- So why the essential elements of data mining?…What's in a name?…Why data mining?…There is a lot of competition among words…for indicating the concept of finding meaningful…and valuable patterns in data.…Predictive analytics, data science, and big data…are all popular at the moment.…It's an endless debate and never seems to come to closure.…My choice is simple…I use the term data mining…because I use the cross industries standard process…for data mining.…
Which we will discuss in the final section of the course.…It's considered the defact of a standard.…So since it uses the term data mining…so do I.…The essential elements are my attempt…to clarify what data mining is…and what it isn't.…I'm not seeking the platonic form of data mining.…I just want to help give some clarity…where it is often lacking.…There is much confusion surrounding how data mining…is distinct from related areas like statistics…and business intelligence.…
My goal is to clarify the characteristics…of a true data mining project.…By implication, statistical analysis,…
Author
Released
7/10/2017- What makes a successful predictive analytics project?
- Defining the problem
- Selecting the data
- Acquiring resources: team, budget, and SMEs
- Dealing with missing data
- Finding the solution
- Putting the solution to work
- Overview of CRISP-DM
Skill Level Intermediate
Duration
Views
Related Courses
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Predictive Customer Analytics
with Kumaran Ponnambalam1h 37m Intermediate
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Introduction
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Welcome1m 54s
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1. What Is Data Mining and Predictive Analytics?
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Introduction17s
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2. Problem Definition
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Introduction48s
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Program management1m 47s
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3. Data Requirements
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Introduction1m 9s
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Customer footprint1m 18s
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Flat file1m 10s
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Understand your target1m 42s
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Select the data for modeling2m 41s
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Understand integration2m 35s
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Understand data construction3m 47s
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4. Resources You'll Need
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Introduction36s
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Assess team requirements3m 46s
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Budget time1m 40s
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5. Problems You'll Face
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Introduction46s
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Deal with missing data2m 26s
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Why models degrade3m 28s
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6. Finding the Solution
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Introduction1m 5s
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Search the solution space2m 30s
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Unexpected results1m 59s
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Trial and error1m 40s
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Construct proof2m 16s
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7. Putting the Solution to Work
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Introduction48s
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Understand propensity1m 56s
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Understand metamodeling3m 6s
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Understand reproducibility1m 56s
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Master documentation2m 7s
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Time to deploy1m 17s
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8. CRISP-DM and the Nine Laws
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Introduction49s
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Understanding CRISP-DM1m 48s
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Understand laws 1 and 21m 48s
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Understand law 33m 20s
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Understand laws 4 and 53m 9s
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Understand laws 6, 7, and 84m 34s
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Understand law 91m 29s
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Conclusion
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Next steps1m 13s
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Video: What are the essential elements?