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Big Data /Hadoop and SAP HANA

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Intro to next step in Technology, Big Data. Basic understanding plus common jargon. How they integrate and makes sense for Business enablement.

Intro to next step in Technology, Big Data. Basic understanding plus common jargon. How they integrate and makes sense for Business enablement.

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  • 1. ASUG/SAP SERIES – Big Data/Hadoop/HANA Why Big Data ? Why it can fit into your Business and Technology Roadmap What it can do to Enable your Business! John Choate – PMMS SIG Chair Bill Klinke – PMMS Program Chair David Burdett – Strategic Technology Advisor, SAP
  • 2. The New and Ever Changing Landscape 2
  • 3. Open Source Big Data – CONFUSED???? 3
  • 4. The 5 Part Series  Webinar 1: Why Big Data matters, how it can fit into your Business and Technology Roadmap, and how it can enable your business!  Webinar 2: How Big Data technologies provide Solutions for Big Data problems  Webinar 3: Using Hadoop in an SAP Landscape with HANA  Webinar 4: Leveraging Hadoop with SAP HANA smart data access  Webinar 5: Using SAP Data Services with Hadoop and SAP HANA Resources … Webinar Registration 1. Go to www.saphana.com 2. Search “ASUG Big Data Webinar” 3. Registration links in blog … Big Data, Hadoop and Hana – How they Integrate and How they Enable your Business! Info on SAP and Big Data – go to www.sapbigdata.com 4
  • 5. BIG DATA DEFINED UNDERSTANDING BIG DATA BIG DATA JARGON 5
  • 6. Multiple Definitions of Big Data*  The Original Big Data – Big Data as the three Vs: Volume, Velocity, and Variety  Big Data as Technology – Fast rise of open source technologies such as Hadoop and other NoSQL ways of storing and manipulating data  Big Data as Data Distinctions – Interactions are data collected from people, e.g. web page clicks; Observations are data collected automatically  Big Data as Signals – In the ‘new world,’ companies can use new signal data to anticipate what’s going to happen in “Real Time”, and intervene  Big Data as Opportunity – Explore new opportunities for Business via Technology enablers  Big Data as Metaphor – Creating the planet’s nervous system. Read the The Human Face of Big Data by Rick Smolan and you will understand  Big Data as New Term for Old Stuff – BI or analytics in the past have been rebranded in a leap to jump onto the big data bandwagon 6 * http://timoelliott.com/blog/2013/07/7-definitions-of-big-data-you-should-know-about.html
  • 7. Big Data Simplified Definition • “Big data” is high-volume, - velocity and -variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making Gartner Three Key Parts • Part One: 3V’s – Volume, Velocity, Variety • Part Two: Cost-Effective, Innovative Forms of Information Processing • Part Three: Enhanced insight for “Real Time” decision making 7
  • 8. The 7 Key Drivers Behind the Big Data Movement? * Business 1. Opportunity to enable innovative new business models 2. Potential for new insights that drive competitive advantage Technical 1. Data collected and stored continues to grow exponentially 2. Data is increasingly everywhere and in many formats 3. Traditional solutions are failing under new requirements Financial 1. Cost of data systems, as a percentage of IT spend, continues to grow 2. Cost advantages of commodity hardware & open source software 8 * http://hortonworks.com/blog/7-key-drivers-for-the-big-data-market/
  • 9. Todays Key Challenges in Big Data Information Strategy 1. Which investments will deliver most business value and ROI? 2. Governance – New expectations for data quality and management 3. Talent – How will you assemble the right teams and align skills? Data Analytics 1. Data Capture & Retention – What data should be kept and why 2. Behavioral Analytics – Understanding and leveraging customer behavior 3. Predictive Analytics – Using new data types (sentiment, clickstream, video, image and text) to predict future events Enterprise Information Management 1. User expectations – Making “Big Data” accessible for the end user in “real-time” 2. Costs – How to provide access to big data in a rapid and cost-effective way to support better decision-making? 3. Tools – Have you identified the processes, tools and technologies you need to support big data in your enterprise? 9
  • 10. 10 BIG DATA DEFINED UNDERSTANDING BIG DATA BIG DATA JARGON
  • 11. How did we get here? 1990 20152000 2005 2010 DATABASE (CIRCA 1980) ANALYTICS (CIRCA 1980) PREDICTIVE ANALYTICS (CIRCA 1980) SEMANTIC ANALYTICS (CIRCA 1980) REAL TIME 1,000,000+ SOLD WWW 3,000,000 people had access to internet worldwide B2B / B2C MOBILE More people have mobile phones than electricity or safe drinking water Facebook: 1 billion users; 600 mobile users; more than 42 million pages and 9 million apps Youtube: 4 billion views per day Google+: 400 million registered users Skype: 250 million monthly connected users SOCIAL BIG DATA PERSONAL COMPUTER AND CLIENT SERVER 11 2013
