Forecast of Big Data Trends

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Presentation by IMC Institute's Executive Director at "Big Data: From Data to Business Insight" on 3 September 2014

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Forecast of Big Data Trends

  1. 1. Forecast of Big Data Trends Assoc. Prof. Dr. Thanachart Numnonda Executive Director IMC Institute 3 September 2014
  2. 2. 2 BBiigg DDaattaa transforms Business
  3. 3. 3 Data created every minute Source http://mashable.com/2012/06/22/data-created-every-minute/
  4. 4. 4 The Rise of Big Data
  5. 5. 5 Data Growth
  6. 6. 6 What is Big Data? Big data is data that exceeds the processing capacity of conventional database systems. The data is too big, moves too fast, or doesn’t fit the structures of your database architectures. To gain value from this data, you must choose an alternative way to process it. Big Data Now: O'Reilly Media
  7. 7. 7 Three Characteristics of Big Data Source Introduction to Big Data: Dr. Putchong Uthayopas
  8. 8. 8 Big Data Supply Chain
  9. 9. 9 Big Data Application Area Source: BIG DATA Case Study,Anju Singh
  10. 10. 10 Big Data Use Cases
  11. 11. 11 Hospitality Industry Captures Source McKinsey & Company
  12. 12. 12 Next Product to Buy Source McKinsey & Company
  13. 13. 13 Big Data Landscape Source: Big Data in the Enterprise. When to Use What?
  14. 14. 14 Big Data Solution Spreadsheet Predictive Analytics Embedded BI Petabytes of Data (Unstructured) Sensors Devices Bots Crawlers ERP CRM LOB APPs Unstructured and Structured Data Parallel Data Warehouse Hadoop On Cloud Hadoop On Private Server Connectors S S RS BI Platform Familiar End User Tools Data Market Place Data Market Hundreds of TB of Data (structured)
  15. 15. 15 “ The market for big data will reach $16.1 billion in 2014, growing 6 times faster than the overall IT market. ” IDC
  16. 16. 16 Prediction #1 Hadoop will gain in stature
  17. 17. 17 What is Hadoop? A scalable fault-tolerant distributed system for data storage and processing Completely written in java Open source & distributed under Apache license
  18. 18. 18 Hadoop is growing Hadoop will continue to displace other IT spending, disrupting enterprise data warehouse and enterprise storage. IDC predicting the co-habitation for the foreseeable future of RDBMS with the newer Hadoop ecosystem and NoSQL databases. Hadoop software revenue was $209.2 million or 11 percent of the total big data software market in 2012. The comprehensive Hadoop market (combined hardware, software, & services) bagged 23 percent of the big data market in 2012, which was projected to grow to 31 percent in 2013. [IDC]
  19. 19. 19 Prediction #2 SQL holds biggest promise for Big Data
  20. 20. 20 Big Data Technologies Adopted or To Be Adopted in Next 24 Months Source: 2013 Big Data Opportunities Survey, Unisphere Research May 2013
  21. 21. 21 SQL development for Hadoop Hadoop uses MapReduce to process Big Data. SQL development for Hadoop enables business analysts to use their skills and SQL tools of choice for big data projects. Developers can now choose – Hive – Impala – Jaql – Hadapt Source: www.eweek.com
  22. 22. 22 Prediction #3 Big Data vendor consolidation begins
  23. 23. 23 Worldwide Big Data Revenue 2013 Source: Wikibon.org
  24. 24. 24 Hadoop Distribution Amazon Cloudera MapR Microsoft Windows Azure IBM Infosphere BigInsights EMC Greenplum HD Hadoop distribution Hartonwork
  25. 25. 25
  26. 26. 26 Hadoop clone wars end Expects to see consolidation among big data startups Some companies will start to close their doors, while others will probably get acquired. Cloudera competes against the likes of tier-one megavendors like IBM and Oracle.
  27. 27. 27 Prediction #4 Internet of things grow
