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Big Data Analytics Platform- Beyond Traditional EDW
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Big Data Analytics Platform- Beyond Traditional EDW


Recorded version available at …

Recorded version available at

Impetus Webinar on 'Big Data Analytics Platform: Beyond Enterprise DW'

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  • 1. Big Data Analytics PlatformBeyond Traditional Enterprise Data Warehouse
    Recorded version available at
  • 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
  • 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
  • 4. Traditional EDW
    Recorded version available at
  • 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
    Automated Analysis - Data Mining
    Machine learning / NLP
    Recommendations & forecasting
    Recorded version available at
  • 6. Enter Big Data
    Recorded version available at
  • 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
  • 8. Big Data in EDW
    Recorded version available at
  • 9. Key Characteristics - Big Data Platform
    • Highly scalable
    • 10. Works on massive data sets
    • 11. Support for multiple data sources
    • 12. Easy deployment/ seamless integration
    • 13. Deep analytics
    • 14. Canned& customized reports as well as valuable BI
    • 15. Support for real time analytics
    Recorded version available at
  • 16. Building Big Data Analytics Platform
    Recorded version available at
  • 17. Building Big Data Analytics Platform
    Recorded version available at
  • 18. Building Big Data Analytics Platform
    Recorded version available at
  • 19. Building Big Data Analytics Platform
  • 20. Our Key Learnings
    • Open source yields better results for larger volumes of data
    • 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
  • 25. Impetus Big Data Analytics Platform- iLaDaP
    Recorded version available at
  • 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
  • 27. Reusing EDW Investments
    • Infrastructure
    • 28. Code – logic and algorithm
    • 29. Traditional data warehouse
    • 30. RDBMS engine
    • 31. Reporting tools
    • 32. ETL tools
    • 33. Development and testing strategy
    Recorded version available at
  • 34. Case Study - 1
    The Client
    Leaders in internet services and media in Europe
    Key Challenge
    Very high volumes of data recorded each month
    Near real time reporting engine needed
    How much infrastructure needed?
    Impetus Solution
    Proposed Cloud for POC
    Usage of Flume for collecting streaming data
    Usage of Hbase/Hive for analysis
    Benefits Realised
    • Highly scalable
    • 35. Near real time analytics
  • Web Analytics
  • 36. Case Study - 2
    The Client
    One of the key players in Telecom industry
    Key Challenge
    CDR Data Conversion
    Customer churn analysis
    Impetus Solution
    Workflow based CDR data conversion
    Canned reports for CDR data
    Used Intellicus to generate customer churn analysis reports
    Benefits Realised
    • Predefined canned reports for customer churn analysis
    • 37. Better customer management
  • Case Study - 3
    The Client
    Leading online product retailer
    Key Challenge
    Recommendation engine
    Cross product customer analysis
    Provide ‘Big Picture’ across business units
    Impetus Solution
    Proposed iLaDaP based solution
    Apache Mahout based recommendation engine
    Clickstream, Server log and OLTP cross analysis
    Benefits Realised
    • Better product recommendations
    • 38. True centralized business overview across product and business lines
  • Summing up…
    Big Data Analytics needs a well-thought of strategy
    Any single vendor technology may not be sufficient to build a Big Data Analytics Platform
    Hybrid solutions are effective due to their flexible cost model
    Selecting the right tools is the key to build a successful Big Data Analytics Platform
    Easy extension of the existing EDW infrastructure possible
    Recorded version available at
  • 39. Impetus Technologies
    We offer innovative product engineering
    and technology R&D services
    Recorded version available at
  • 40. Questions
    Please send in your questions using the chat panel
    Recorded version available at
  • 41. Thank you
    Mail us at
    or visit
    Recorded version available at