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Big Data Analytics PlatformBeyond Traditional Enterprise Data Warehouse 1 Recorded version available at  http://www.impetus.com/webinar_registration?event=archived&eid=45
Outline What Is A Traditional Enterprise Data Warehouse? What Is Required From A Big Data Warehouse? Building  Big Data Analytics Platform How To Re-use Existing Investments? Real-world Examples Recorded version available at  http://www.impetus.com/webinar_registration?event=archived&eid=45 2
The Answers We Seek The kind of customer who will spend  most with us next year ? What is the most effective  Distribution channel? In which area should we  open  our new store next year? What kind of products my customers are interested in ? Customers that we are likely to lose ? How much does my  service  impact my margin?  Recorded version available at  http://www.impetus.com/webinar_registration?event=archived&eid=45 3 3
Traditional EDW 4 Recorded version available at  http://www.impetus.com/webinar_registration?event=archived&eid=45
EDW Components Extraction, Transformation and Loading - ETL Data is extracted from a heterogeneous data sources Transformed to match the data warehouse schema Loaded into the data warehouse database  Analyze and Query - OLAP Tools Active analysis - user queries User guided data analysis OLAP Automated Analysis - Data Mining Machine learning / NLP Recommendations & forecasting Recorded version available at  http://www.impetus.com/webinar_registration?event=archived&eid=45 5
Enter Big Data Recorded version available at  http://www.impetus.com/webinar_registration?event=archived&eid=45 6
The Gap Area- Big Data v/s EDW Large data volumes Complex unstructured data Deeper insights Storing images, videos The bottom-line - $/TB Recorded version available at  http://www.impetus.com/webinar_registration?event=archived&eid=45 7
Big Data in EDW 8 Recorded version available at  http://www.impetus.com/webinar_registration?event=archived&eid=45
Key Characteristics - Big Data Platform ,[object Object]
Works on massive data sets
Support for multiple data sources
Easy deployment/ seamless integration
Deep analytics
Canned& customized reports as well as valuable BI
Support for real time analyticsRecorded version available at  http://www.impetus.com/webinar_registration?event=archived&eid=45 9
Building Big Data Analytics Platform 10 Recorded version available at  http://www.impetus.com/webinar_registration?event=archived&eid=45
Building Big Data Analytics Platform Recorded version available at  http://www.impetus.com/webinar_registration?event=archived&eid=45
Building Big Data Analytics Platform Recorded version available at  http://www.impetus.com/webinar_registration?event=archived&eid=45
Building Big Data Analytics Platform
Our Key Learnings ,[object Object]
Parallel processing or faster mechanisms can be used for import/export of data
Real time is a myth in big data – needs careful design
Hadoop is the most cost effective option for big data
Reuse of existing EDW investments possible Recorded version available at  http://www.impetus.com/webinar_registration?event=archived&eid=45 14
Impetus Big Data Analytics Platform- iLaDaP 15 Recorded version available at  http://www.impetus.com/webinar_registration?event=archived&eid=45

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Big Data Analytics Platform- Beyond Traditional EDW

  • 1. Big Data Analytics PlatformBeyond Traditional Enterprise Data Warehouse 1 Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=45
  • 2. Outline What Is A Traditional Enterprise Data Warehouse? What Is Required From A Big Data Warehouse? Building Big Data Analytics Platform How To Re-use Existing Investments? Real-world Examples Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=45 2
  • 3. The Answers We Seek The kind of customer who will spend most with us next year ? What is the most effective Distribution channel? In which area should we open our new store next year? What kind of products my customers are interested in ? Customers that we are likely to lose ? How much does my service impact my margin? Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=45 3 3
  • 4. Traditional EDW 4 Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=45
  • 5. EDW Components Extraction, Transformation and Loading - ETL Data is extracted from a heterogeneous data sources Transformed to match the data warehouse schema Loaded into the data warehouse database Analyze and Query - OLAP Tools Active analysis - user queries User guided data analysis OLAP Automated Analysis - Data Mining Machine learning / NLP Recommendations & forecasting Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=45 5
  • 6. Enter Big Data Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=45 6
  • 7. The Gap Area- Big Data v/s EDW Large data volumes Complex unstructured data Deeper insights Storing images, videos The bottom-line - $/TB Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=45 7
  • 8. Big Data in EDW 8 Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=45
  • 9.
  • 10. Works on massive data sets
  • 11. Support for multiple data sources
  • 14. Canned& customized reports as well as valuable BI
  • 15. Support for real time analyticsRecorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=45 9
  • 16. Building Big Data Analytics Platform 10 Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=45
  • 17. Building Big Data Analytics Platform Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=45
  • 18. Building Big Data Analytics Platform Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=45
  • 19. Building Big Data Analytics Platform
  • 20.
  • 21. Parallel processing or faster mechanisms can be used for import/export of data
  • 22. Real time is a myth in big data – needs careful design
  • 23. Hadoop is the most cost effective option for big data
  • 24. Reuse of existing EDW investments possible Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=45 14
  • 25. Impetus Big Data Analytics Platform- iLaDaP 15 Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=45
  • 26. iLadap- Technologies Used Plug and Play Service Oriented Architecture Workflow and ETL Underlying PB Scale Store BI and Analytics Query Engine Real Time Analytics Application Integration/ Development 16
  • 27.
  • 28. Code – logic and algorithm
  • 33. Development and testing strategyRecorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=45 17
  • 34.
  • 35.
  • 36.
  • 37.
  • 38.
  • 39. Impetus Technologies We offer innovative product engineering and technology R&D services 23 Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=45
  • 40. Questions Please send in your questions using the chat panel 24 Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=45
  • 41. Thank you Mail us at inquiry@impetus.com or visit bigdata.impetus.com Recorded version available at http://www.impetus.com/webinar_registration?event=archived&eid=45