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Chapter 2 - Video # 10

What is Data Mining?

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Chapter 2: Business Intelligence & Data Warehousing with SSASCourse: SQL Server 2008/R2 Analysis ServicesCourse Id: 165Presented by Scott Whigham

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• The ability to do data mining is a major attraction of MDBs– SSAS can be considered a “multidimensional OLAP

and data mining server”

* Graphic: MSDN

Data Mining

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• Data mining is the practice of digging through lots of data to find patterns– Given 100,000,000 rows covering more than 30

years, can you spot the trends?

• “100,000,000 rows?!?! Gah!!!!!”

Data Mining

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• With data mining, you are hoping to find trends and patterns that would have otherwise gone unnoticed– Due to the sheer volume of data:

• Trends cannot be visually identified

• Hundreds of data points collected about a single entity

• Intricate relationships between entities

• Manual analysis can only go so far

Data Mining

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• Asking questions and reviewing the answers is a great way to perform analysis– To put it another way: “Writing queries and

reviewing the result sets is a great way to perform analysis”

Data Mining

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• Manual data analysis is knowing the question and reviewing the answer– “How many tickets did our customer service team

close over the last three years?”

Data Mining

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• Data mining does not require strict questions– Data mining can provide you with answers to

questions you should have asked

Data Mining

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• Data mining often starts with an attempt to find “known unknowns”– “What are the not-so-obvious attributes of people

who are a bad credit risk?”

Data Mining

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• We are looking for the key influencers– “If we could identify these common attributes, we

could stop/start marketing to this group”

Data Mining

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• Data mining can even use these key influencers to predict the future– Sales forecasting is a common scenario

• By reviewing the past 5 years of data, SSAS’ data mining algorithm(s) can predict future sales

Data Mining

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• Analysis Services features Data Mining as a core task– We will cover Data Mining exclusively in Chapter

11

Data Mining

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• But first! I must trim my waist, tummy, hips and thighs…

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