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Real-time Data Analysis with Hadoop and SAP HANATUT18851
dr. Tamas Szirtes
Director Innovation & Technology
SOA People Nederland
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Leading European consulting and services group
specialized in SAP solutions
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38 4048 50 53
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2007 2008 2009 2010 2011 2012 2013 2014 2015
+400 customersIn all kinds of industries and companies of
all sizes
+500experts
+8 years of success
+8 regionaloffices in Europe
SOA People in numbers
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Organi-zation
CUSTOMERS’ CHALLENGES
STRATEGY
Business Processes
Tools
MobileAnalyticsApplications Big data & real time
CloudNetworks
Based on disruptive technology to gain higher competitiveness
Being your IT partner to develop your Business strategy in full
alignment with SAP leading solutions
SOA People’s positioning
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Agenda
• Introduction
• Technologies covered
– Hadoop
– SAP HANA
• Typical solution architectures
• SUSE enabling technology
• Q&A
Introduction
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The Big Data Opportunity
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Transactions
“Which types of data do you anticipate using in the next year?”
Source: Paradigm4 data scientist survey 2014www.paradigm4.com/wp-content/uploads/2014/06/P4-data-scientist-survey-FINAL.pdf
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SAP Big Data Applications
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SAP Big Data Analytics
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SAP Big Data IT Landscape Challenge
Technologies covered: Hadoop
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What is Hadoop
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Spark
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CDH
Technologies covered: SAP HANA
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What is SAP HANA
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In Memory Technology
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SAP HANA Live
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SAP HANA Two-Tier Architecture
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Predictive Analytics
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SAP HANA Evolution
Typical solution architectures
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Big Data Architectures
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What does Hadoop bring to HANA?
Batch processingWhere fast response times are less critical than reliability and scalability
Complex information processing at scaleEnable heavily recursive algorithms, machine learning, & queries that cannot be easily expressed in SQL
Massive store for low value dataData stays available, though access is much slower
Post-hoc analysis Mine raw data that is either schema-less or where schema changes over time
Cost efficient data storage and processing for large volumes of structured, semi-structured, and unstructured data such as web logs, machine data, text data, call data records (CDRs), audio, video data
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Scenarios for implementations
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SAP Big Data Acquisition
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Data Aging
+ Data Tiering
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Intel + Intenzz
http://www.intel.com/content/www/us/en/big-data/intenzz-xeon-e7-4880-big-data-brief.html
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Hadoop integration
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Hadoop Integration Roadmap
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HANA Vora
SAP HANA Vora is an in-memory query engine which leverages and extends the Apache Spark execution framework to provide enriched interactive analytics on Hadoop. Drill Downs on HDFS
Mashup API Enhancements
Compiled Queries
HANA-Spark Adapter
Unified Landscape
Open Programming
Make PrecisionDecisions
DemocratizeData Access
SimplifyBig DataOwnership
Any Hadoop Clusters
SUSE enabling technology
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SUSE for SAP
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SUSE for SAP
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SUSE for SAP
• Optimized for fast deployment.• Seamless integration.• Optimized for business continuity.• Integrated 24x7 support.• Support for large memory intensive workloads.• Extended service pack overlap support.• Flexible cloud options.• Optimized for SAP HANA.• Optimized for performance.
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SUSE Linux Enterprise + SAP HANA
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SUSE Linux Enterprise Server for SAP
• Automate HANA System Replication• Patch the OS kernel while it’s running• Undo system changes
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Q&A