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Analytical processing of data
Analytical processing of data
Analytical processing of data
Analytical processing of data
Analytical processing of data
Analytical processing of data
Analytical processing of data
Analytical processing of data
Analytical processing of data
Analytical processing of data
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Analytical processing of data

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  • 1. Analytical Processing of Data Prasad Chitta
  • 2. Agenda or TOC • The Analytical • Data , where there is no data to analyse to where we have too much of data to analyse • “ ” used till date for this • we have a single structure for OLTP and Analytics? • The ‘data’ of data • Data
  • 3. Analytical Processing of Data Operational Reporting / MI Analytics OLAP / BI / ETL Descriptive (Uni or bivariate) Analytics Diagnostic or Inquisitive Content (Unstructured) Discovery Predictive Structured Predictive Statistical Techniques Machine Learning
  • 4. Data Scenarios… • New product design • Simulation • Knowledge representation No Data Structured Data • From normalized OLTP systems • Variables , mostly numbers • Unstructured • Quickly varying • Mostly non-numeric BIG data
  • 5. Data analysis technology “names” • Adhoc Data & Queries • Management Information , Business Intelligence • Business Analytics • Real-Time BI • Artificial Analytics • In-memory
  • 6. Why can’t we analyze OLTP data • • • • OLTP schema Optimized for handling transactions i.e., updates Short and quick transaction are catered Multiple concurrent users read small amounts of data Key based, index lookups used to access data • • • • OLAP schema Optimized for large loads of data in ETL mode Large summarizations to be performed Less number of users read huge amounts of data Full scans through data are often required
  • 7. The Data lifecycle Sensing ETL, Warehousing OLAP reporting Acquiring, Validating Operational Reporting, Dashboarding Analytics Storing Transactional Update Archiving, Purging
  • 8. Aspects of ‘Data’ Integration, Migration Reference Data Master Data Meta data Data Quality Visualization
  • 9. Business Value Business Value - Analytics Matrix What is the best that can happen? What will happen? Optimization Linear/Non-linear programming & Simulations Predictive Modeling Baseline Demand Impact of Causal Factors Descriptive Modeling Why something happened? Describe historical event Insights/Limited What-if A n a l y t i c s Actionable insights What happened? R T B I OLAP Reporting Drill-thru Drill-Across Standard Reporting Sales, Inventory, Business Performance Data Management Internal, Syndicated, Decision Support DSS Decision Guidance  Advanced analytics DSS – Decision Support Systems, RTBI – Real Time Business Intelligence 9
  • 10. http://www.linkedin.com/in/prasadchitta

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