Forecast of Big Data Trends. Assoc. Prof. Dr. Thanachart Numnonda Executive Director IMC Institute 3 September 2014

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1 Forecast of Big Data Trends Assoc. Prof. Dr. Thanachart Numnonda Executive Director IMC Institute 3 September 2014

2 Big Data transforms Business 2

3 Data created every minute Source 3

4 The Rise of Big Data 4

5 Data Growth 5

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 6

7 Three Characteristics of Big Data Source Introduction to Big Data: Dr. Putchong Uthayopas 7

8 Big Data Supply Chain 8

9 Big Data Application Area Source: BIG DATA Case Study,Anju Singh 9

10 Big Data Use Cases 10

11 Hospitality Industry Captures Source McKinsey & Company 11

12 Next Product to Buy Source McKinsey & Company 12

13 Big Data Landscape Source: Big Data in the Enterprise. When to Use What? 13

14 Big Data Solution Spreadsheet Predictive Analytics Embedded BI Data Market Place Familiar End User Tools S S R S BI Platform Hundreds of TB of Data (structured) Petabytes of Data (Unstructured) Hadoop On Private Server Hadoop On Cloud Sensors Devices Data Market Bots Connectors Parallel Data Warehouse Crawlers ERP CRM Unstructured and Structured Data LOB APPs 14

15 The market for big data will reach $16.1 billion in 2014, growing 6 times faster than the overall IT market. IDC 15

16 Prediction #1 Hadoop will gain in stature 16

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 17

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 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 [IDC] 18

19 Prediction #2 SQL holds biggest promise for Big Data 19

20 Big Data Technologies Adopted or To Be Adopted in Next 24 Months Source: 2013 Big Data Opportunities Survey, Unisphere Research May

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: 21

22 Prediction #3 Big Data vendor consolidation begins 22

23 Worldwide Big Data Revenue 2013 Source: Wikibon.org 23

24 Hadoop Distribution Amazon Cloudera MapR Microsoft Windows Azure IBM Infosphere BigInsights EMC Greenplum HD Hadoop distribution Hartonwork 24

25 25

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 tierone megavendors like IBM and Oracle. 26

27 Prediction #4 Internet of things grow 27

28 28

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). 29

30 30

31 Prediction #5 More data warehouses will deploy enterprise data hubs 31

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: 32

33 Data Warehouse Offload 33

34 Enterprise Data Hub 34

35 Prediction #6 Business intelligence (BI) will be embedded on smart systems 35

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: 36

37 Evolution of Embedded BI Source: 37

38 Source: Jaspersoft 38

39 Prediction #7 Less relational SQL, more NoSQL 39

40 Data Management Trends Source KMS Technology 40

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 41

42 Popular NoSQL/New SQL Distributions 42

43 Prediction #8 Hadoop will shift to real-time processing 43

44 Hadoop 1.0 Ecosystem Pig MapReduce (Job Scheduling/Execution System) HBase Flume Zookepper Hive HDFS (Hadoop Distributed File System) Source Big Data Hadoop: Danairat Thanabodithammachari 44

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 45

46 Hadoop

47 Prediction #9 Big Data as a Service (BDaaS) 47

48 Analytics Analytics Software Software as as aa Service Service Data Data as as aa Service Service (Database, (Database, No No SQL, SQL, Hadoop, Hadoop, in-memory) in-memory) Storage Storage as as aa Service Service Compute as a Service 48

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 More Cloud provider will offer Hadoop as a Service Amazon AWS Microsoft Azure HD Insight IBM Bluemix Qubole 49

50 50

51 51

52 52

53 Prediction #10 External data is as important as internal data 53

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 54

55 Hadoop & BI Hadoop Internal Fast Database BI Tool External 55 Source: Big Data and BI Best Practices: YellowFin

56 56

57 Thank you

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