAP solution with best practices, templates, assets, test scripts and tools 5 industry solutions on HANA (e.g. AAES Metal) 20 tested end-to-end scenarios Accenture and SAP Business Solutions Group 21

22 Accenture and SAP Business Solutions Group (ASBSG) Drives Differentiated Value to Customers New partnership to facilitate execution and speed-to-market of new solutions for customers Dedicated joint team to develop industry specific solutions Customer requirements feed into SAP s product development roadmap Access to the highest levels of Accenture and SAP leadership Co-investment on customer priorities Focus on HANA, Big Data, analytics, cloud, mobile, etc End-to-end and pre-integrated solutions Rapid time-to-market Accenture ASBSG SAP Charter clients aid in shaping the solutions they need (e.g. Marketing Performance Solution and Upstream Operations Management, Omni-Channel Rapid Commerce) Customer 22

23 Accenture Innovation Center for SAP HANA & Ecosystem (AICS) in Frankfurt/Kronberg, Germany SAP Technology Innovation Hubs 17 Innovation Centers globally Kronberg HANA Lab led by Prof. Dr. Alexander Zeier 14 HANA powered Industry Day in the Life scenarios First SI with HANA production customer reference Accenture is a Leader in the Gartner Magic Quadrant for: SAP Application Management Service Providers, Worldwide, 2013 SAP Implementation Service Providers, Worldwide,

24 Accenture Innovation Center for SAP HANA & Ecosystem Works with Clients to Deliver Value in Several Ways Value Discovery Workshops Client specific workshops with a focus on SAP HANA & Ecosystem to identify added value for business and IT organizations HANA Proof-of-Concepts and Pilots Test drive HANA to validate the value proposition with a limited investment, leveraging Accenture s infrastructure Innovation Workshops Design Thinking Strategy Roadmaps Industry Use Cases Day in the Life Scenarios Technology Demos Proof-of-Concepts Proof-of-Value Studies Pilots Providing Infrastructure SME Support HANA Performance Reviews Delivery Excellence Jump start your implementation leveraging our pre-defined use cases, assets and infrastructure Global HANA Center of Excellence (CoE) Make use of our solutioning offerings and leverage our SMEs in the Accenture Innovation Center for SAP HANA & Ecosystem Use Cases Reuse of Assets SME Support Standardized Methodology HANA Solution Factory in Indian Delivery Center Solutions as a Service for HANA (SaaSH) The global HANA CoE SME Network HANA Performance Reviews Capability Building Solution Architect Reviews Comparative Technology Evaluation 24

25 Specific Roles Needed to Deliver SAP HANA Projects Proposed HANA roles 1) Analyze Design Build - Deep understanding HANA technology combined with functional / business knowledge - Skills in HANA Applications HANA Consultant - HANA specific data modeling skills (incl. SQL, SQL Script) - Design database architecture - Business Case - HANA IT Strategy/ Roadmap - Enable new business process HANA Value Architect (HANA VA) HANA Data Engineer/ Architect Data Scientist - TGP Solution Architect + Deep HANA skills - Solution Planning HANA Solution Architect (HANA SA) HANA Developer HANA High Performance Developer (HANA HPD) - Technical HANA architecture / landscape - IT Landscape transformation - Integration HANA Technical Architect (HANA TA) - Design, Implement and test native applications on SAP HANA Run - HANA System installation and setup HANA System/DB Admin - Design and implementation of HANA - Operate, monitor and projects/apps for maximum maintain the HANA performance environment - Deep technical understanding (Business Library Functions in C++) 1) Alignment to key project phases is indicative only 25

26 Accenture s Expertise in Business Transformation End-to-End Offering Strategy and Business Process Consulting For functional analysis, organizational process changes, and design work To drive HANA opportunities at a strategic level Functional Technology Delivery Units & Industry Groups Many HANA applications (e.g. Fraud) or use cases (e.g. CRM, ERP) are functional domain or even industry specific Capabilities to drive HANA opportunities at functional domains and industries One HANA organizational unit across all areas Technology Consulting and Infrastructure Outsourcing Involvement We see an increasing demand for hosting and infrastructure services. Many topics, especially roadmaps, are technical architecture driven Capabilities for solution architecture and delivery 26

27 In-Memory Systems Now The Route to a HANA Strategy SAP HANA Open Real-Time Data Platform for Enterprise Applications User driven experience Design Thinking SAP UI HTML 5 Mobile SAP BI4 Real-time Planning and Execution SAP Business Suite ERP CRM SCM SRM PLM SAP Netweaver SAP HANA New Applications SAP Business Warehouse Business Intelligence New Analytical Applications Real-time Reporting and Analytics In-Memory Real-Time Data Platform SAP HANA OLTP + OLAP + streaming data + unstructured data (text, video, speech) 27

28 NEW Style of Working With Suite on HANA Example: Receivables Management RFDOPR10 Customer Open Item Analysis by Balance of Overdue Items? RFDOFW00 Open Items - Customer Due Date Forecast Closed loop alert driven process FBL5N Customer line item display RFDEPL00 List of Customer Line Items RFDOPR20 Customer Payment History RFDOPO10 List of Customer Open Items 28

