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Instant Results with Infinite Storage David Parker, VP SAP Big Data Platform.

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Presentation on theme: "Instant Results with Infinite Storage David Parker, VP SAP Big Data Platform."— Presentation transcript:

1 Instant Results with Infinite Storage David Parker, VP SAP Big Data Platform

2 ©2013 SAP AG. All rights reserved.2 Big Data Economics Lots of Opportunity Predictive incl. data mining and machine learning “Unstructured” Analysis Incl. text, media, spatial etc. Scalable Storage Streaming Data incl. Sensors, Social and Mobile Urgent Need

3 ©2013 SAP AG. All rights reserved.3 Open Source Community Gift Apache Hadoop Predictive incl. data mining and machine learning “Unstructured” Analysis Incl. text, media, spatial etc. Scalable Storage Streaming Data incl. Sensors, Social and Mobile Urgent Need Apache Hadoop ► [Commons] ► [Projects] ► [Distributions] ► [Data Scientists]

4 ©2013 SAP AG. All rights reserved.4 The Big Data Phenomenon Big Data is More Than Just Hadoop… Exploding data volumes Accelerating data velocity Increasing data variety Business TrendsTechnology Trends Storage / Memory / CPU advances Data Mining/Predictive analysis In-memory computing Hadoop & distributed MPP Complex event processing “Enterprise” Big Data

5 ©2013 SAP AG. All rights reserved.5 SAP HANA + Hadoop Real-Time Big Data for the Enterprise Combine INSTANT Results with INFINITE Storage 8 Real-time Infinite storage Instant Results SAP HANA HADOOP Modern In-memory platform Transact/Analyze in Real-Time Native Predictive, Text, and Spatial algorithms Distributed Disk platform Store infinite amounts of unstructured data No-SQL Access

6 ©2013 SAP AG. All rights reserved.6 Example: Data Analysis of Cancer Genome Goal: Analytics for Personalized Medicine

7 ©2013 SAP AG. All rights reserved.7 MKI Design Decisions to Improve Speed of Processing Use Hadoop for Pre-Processing; SAP HANA for Advanced Analytics

8 ©2013 SAP AG. All rights reserved.8 Genomic DNA analysis in real-time will transform how we enable comprehensive patient care to fight against cancer. SAP HANA will be the mission critical and reliable data platform to make real-time cancer analytics into a reality. Separately, our internal technical comparison demonstrated that SAP HANA outperforms a traditional disk-based system by factor of 408,000 when performing other types of data analysis. Yukihisa Kato, Director & Executive Officer, CTO, Research and Development Center, MITSUI KNOWLEDGE INDUSTRY CO.,LTD. Benefits  Accelerated predictive & correlation analysis with in- memory processing  Reduced time to detect variant DNA  Optimized treatment plans based on DNA mutations 408,000x faster than traditional disk-based systems in PoC 216x faster DNA analysis results - from 2-3 days to 20 minutes “” SAP HANA + HADOOP + R SAP HANA + Hadoop for Advanced Analytics Results: Deliver Personalized Results More Quickly

9 ©2013 SAP AG. All rights reserved.9 Supports any Device Any Apps Any App Server Any Apps Any App Server SAP Business Suite and BW ABAP App Server JSONROpen ConnectivityMDX SQL Other AppsLocationsReal-timeHADOOPMachineUnstructuredTransaction HANA Platform SQL, SQLScript, JavaScript Integration Services Spatial Business Function Library Search Text Mining Predictive Analysis Library Database Services Stored Procedure & Data Models Planning Engine Rules Engine Application & UI Services SAP HANA Platform More than Just a Database

10 ©2013 SAP AG. All rights reserved.10 SAP HANA Platform ApplicationsAnalytics Landscape management SAP HANA In Memory Modeling & lifecycle management Apache Hadoop Distributions Roles, security, governance, compliance, audits Consume Store & Process Ingest Replication Framework Data Services Transactional Planning & Simulation Graph Analytical Machine Learning & Predictive Machine Learning & Predictive Native HANA Apps & Services Spatial Consume Process ESP IM Extended Storage (IQ) Tiered Storage (Hot-warm-cold) Smart Data Access Text, Social Media Processing Exploration, Dashboards, Reports, Charting, Visualization Exploration, Dashboards, Reports, Charting, Visualization SAP HANA Platform for Big Data End-to-End Environment for the Enterprise

