《SAPHANA介绍》.ppt

Introduction to HANA,,Core Team: xxx,.,In-Memory Computing,Technology that allows the processing of massive quantities of real time data in the main memory of the server to provide immediate results from analyses and transactions,,,.,Increasing Data Volumes,Calculation Speed,Type and # of Data Sources,,Lack of business transparency Sales & Operations Planning based on subsets of highly aggregated information, being several days or weeks outdated.,Reactive business model Missed opportunities and competitive disadvantage due to lack of speed and agility Utilities: daily- or hour-based billing and consumption analysis/simulation.,Vision: In-Memory Computing Technology Constrained Business Outcome,,Sub-optimal execution speed Lack of responsiveness due to data latency and deployment bottlenecks Inability to update demand plan with greater than monthly frequency,,Information Latency,.,TeraBytes of Data In-Memory,100 GB/s data througput,Real Time,Freedom from the data source,,,Improve Business Performance IT rapidly delivering flexible solutions enabling business Speed up billing and reconciliation cycles for complex goods manufacturers Planning and simulation on the fly based on actual non-aggregated data,Competitive AdvantageE.g. Utilities Industry: Sales growth and market advantage from demand/cost driven pricing that optimizes multiple variables consumption data, hourly energy price, weather forecast, etc.,Vision: In-Memory Computing Leapfrogging Current Technology Constraints,Flexible Real Time Analytics Real-time customer profitability Effective marketing campaign spend based on large-volume data analysis,,.,,,,In-Memory Computing The Time is NOWOrchestrating Technology Innovations,HW Technology Innovations,64bit address space 2TB in current servers 100GB/s data throughput Dramatic decline in price/performance,Multi-Core Architecture (8 x 8core CPU per blade) Massive parallel scaling with many blades,Row and Column Store,Compression,Partitioning,No Aggregate Tables,Real-Time Data Capture Insert Only on Delta,The elements of In-Memory computing are not new. However, dramatically improved hardware economics and technology innovations in software has now made it possible for SAP to deliver on its vision of the Real-Time Enterprise with In-Memory business applications,SAP SW Technology Innovations,.,SAP Strategy for In-Memory,,,,,,EXPAND PARTNER ECOSYSTEM Partner-built applications, Hardware partners,CUSTOMER CO-INNOVATION Design with customers,TECHNOLOGY INNOVATION BUSINESS VALUE Real-Time Analytics, Process Innovation, Lower TCO,,,GUIDING PRINCIPLES,INNOVATION WITHOUT DISRUPTION New Capabilities For Current Landscape,HEART OF FUTURE APPLICATIONS Packaged Business Solutions for Industry and Line of Business,.,,In-Memory Computing Product “SAP HANA”SAP High Performance Analytic Appliance,What is SAP HANA? SAP HANA is a preconfigured out of the box Appliance In-Memory software bundled with hardware delivered from the hardware partner (HP, IBM, CISCO, Fujitsu) In-Memory Computing Engine Tools for data modeling, data and life cycle management, security, operations, etc. Real-time Data replication via Sybase Replication Server Support for multiple interfaces Content packages (Extractors and Data Models) introduced over time Capabilities Enabled Analyze information in real-time at unprecedented speeds on large volumes of non-aggregated data. Create flexible analytic models based on real-time and historic business data Foundation for new category of applications (e.g., planning, simulation) to significantly outperform current applications in category Minimizes data duplication,SAP HANA,SAPBusiness Suite,SAP BW,3rd Party,,,,replicate,ETL,SAP HANAmodeling,BI Clients,,,,SQL,MDX,BICS,,3rd Party,.,Technical Overview,,,Calculation models Extreme Performance and Flexibility with Calculations on the fly,Calculation Model A calc model can be generated on the fly based on input script or SQL/MDX A calc model can also define a parameterized calculation schema for highly optimized reuse A calc model supports scripted operations,Data Storage Row Store - Metadata Column Store 10-20 x Data Compression,., SAP 2007/Page 9,SAP BusinessObjects Data Services Platform,Integrate heterogeneous data into BWA,,Extract From Any Data Source into HANA Syndicate From HANA to Any Consumer,Integrated Data Quality Text Analytics,Rich Transforms,.,SAP HANA Road Map:In-Memory Introduction,Todays System Landscape ERP System running on traditional database BW running on traditional database Data extracted from ERP and loaded into BW BWA accelerates analytic models Analytic data consumed in BI or pulled to data marts,Step 1 In-Memory in parallel(Q4 2010) Operational data in traditional database is replicated intomemory for operational reporting Analytic models from production EDW can be brought into memory for agile modeling and reporting Third party data (POS, CDR etc) can be brought into memory for agile modeling and reporting,.,Step 3 New Applicati。