Analytics & Business Intelligence @ center-stage

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Short presentation articulating rationale and endorsement on Analytics and Business Intelligence occupying the center-stage.

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Analytics & Business Intelligence @ center-stage

  1. 1. Analytics & Business Intelligence ~ @ Centre-Stage ~ Shreekant W Shiralkar
  2. 2. • IBM CIO Study: Analytics and BI are Priority for 2012/2013 • Gartner says – Analytics and BI a $ Billion market. • International Data Corporation (IDC) forecasts business analytics market at $ Billion by 2016. Centre-Stage ~ Recognition
  3. 3. Triggers ~ Technology In the period of Knowledge Economy, Pervasive Technology (1) and it’s innovation, position Analytics and BI at the centre- stage. Listed below are some of evidences; – Social Media, Mobility & Wearable Computing, – Internet of things – Big Data – Cloud Computing – Massively Parallel Processing [MPP] (2) – In-memory computing(3) – Complex Event Processing [CEP] (4) – Machine Learning (5) – ……. (1, 2,3,4,5)  Pl. refer definitions in annexure for meaning of these technical terms
  4. 4. Impact ~ Ecosystem Heretofore inconceivable applications coupled with implicit developments, keep Analytics and BI at centre- stage. Listed below are a few; – Research : Meteorology, Genomics, Connectomics(6), …… – Government : example the US Govt announced the Big Data Research and Development Initiative to solve important problems facing the government. – Technology Industry : New Service Paradigm » Data-as-a-service (DaaS) » Analytics-as-a-Service (AaaS) ….. – Academia: Data-informed decision-making (DIDM)skills at leading Universities. (6) Pl. refer definitions in annexure for meaning of this technical term
  5. 5. Note : Data is based on published and available information over internet for the period between 2009 and 2010 Leaders ~ Market
  6. 6. Annexure
  7. 7. Definitions (1) Pervasive Technology = Surrounding, ubiquitous and mobile technology, operating together. (2) Massively parallel processing [MPP] = Use of a large number of processors (or separate computers) to perform a set of coordinated computations in parallel. (3) In-memory computing = storage of information in the main random access memory (RAM) of dedicated servers rather than in complicated relational databases to quickly detect patterns, analyze massive data volumes on the fly, and perform their operations quickly. For example, the in-memory computing technology developed by SAP, called High-Speed Analytical Appliance (HANA). (4) Complex event processing [CEP] = Tracking and analyzing streams of information (data) from multiple sources about things that occur and deriving a conclusion from them. (5) Machine learning = System attempts to eliminate the need for human intervention in data analysis. (6) Connectomics = Application of neural imaging and histological techniques aimed at increasing speed, efficiency, and resolution of maps of the multitude of neural connections in a nervous system such as human brain.
  8. 8. Published Information # 1 Note : Missing out to acknowledge the accurate source of the information on the slide is sincerely regretted.
  9. 9. Published Information # 2 Note : Missing out to acknowledge the accurate source of the information on the slide is sincerely regretted.
  10. 10. Published Information # 3 Note : Missing out to acknowledge the accurate source of the information on the slide is sincerely regretted.
  11. 11. Published Information # 4 Note : Missing out to acknowledge the accurate source of the information on the slide is sincerely regretted.
  12. 12. Thank You Pl. read my books on Supply Chain Analytics & Business Intelligence Queries and feedback to S_Shiralkar@hotmail.com Shreekant W Shiralkar

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