  • 12. How big is Big Data? 1.8 IN 2011, THE AMOUNT OF DATA SURPASSED ZETTABYTES 90% OF THE DATA IN THE WORLD TODAY has been created in the last two years alone! Today we measure available data in zettabytes (1 trillion gigabytes) 12 Eight 32GB iPads per person alive in the world
  • 13. Social Media Growth 2013* Mobile phones increased 60.3% to 818.4m in last two years Facebook has 665m daily active users Twitter has 228m monthly active users – 44% growth YouTube hours watched – doubled to 6B hours watched Google+ has 395m monthly active users – grew 33% LinkedIn has 200m users * http://growingsocialmedia.com/social-media-statistics-and-facts-of-2013-infographic/ 13
  • 14. The Internet of Things 14 Key contributor to growth of Big Data • Sensor data • RFID • Telematics • Devices connected to Internet expected to grow 25 billion by 2015 & 50 billion by 2020
  • 15. Many Types of Data Mobile CRM Data Planning Opportunities Transactions Customer Sales Order Things Instant Messages Demand Inventory Big Data Sales Order Things MobileDemand Big Data CRM Data CustomerPlanning Transactions Data comes in many different shapes and sizes 15
  • 16. SAP Data + Big Data = Better Value 16 Mobile CRM Data Planning Opportunities Transactions Customer Sales Order Things Instant Messages Demand Inventory Big Data Sales Order Things MobileDemand Big Data CRM Data CustomerPlanning Transactions Non-SAP (Big) Data SAP® Solutions SAP HANA Data warehouse/database SAP Business Suite Other SAP solutions SAP Data + Combining SAP Data with “Big Data” provides better business insights
  • 17. Big Data and Competitive Advantage 17 Utilize your data to gain a competitive advantage! Competitiveness of fact-finders vs. fumblers Laggards Leaders Fumblers Fact- finders Fumblers Fact- finders • Base decisions on the latest, granular multi-structured data • Make decisions on analytics rather than intuition • Frequently reassess forecasts and plans • Utilize analytics to support a spectrum of strategic, operational and tactical decision making • Rapidly evaluate alternative scenarios Leading businesses can outpace the competition because they can: n=1,002 Source: IDC‘s SAP HANA Market Assessment, August 2011
  • 18. BIG DATA DEFINED UNDERSTANDING BIG DATA BIG DATA JARGON 18
  • 19. Demystifying Big Data Demystifying Big Data Jargon  Big Data – the six V’s  Structured vs. Unstructured Data  SQL vs. NoSQL  Hadoop 19
  • 20. Demystifying Big Data – The Six V’s 20
  • 21. Demystifying Big Data – Structured vs. Unstructured Structured Data • Well-defined content • Examples – Customer data – Sales data – Sensor data • Easily understood • Stored in an RDBMS Unstructured Data • Structure not obvious • Examples: – Images – Video – Natural language text • Process data to understand • RDBMS not a good fit 21 Semi-Structured Data Combination of both, e.g. email, social media feeds
  • 22. Demystifying Big Data – SQL vs. NoSQL SQL Databases • Structured data only • Scalable • High Data Consistency • Define structure first • Systems of Record (SAP) • Examples: DB2, Oracle NoSQL Databases • Structured or unstructured • More scalable • Eventual data consistency • Define structure later • Flexible Data Store • Examples: Cassandra, HBase, MongoDB 22
  • 23. Demystifying Big Data – Hadoop • 10s to 1000s servers • Open source SW • Commodity HW • Any type of data (NoSQL) • Many ways to process • Relatively slow • Rapidly evolving 23 Cluster of Commodity Servers Hadoop NameNode   10s to 1000s DataNode(s) Hadoop Computation Engines Map-Reduce Hive HBase Mahout Pig Sqoop … Data storage (Hadoop Distributed File system) Hadoop Software Architecture
  • 24. The Challenge of Big Data 24 Customer IT Developer Analyst LOB User Data Decision-Maker
  • 25. Key Take Aways  Big Data is having a big impact on business  Leveraging Big Data provides new opportunities  Better value from SAP Data + Big Data together  Challenge is how to leverage Big Data for benefit  Watch the rest of the series to find out more 25
  • 26. The 5 Part Series  Webinar 1: Why Big Data matters, how it can fit into your Business and Technology Roadmap, and how it can enable your business!  Webinar 2: How Big Data technologies provide Solutions for Big Data problems  Webinar 3: Using Hadoop in an SAP Landscape with HANA  Webinar 4: Leveraging Hadoop with SAP HANA smart data access  Webinar 5: Using SAP Data Services with Hadoop and SAP HANA Resources … Webinar Registration 1. Go to www.saphana.com 2. Search “ASUG Big Data Webinar” 3. Registration links in blog … Big Data, Hadoop and Hana – How they Integrate and How they Enable your Business! Info on SAP and Big Data – go to www.sapbigdata.com 26
  • 27. Q & A Questions ? 27
  • 28. THANK YOU FOR PARTICIPATING For ongoing education on this area of focus, visit ASUG.com 28