  28. 28. 28
  29. 29. 29 Internet of things The Internet is expanding beyond PCs and mobile devices into enterprise assets such as field equipment, and consumer items such as cars and televisions. Over 50% of Internet connections are things. Enterprises should not limit themselves to thinking that only the Internet of Things (i.e., assets and machines) as the potential to leverage the four "internets” (people, things, information and places).
  30. 30. 30
  31. 31. 31 Prediction #5 More data warehouses will deploy enterprise data hubs
  32. 32. 32 Hadoop roles in data warehouses Data hubs offload ETL processing and data from enterprise data warehouses to Hadoop Hadoop acting as a central enterprise hub. 10 times cheaper and can perform more analytics for additional processing or new apps. Source: www.eweek.com
  33. 33. 33 Data Warehouse Offload
  34. 34. 34 Enterprise Data Hub
  35. 35. 35 Prediction #6 Business intelligence (BI) will be embedded on smart systems
  36. 36. 36 Embedded BI Embedded data analytics and “business intelligence” begin to emerge. Sales forces may manage their customer relationships through embedded, smart apps with built-in analytics to make decisions Progressively, smart software in mobile and enterprise systems will make decisions and make data scientists redundant. Source: http://www.experfy.com
  37. 37. 37 Evolution of Embedded BI Source: http://www.b-eye-network.com/
  38. 38. 38 Source: Jaspersoft
  39. 39. 39 Prediction #7 Less relational SQL, more NoSQL
  40. 40. 40 Data Management Trends Source KMS Technology
  41. 41. 41 NoSQL NoSQL means “Not only SQL”, rather than “the absence of SQL” There are many ways to look at data other tham structure and ordered approach that SQL requires. The industry is begining to seatle on a few major of players
  42. 42. 42 Popular NoSQL/New SQL Distributions
  43. 43. 43 Prediction #8 Hadoop will shift to real-time processing
  44. 44. 44 Hadoop 1.0 Ecosystem Pig MapReduce Hive (Job Scheduling/Execution System) HDFS (Hadoop Distributed File System) Zookepper Flume HBase Source Big Data Hadoop: Danairat Thanabodithammachari
  45. 45. 45 Limitation of Hadoop 1.x No horizatontal scalability of NameNode Does not support NameNode high availability Not possible to run Non-MapReduce Big Data applications on HDFS Run as a batch job Does not support Multi-tenancy
  46. 46. 46 Hadoop 2.0
  47. 47. 47 Prediction #9 Big Data as a Service (BDaaS)
  48. 48. 48 AAnnaallyyttiiccss SSooffttwwaarree aass aa SSeerrvviiccee Data as a Service Data as a Service (Database, No SQL, Hadoop, in-Memory) (Database, No SQL, Hadoop, in-Memory) SSttoorraaggee aass aa SSeerrvviiccee Compute as a Service
  49. 49. 49 Big Data as a Service The IDC estimates for Hadoop-as-a-service market in 2012 was about $130 million, projected to grow by 145 percent to $318 million in 2013. More Cloud provider will offer Hadoop as a Service – Amazon AWS – Microsoft Azure HD Insight – IBM Bluemix – Qubole
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  52. 52. 52
  53. 53. 53 Prediction #10 External data is as important as internal data
  54. 54. 54 External Data The explosive growth of social media, mobile devices, and machine sensors is generating a wealth of bits. Some of this data is generated within an organization, but a larger percentage comes from the outside In 2014, businesses will find more ways to harness this mix of structured and unstructured data
  55. 55. 55 Hadoop & BI Hadoop Fast Database BI Tool Internal External Source: Big Data and BI Best Practices: YellowFin
  56. 56. 56 www.facebook.com/imcinstitute
  57. 57. 57 Thank you thanachart@imcinstitute.com www.facebook.com/imcinstitute www.slideshare.net/imcinstitute

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