Step by Step: Big Data Technology. Assoc. Prof. Dr. Thanachart Numnonda Executive Director IMC Institute 25 August 2015

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1 Step by Step: Big Data Technology Assoc. Prof. Dr. Thanachart Numnonda Executive Director IMC Institute 25 August 2015

2 Data Sources IT Infrastructure Analytics 2

3 B y 2015, 20% of Global 1000 organizations Will have established a strategic focus on information infrastructure Gartner 3

4 The Need for new technology Size of data is too big RDBMS are the square peg for all round holes Not all data requires ACID Many data are unstructure 4

5 Big Data Technologies Source: Splunk 5

6 Big Data Technology!! 6

7 Big Data Landscape Source: Big Data in the Enterprise. When to Use What? 7

8 Big Data Technology Storage Analytics 8

9 What is Hadoop? A scalable fault-tolerant distributed system for data storage and processing Completely written in java Open source & distributed under Apache license 9

10 Hadoop Environment Source: Hadoop in Practice; Alex Holmes 10

11 Hadoop 2 11

12 Hadoop Distribution Microsoft Azure 12

13 Apache Spark Stack 13

14 14

15 Big Data Future Architecture Spreadsheet Predictive Analytics Data Market Place Familiar End User Tools BI Platform Hundreds of TB of Data (structured) Petabytes of Data (Unstructured) Hadoop On Private Server Hadoop On Cloud Sscial Media Images S S R S s Connectors Data Warehouse / NewSQL Crawlers NoSQL ERP Unstructured and Structured Data CRM LOB APPs 15

16 16

17 Components of Big Data Architecture Source: ThinkBig Analytics 17

18 Big Data Architecture Platform Source: ThinkBig Analytics 18

19 Big Data Architecture Platform Source: ThinkBig Analytics 19

20 Big Data Architecture: Data Source: ThinkBig Analytics 20

21 Big Data Architecture: Applications Source: ThinkBig Analytics 21

22 Big Data Architecture: Analytics Source: ThinkBig Analytics 22

23 Big Data is complicated and hard to implement Multilayer of technology to integrate Many vendors: each selling only piece of a solution It can take months to build one analytics application Source: ThinkBig Analytics 23

24 Issue with Big Data Infrastructure Large investment Scalabilty ROI Business Cases 24

25 Big Data on Cloud Using IaaS to leverage Cloud Vms Using Big Data as a Services 25

26 Big Data using IaaS 26

27 27

28 28

29 29

30 Source: 30

31 Big Data Services on Cloud Amazon Elastic Mapreduce Microsoft Azure Hadoop 31

32 Big Data as a Service 32

33 Database as a Service Amazon RDS IBM SQL Database for Bluemix Microsoft SQL Database Google CloudSQL 33

34 NoSQL as a Service Amazon DynomoDB Google Cloud DataStore Microsoft Azure DocumentDB Cloudant on IBM Bluemix. Mongo DB on Heroku 34

35 Hadoop as a Service Amazon Elastic Map Reduce Rackspace Cloud Big Data Platform Qubole Google Cloud Platform IBM Bluemix: Analytic on Hadoop Microsoft Azure HDInsight 35

36 Amazon EMR 36

37 Analytic as a Service Google Big Query Amazon Machine Learning Azure Machine Learning BIME: BI as a Service IBM Watson Analytic 37

38 38

39 39

40 Sample applications Enterprise applications already hosted in the cloud High-volume external data sources that require considerable preprocessing Tactical applications beyond your onpremises, Big Data capabilities Elastic provisioning of very large but shortlived analytic sandboxes Source : Deploying Big Data Analytics Applications to the Cloud: Roadmap for Success: CSCS40

41 41

42 42

43 IMC Institute's Big Data Courses 2016 Big Data in Action for Senior Management Big Data using Hadoop Workshop Big Data Programming using Hadoop for Developer Big Data Certification courses Introduction to Data Science Introduction to Machine Learning Data Amaytics using Spark Introduction to R Programming Data Visualisation Workshop Web-based Data Visualization with JavaScript Business Intelligence Design and Process 43

44 44

45 Thank you

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