introduction to data mining, business intelligence and data science
TRANSCRIPT
![Page 1: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/1.jpg)
Asst. Prof. Dr. Jirapun Daengdej
Faculty of Science and Technology
Assumption University
1
![Page 2: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/2.jpg)
2 http://www.greenbookblog.org/2013/05/16/are-you-burning-away-your-data-fuel/
![Page 3: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/3.jpg)
3
The problem is…..
![Page 4: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/4.jpg)
Background
Your Expectations & Pain Points?
What is “Data Mining”?
What is “Business Intelligence”?
What is “Data Science”?
Real-World Cases
Contents
4
![Page 5: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/5.jpg)
Background
5
![Page 6: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/6.jpg)
Background
6
![Page 7: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/7.jpg)
Background
7
![Page 8: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/8.jpg)
Background
8
![Page 9: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/9.jpg)
Background
9
![Page 10: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/10.jpg)
What about “Data Game”?
10
![Page 11: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/11.jpg)
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
![Page 12: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/12.jpg)
Your Expectations & Pain Points?
12
![Page 13: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/13.jpg)
YOUR Expectation(s) and Pain Points?
13
![Page 14: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/14.jpg)
What is “Data Mining”?
14
![Page 15: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/15.jpg)
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…
![Page 16: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/16.jpg)
"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
![Page 17: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/17.jpg)
Data Mining & Stats?
17
![Page 18: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/18.jpg)
What is “Business Intelligence”?
18
![Page 19: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/19.jpg)
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
![Page 20: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/20.jpg)
BI 1.0 - 2.0 - 3.0
20
http://smartdatacollective.com/yellowfin/195811/defining-business-intelligence-30
![Page 21: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/21.jpg)
What Business want from BI?
21
Buyers Overwhelmingly Want Better Data Visualization
http://www.softwareadvice.com/bi/buyerview/report-2014/
![Page 22: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/22.jpg)
What is “Data Science”?
22
![Page 23: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/23.jpg)
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
![Page 24: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/24.jpg)
Definition?
24
![Page 25: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/25.jpg)
Related Qualification?
25
http://www.becomingadatascientist.com/2014/06/13/doing-data-science-review/
![Page 26: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/26.jpg)
Data Science vs. Data Analytics
26
http://datascientistinsights.com/2013/09/09/data-analytics-vs-data-science-two-separate-but-interconnected-disciplines/
![Page 27: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/27.jpg)
Relationship between them?
27
![Page 28: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/28.jpg)
What do you think?
28
![Page 29: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/29.jpg)
Real-World Cases
29
![Page 30: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/30.jpg)
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
![Page 31: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/31.jpg)
From Yahoo! To DigiMine
31
![Page 32: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/32.jpg)
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
![Page 33: Introduction to Data Mining, Business Intelligence and Data Science](https://reader034.vdocuments.mx/reader034/viewer/2022042518/55a5dd5a1a28ab8d558b4584/html5/thumbnails/33.jpg)
Q & A
33