11 ©2013 SAP AG. All rights reserved.11 SAP HANA Platform for Big Data Open Hadoop Strategy Big Data Science Services SAP HANA Platform SAP Data Services Data Connectors Acquire Accelerate Analyze Sybase IQ SAP HANA GeospatialPredictiveText Analysis Visualize and Act Industry/LOB Apps Custom AppsAnalytic Apps SQLXS EngineR

12 ©2013 SAP AG. All rights reserved.12 Enterprise Scenarios: SAP HANA and Hadoop 4 Common Use Cases Hadoop Data storage (Hadoop Distributed File system) Job Management Computation Engine(s) Hadoop as a flexible data store Hadoop as a simple database Hadoop as a processing engine Hadoop for advanced analytics Reference Data Streaming Data Enterprise Data Transaction Data Social Media SAP HANA Platform SAP Data Services Data Connectors Acquire Accelerate Sybase IQ SAP HANA Analyze GeospatialPredictiveText AnalysisSQLXS EngineR Visualize and Act Applications Analytic Tools Hive

13 ©2013 SAP AG. All rights reserved.13 Execute Query Query Feder- ation Split Query Execute Consolidate Execute New Technology: Smart Data Access Rapid Analysis of Big Data without Data Movement BI and analytics software from SAP In-memory Disk-based data ware- house (SAP Sybase IQ) … and/or... Analytic engine Hadoop Data storage (Hadoop Distributed File system) Job Management Computation Engine(s) HiveHBase … Users Submit a query that accesses remote data like local data Leverage the full power of SAP HANA – analytics, predictive, text search, geospatial – during processing Synthesize enterprise data regardless of location, size, representation – without moving it

14 ©2013 SAP AG. All rights reserved.14 Decide what remote data sources are needed for the application running on SAP HANA Data Needs Define the remote data source with the appropriate security credentials Sources Create virtual tables which reference the remote data source (table) References Write your application, using HANA tables and virtual tables Query processor in HANA does the rest of the optimizations and data access Application SAP HANA Smart Data Access How to Use

15 ©2013 SAP AG. All rights reserved.15 Example: Smart Data Access Steps For Creating and Using Virtual Tables 1. Create table in HIVE 2. On SAP HANA, create DSN, e.g. “hive1” 3. With SAP HANA Studio or using DLL command, create a remote source: o CREATE REMOTE SOURCE HIVE1 ADAPTER "hiveodbc" CONFIGURATION 'DSN=hive1' WITH CREDENTIAL TYPE 'PASSWORD' USING 'user=dftest;password=dftest'; 4. Using a DLL command, create a virtual table for Hive:  CREATE VIRTUAL TABLE "HIVE1_PRODUCT" AT "HIVE1"."default"."default"."product"; 5. Execute a query on virtual table:  SELECT * FROM HIVE1_PRODUCT; 6. Drop a virtual table  DROP REMOTE SOURCE HIVE1 CASCADE;

16 ©2013 SAP AG. All rights reserved.16  SAP HANA Platform  Unprecedented insights  combine structured and unstructured data for insights never seen before  Advanced analytics  predictive, text, and spatial analytics  Instant results with in-memory processing  Apache Hadoop  Data exploration / mining  uncover nuggets information from large volumes of unknown data  Infinite storage  offload or archive cold data Amplify the Value of Big Data Marry SAP HANA and Hadoop for real-time business results

17 ©2013 SAP AG. All rights reserved.17 Get SAP HANA for Free www.saphana.com/docs/DOC-369

18 ©2013 SAP AG. All rights reserved.18 Participate in SAP HANA Academy www.saphana.com/community/hana-academy  Developer Sandbox  Available for hands-on training  Projects  Create HTML5 applications  Create data marts  Etc.  Online Courses and Videos  SAP HANA  Predictive Analytics Library  R Integration  SAP Lumira (visualizations)  And more…

19 ©2013 SAP AG. All rights reserved.19 Join the Big Data Geek Challenge by SAP www.sap.com/bigdata/challenge How to Enter*: 1) Get SAP Lumira (for free) 2) Design a data visualization to analyze Big Data quickly 3) Make a video to present your use case 4) Submit your entry 5) Winners to be announced by December 2013 Challenge only available to residents of the United States. See official entry rules for details.

20 ©2013 SAP AG. All rights reserved.20 SAP Startup Focus Program www.saphana.com/community/learn/startups

21 SAP Lumira & SAP Predictive Analysis SAP Startup Focus Program SAP HANA + HADOOP Instant results + Infinite Storage Visit Booth 311

22 Thank you Contact information: David Parker david.parker@sap.com www.sap.comwww.sap.com/bigdata facebook.com/sapanalytics twitter.com/#!/@sapinmemory


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