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Introduction to Data Mining, Business Intelligence and Data Science

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Presentation by Dr. Jirapun Dandej for the Big Data Certification Course @ IMC Institute in March 2015

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Introduction to Data Mining, Business Intelligence and Data Science

  1. 1. Asst. Prof. Dr. Jirapun Daengdej Faculty of Science and Technology Assumption University jirapun@scitech.au.edu 1
  2. 2. 2 http://www.greenbookblog.org/2013/05/16/are-you-burning-away-your-data-fuel/
  3. 3. 3 The problem is…..
  4. 4.   Background  Your Expectations & Pain Points?  What is “Data Mining”?  What is “Business Intelligence”?  What is “Data Science”?  Real-World Cases Contents 4
  5. 5.  Background 5
  6. 6.  Background 6
  7. 7.  Background 7
  8. 8.  Background 8
  9. 9.  Background 9
  10. 10.  What about “Data Game”? 10
  11. 11. 11 Figures don't lie, the old saying, but liars can figure. Put another way, even accurate and honest-in-itself data can be presented in misleading ways to support a less-than-honest result. To protect against data- rich lies, we must learn to understand the limitations of data and how it can be used - even inadvertently - to mislead. http://www.grtcorp.com/content/data-may-not-lie-liars-can
  12. 12.  Your Expectations & Pain Points? 12
  13. 13.  YOUR Expectation(s) and Pain Points? 13
  14. 14.  What is “Data Mining”? 14
  15. 15.  Definition 15 Data mining is the application of specific algorithms for extracting patterns from data. The distinction between the KDD process and the data-mining step (within the process) is a central point…
  16. 16.  "Data mining" was introduced in the 1990s, but data mining is the evolution of a field with a long history. History http://www.unc.edu/~xluan/258/datamining.html Data mining roots are traced back along three family lines: • classical statistics, • artificial intelligence, • and machine learning. 16
  17. 17.  Data Mining & Stats? 17
  18. 18.  What is “Business Intelligence”? 18
  19. 19.  Business intelligence (BI) is an umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance. 19 Definitions
  20. 20.  BI 1.0 - 2.0 - 3.0 20 http://smartdatacollective.com/yellowfin/195811/defining-business-intelligence-30
  21. 21.  What Business want from BI? 21 Buyers Overwhelmingly Want Better Data Visualization http://www.softwareadvice.com/bi/buyerview/report-2014/
  22. 22.  What is “Data Science”? 22
  23. 23. 23 http://www.datasciencecentral.com/profiles/blogs/17-analytic-disciplines-compared http://www.quora.com/What-is-the-difference-between-Data-Analytics-Data-Analysis-Data-Mining-Data-Science-Machine-Learning-and-Big-Data-1 http://www.kdnuggets.com/2013/10/7-steps-learning-data-mining-data-science.html
  24. 24.  Definition? 24
  25. 25.  Related Qualification? 25 http://www.becomingadatascientist.com/2014/06/13/doing-data-science-review/
  26. 26.  Data Science vs. Data Analytics 26 http://datascientistinsights.com/2013/09/09/data-analytics-vs-data-science-two-separate-but-interconnected-disciplines/
  27. 27.  Relationship between them? 27
  28. 28.  What do you think? 28
  29. 29.  Real-World Cases 29
  30. 30.  Real-World Cases 30 2005….Yahoo!'s users, through their use of our network of products, generate over 10 terabytes of data per day. This is the equivalent of the entire text contents of the library of Congress. This is data that describes product usage, and does not include content, email, or images, etc. http://www.kdd.org/newsletter/explorations-october-2005
  31. 31.  From Yahoo! To DigiMine 31
  32. 32.  1. Understanding and Targeting Customers 2. Understanding and Optimizing Business Processes 3. Personal Quantification and Performance Optimization 4. Improving Healthcare and Public Health 5. Improving Sports Performance 6. Improving Science and Research 7. Optimizing Machine and Device Performance 8. Improving Security and Law Enforcement. 9. Improving and Optimizing Cities and Countries 10. Financial Trading 32 The Awesome Ways Big Data Is Used Today To Change Our World http://www.datasciencecentral.com/profiles/blogs/the-awesome-ways-big-data-is-used-today-to-change-our-world
  33. 33.  Q & A 33

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