This document discusses data mining using SQL Server. It outlines different data mining algorithms and their purposes, such as using decision trees to predict discrete or continuous attributes, and clustering algorithms to find groups of similar items. It also mentions demo examples on forecasting sales and analyzing Facebook and Ülker customer data. The document promotes the #sqlsatistanbul conference and provides contact information for the speaker.

1. Data Mining using SQL Server
Koray Kocabas
@koraykocabas
tr.linkedin.com/koraykocabas

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Sponsors
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Statistics are like mini-skirts,
shows a lot of things
but does not show what is essentially.
Sir Alex Ferguson

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Is Data New Oil?

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Data Mining
Purpose Solution
Predicting a discrete attribute Decision Trees Algorithm
Naive Bayes Algorithm
Clustering Algorithm
Neural Network Algorithm
Predicting a continuous attribute Decision Trees Algorithm
Time Series Algorithm
Linear Regression Algorithm
Predicting a sequence Sequence Clustering Algorithm
Finding groups of common items in transactions Association Algorithm
Decision Trees Algorithm
Finding groups of similar items Clustering Algorithm
Sequence Clustering Algorithm

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Demo (Facebook,Ülker)

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Forecast Sales

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Demo
 Forecast Sales Amount & Quantity

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Sponsors
Main
Gold
Bronze
Media
Swag

19. For more Information
#sqlsatistanbul
@koraykocabas
tr.linkedin.com/koraykocabas