29 Fiori App Types and Delivery Packages (70% based on HANA) Currently 508 Fiori Apps with focus on mobile access are available in total for SAP HANA Transactional Analytical Factsheets Smart Business Task-based access Access tasks to create, change, approve processes with guided navigation Insights Get a visual overview of a complex topic for monitoring or tracking purposes Search and explore View essential information about an object with contextual navigation between related objects Insight to action cockpit Analyze and evaluate strategic or operational KPIs in real time and trigger the right action anydb SAP HANA SAP HANA SAP HANA SAP HANA 29

30 HANA as Real-Time Platform for BigData & Analytics Predictive Analysis Library Contains universal predictive algorithms (currently 30 algorithms) Support clustering, classification, association, time series functions and ABC analysis Business Function Library Contains pre-built parameter-driven functions with complex and performance-critical algorithms that fit a wide array of business needs Currently ca. 60 functions (e.g. Year-to-Date Difference,Net Present Value, Discounted Cash Flow) SAS HPA integration on the Platform The SAS embedded process scores models in place on data and enables selected algorithms to run on data in HANA SAS High Performance Analytics (HPA) provides the scale-out needed to run intense math workloads in-memory R integration R as open source statistical programming language provides over 3,500 add-on packages (more than SAS+SPSS+Statistica) along with the ability to write your own functions R code can be embedded and processed as part of the overall query execution plan in the SAP HANA Database Communication / data exchange between HANA and R server via high performance parallelized connection Client Tools SAP Predictive Analysis, SAP InfiniteInsight, SAP Lumira, SAP HANA Studio application function modeler (AFM) SAP ERP Location data Full-text search Text Analysis HADOOP Machine data SAP Industry and LoB Applications Demand signal management, fraud management, audience discovery and targeting, over 20 other apps Business Function Library (BFL) SAP IQ, SAP ESP, SAP ASE Timeseries data Rules Engine RDS Predictive analytics rapiddeployment solutions Transaction data SAP HANA Platform Predictive Analysis Library (PAL) Spatial Processing Third-Party data source Unstructured data Partner Tools and Solutions SAS, Rogue Wave (IMSL) Over 30 partners SAP Data Services SAS HPA Real-time data 30 R

31 The SAP Codebase is Optimized to Take Advantage of HANA Business Function Libraries for Acceleration For data-intensive applications, ~90% of runtime is spent on transferring data between the database and application server Illustrative Applications ERP CRM BW Custom Applications ERP CRM BW Custom Applications Application Server HANA-based Apps DB / Platform anydb Business Function Libraries (BFLs) HANA è Large data volume transferred è Processing only on Application Server è Optimized processing directly on HANA Platform with BFLs è Minimal data transfer (results only) 31

32 Accenture SAP HANA Credentials Overview Client Industry Solution Benefits achieved Products Suite on HANA Proof of Concept DMO Migration of Productive near client system to SAP HANA within the AICS to evaluate technical feasibility and to measure the performance improvements by custom code optimization (10 weeks) Performance improvement for optimized code by 96% Performance improvements for used functionalities out of the box up to 99,9 % (based on EHP 7 Upgrade) Implementation of Real time reporting using SAP HANA live (Incl. LUMIRA standard reports) Definition of Technical Architecture Concept for To-Be solution Evaluation of migration and Upgrade approach based on client system Aerospace Foodstuff & Agricultural services Fragrances Telecommunications Telecommunications HANA Custom App, HBA Data model for production orders and operational KPI dashboard created. Reconciliation reports for Finance SAP BW on HANA 5+ TB data model consisting of 200 Data Store Objects and 150 Cube objects, 250 reports (7 months) SAP BW on HANA With 35 reports for Sales, Controlling, PA, CCA, Stocks & AR (8 weeks) Financial month end HANA Implementation of full financial data flows to support the month end close process (4 months) SAP BW on HANA Implementation of a model supporting highly complex calculated metrics (7 months) Faster and more accurate production order reports More then 100% improvement in cycle time for financial data reconciliation Month end closing acceleration ETL run time cut by 50% Up to 22x improvement in report execution Up to 100x improvement in report execution 10x compression rate in overall storage Up to 400x improvement in report execution 60x improvement in query navigation execution 10x average compression rate Financial month end close 1 day earlier than previously achievable 1000x improvement in data processing from standard BW ETL to HANA studio model. 30x improvement in reporting performance Highly complex in-depth analysis on 1.5 B records on finger tips which was not possible earlier. 10x improvement in data transfer times from the existing ETL 5:1 improvement in data compression 32

33 Thank You for Your Attention Please feel free to contact me: Prof. Dr. Alexander Zeier In-Memory/HANA Blog at MIT: Prof. Dr. Alexander Zeier Global Managing Director In-Memory Solutions Director Accenture Innovation Center for SAP Titel Alexander Accenture GmbH Campus Kronberg 1 D Kronberg alexander.zeier@accenture.com 33