Carlo Colicchio: Big Data for business
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Carlo Colicchio: Big Data for business

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Project by Carlo Colicchio

Project by Carlo Colicchio
Course "Innovation and New Technologies" - University of Camerino
(teacher C. Vaccari)

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Carlo Colicchio: Big Data for business Presentation Transcript

  • 1. AN INSIGHT INTO… Innovation and New Technologies Lecturer: Prof. Carlo Vaccari AS 2013 04.02.2014 Author: Carlo Colicchio
  • 2. Agenda Big Data in Facts Chances and Challenges of Big Data The Business Value of Big Data The Big Data Landscape Case 2
  • 3. Big Data is emerging from several new Technologies... Source: Experton Group 2012 } The Mobile Use of the Internet and Cloud Computing are the most important drivers for BIG DATA increase 85% unstructured data, with valuable content which can be analysed Source: TechAmerica Foundation, 2013 Big Data in Facts 3
  • 4. Source: Credit Suisse - Global Investor Report. 2013 Big Data in Facts 4
  • 5. ...which enhance the data growth ... The Growth of Data is rapid and unstoppable. Big Data will affect enterprises from all kind of branches. Zettabyte is the unit of measure which follows after Terabyte, Petabyte and Exabyte. Source: IDC Universe Study, 2010 Big Data in Facts 5
  • 6. ...and it is characterised the 3 V‘s. Volume •  Large amount of data sets, files and measurement data from new sources Variety •  Processing of internal/ external data •  Un-/ and structured data (Video, Images, Tweets etc.) Velocity Analytics Viability, Veracity •  Data generation and analysis with high velocity •  Data transfer in real-time (Miliseconds) Source: Hoge, 2012, IBM Deutschland •  Identification of correlations, meanings, patterns (Data- and Text Mining, Real-Time, Visualisation) Big Data in Facts 6
  • 7. Business Intelligence is moving on due to three market trends. Traditional Reporting Big Data Real Time Predictive Source: Forrester, The Business Intelligence Growth Opportunity, 2011 Big Data in Facts 7
  • 8. Big Data creates new Chances for Enterprises to improve their Market Position... Time-tomarket Process optimization Customer Insights Reduced Systeminfra -structure Business Models Reasonable decisions Compliance Big Data Strategy Source: BITKOM, 2012 Chances and Challenges of Big Data 8
  • 9. ... but also Challenges have to be faced. Dataloss Total Cost of Ownership Data Interpretation/ Validation Transparancy Basis for decisions IT-Security / Fraud Source: BITKOM, 2012 Chances and Challenges of Big Data 9
  • 10. Big Data generates significant financial value across various sectors... Retail (Marketing & Sales) - Accurate Market and Competition Analysis - Revenue increase and cost reduction Health Care - Improved cost efficiency due to better patient analysis and resp. more accurate diagnosis Manufacturing, Services and Support - Production optimization with sensor data - Early identification of production problems Finance and Risk Controlling - Fraud and Manipulation recognition - Real time risk controlling Source: McKinsey Global Institute, 2011 / BITKOM, 2012 The Business Value of Big Data 10
  • 11. ...and is also perceived as a valueable discipline to enhance Business. How valuable would it be/is it to your business? How would an application of Big Data be most useful? Source: AIIM, BIG DATA, 2012 Enterprises rate Big Data as very valuable and would like to enhance their competitve position, avoid business discontinuity, or detect noncompliance. The Business Value of Big Data 11
  • 12. Within the „BIG DATA“ domain several entities are involved. Ø  Ø  Ø  Ø  Ø  Ø  Infrastructure Analytics Applications Data Sources Cross Infrastructure / Analytics Open Source Projects The Big Data Landscape 12
  • 13. Within the „BIG DATA“ domain several entities are involved. The Big Data Landscape 13
  • 14. IBM developed „WATSON“, a system which makes use of Big Data. Ø  Ø  Ø  Ø  Ø  Ø  Uses the english World Wide Web locally Corresponds to 10km printed books About 200 Mio. book pages therefrom only 2.25 Mio. from Wikipedia Needs about 2000 Years time to read Watson combines: §  natural language processing, hypothesis generation and evaluation to give direct confidence-based responses Watson can be applied now in various sectors like healthcare and finance Trailers: Watson: A system designed for Answers, The Science Behind Watson, Perspectives on Watson: Finance Case 14
  • 15. Thank you for your attention! End 15
  • 16. References Ø  Ø  BITKOM, 2012. Big Data im Praxiseinsatz - Szenarien, Beispiele, Effekte. Das, Nilanjan & Neumann, Uwe. 2013. Big Data - Digitaler Quantensprung. Credit Suisse – Global Investor Report Ø  Hoge, Wilfried, 2012. Big Value from Big Data. IBM Deutschland Ø  Keil, Thomas, 2012. Big Data und High Performance Analytics. SAS Institute GmbH Ø  Ø  Ø  McKinsey Global Institute, 2011. Big data: The next frontier for innovation, competition and productivity. Miles, Doug, 2012. Big Data - extracting value from your digital landfills. AIIM TechAmerica Foundation, 2013. Demystifying Big Data: A Practical Guide To Transforming The Business of Government. 16