Data Mining in SSAS

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Data Mining in SSAS - What is Data Mining ? Data Mining Process Decision Trees Clustering Time Series Association rules Create New Mining Structure Mining Model Viewer Dependency Network Mining Accuracy Chart Mining Model Prediction Singleton Query

Technology

Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent.
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What is Data Mining ?
• the computational process of discovering patterns in large
data sets involving methods at the intersection of artificial
intelligence, machine learning, statistics, and database
systems.
• The overall goal of the data mining process is to extract
information from a data set and transform it into an
understandable structure for further use.

Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent.
ramkedem.com
Data Mining Process
• Cross-Industry Standard Process for Data Mining (CRISP-DM)
consists of six cyclic phases :
• Business Understanding
• Data Understanding
• Data Preparation
• Modeling
• Evaluation
• Deployment

Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent.
ramkedem.com
Data Mining Algorithms
Covered In This Lesson
• Decision Trees
• Clustering
• Time Series
• Association rules

Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent.
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Decision Trees
• Decision Trees
• a tree-like graph or model of decisions and their possible
consequences, including chance event outcomes, resource costs
• Very common, used for classification.

Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent.
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Clustering
• Clustering
• grouping a set of objects in such a way that objects in the same
group (called a cluster) are more similar (in some sense or
another) to each other than to those in other groups (clusters)
• Widely used in areas of fraud detection

Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent.
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Data Validation Sample
• http://www.sqlserverdatamining.com/ssdm/

Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent.
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Time Series
• Time Series
• A time series is a collection of observations made chronologically,
Used to predict a number of some sort.

Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent.
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Association rules
• Association rules
• Association rules are if/then statements that help uncover
relationships between seemingly unrelated data in a relational
database or other information repository.

Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent.
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Define your Data Source

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Define your DSV

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Create new mining structure
• Right click on Mining Structures and choose New Mining
Structure

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Select the Definition Method

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Create the Mining Structure

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Select Data Source View

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Specify Table Types

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Specify Training Data

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Suggest Related Columns

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Columns Content & Data Types

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Create Testing Set

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Completing the Wizard

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View Mining Model
• Deploy and Process the Mining Model.
• View the Mining Model in Mining Models Tab

Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent.
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Adding Mining Models
• It is possible to add more mining models by right-clicking at
the Mining models area and choosing New Mining Model.
• Deploy and Process once finished.

Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent.
ramkedem.com
Mining Model Viewer

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Dependency Network

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Mining Accuracy Chart - Input

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Lift Chart

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Profit Chart

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Mining Model Prediction

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Query Results View

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Order the Data Differently

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Singleton Query

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Time Series Mining Structure
• Right click on Mining Structures and choose New Mining
Structure

Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent.
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Select Definition Method

Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent.
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Create the Data Mining
Structure

Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent.
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Select DSV

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Specify Columns Content and
Data Types

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Data Mining in SSAS

1. Data Mining In SSAS Ram Kedem

2. Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent. ramkedem.com What is Data Mining ? • the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. • The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use.

3. Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent. ramkedem.com Data Mining Process • Cross-Industry Standard Process for Data Mining (CRISP-DM) consists of six cyclic phases : • Business Understanding • Data Understanding • Data Preparation • Modeling • Evaluation • Deployment

4. Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent. ramkedem.com Data Mining Algorithms Covered In This Lesson • Decision Trees • Clustering • Time Series • Association rules

5. Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent. ramkedem.com Decision Trees • Decision Trees • a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs • Very common, used for classification.

6. Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent. ramkedem.com Clustering • Clustering • grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense or another) to each other than to those in other groups (clusters) • Widely used in areas of fraud detection

9. Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent. ramkedem.com Time Series • Time Series • A time series is a collection of observations made chronologically, Used to predict a number of some sort.

10. Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent. ramkedem.com Association rules • Association rules • Association rules are if/then statements that help uncover relationships between seemingly unrelated data in a relational database or other information repository.

11. Create New Mining Structure

14. Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent. ramkedem.com Create new mining structure • Right click on Mining Structures and choose New Mining Structure

24. Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent. ramkedem.com View Mining Model • Deploy and Process the Mining Model. • View the Mining Model in Mining Models Tab

25. Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent. ramkedem.com Adding Mining Models • It is possible to add more mining models by right-clicking at the Mining models area and choosing New Mining Model. • Deploy and Process once finished.

38. Time Series Mining Structure

39. Copyright 2014 © Ram Kedem. All rights reserved. Not to be reproduced without written consent. ramkedem.com Time Series Mining Structure • Right click on Mining Structures and choose New Mining Structure

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