1. TechEd 2013
11/28/ :48 AM
© 2013 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

2. 11/28/ :48 AM
DBI-B340
Taking Your Application Design to the Next Level by Using SQL Server 2012 Data Mining
Peter Myers
Bitwise Solutions Pty Ltd
© 2013 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

3. Presenter Introduction
Peter Myers
BI Expert – Bitwise Solutions
BBus, SQL Server MCSE, MCT, SQL Server MVP
Experienced in designing, developing and maintaining Microsoft database and application solutions, since 1997
Focuses on education and mentoring
Based in Melbourne, Australia

4. Session Objectives Introduce data mining and data mining processes
Introduce SQL Server data mining
Introduce and describe the SQL Server data mining algorithms
Demonstrate how data mining can be used to enrich .NET application experiences

5. Session Outline Introducing Data Mining
Describing the Data Mining Process
Introducing SQL Server Data Mining
Demonstrations
Message for Developers

6. Introducing Data Mining
Addresses the problem: “Too much data and not enough information”
Enables data exploration, pattern discovery, and pattern prediction – which lead to knowledge discovery
Forms a key part of a Business Intelligence solution

7. Introducing Data Mining Data Mining Enabled Predictive Analysis
TechEd 2013
11/28/ :48 AM
Introducing Data Mining Data Mining Enabled Predictive Analysis
Role of Software
Predictive Analysis
Data Mining
Proactive
Interactive
Data Model
Ad hoc Reporting
Canned Reporting
Passive
Business Insight
Presentation
Exploration
Discovery
© 2013 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

8. Introducing Data Mining Data Mining Enabled Predictive Analysis
TechEd 2013
11/28/ :48 AM
Introducing Data Mining Data Mining Enabled Predictive Analysis
Data Mining
Seek Profitable Customers
Understand Customer Needs
Anticipate Customer Churn
Predict Sales and Inventory
Build Effective Marketing Campaigns
Detect and Prevent Fraud
Correct Data During ETL
© 2013 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

9. Introducing Data Mining Describing the Data Mining Process
TechEd 2013
11/28/ :48 AM
Introducing Data Mining Describing the Data Mining Process
“Doing Data Mining”
Business Understanding
Data Understanding
Data Preparation
Data
“Putting Data Mining to Work”
Deployment
Modeling
Evaluation
© 2013 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

10. Data Preparation
Often significant amounts of effort are required to prepare data for data mining
Transforming for cleaning and reformatting
Isolating and flagging abnormal data
Appropriately substituting missing values
Discretizing continuous values into ranges
Normalizing values between 0 and 1
Of course, having the required data to begin with is important
When designing systems, give consideration to attributes that may be required as inputs for classification
For example, demographic data: Age, Gender, Region, etc.

11. Data Mining Modeling
Design time
Process time
Query time
Mining Model

12. Data Mining Modeling Design time Process time Query time Mining Model
Data Mining Engine
Training Data

13. Data Mining Modeling Design time Process time Query time Mining Model
Data Mining Engine
Predicted Data
Data to Predict

14. Introducing Analysis Services 2012
Data Models
Also named BI Semantic Models (BISMs)
Developed by using tabular or multidimensional development approaches
Deliver intuitive browsing and high performance query results
Perform calculations difficult to perform by using relational queries
Support advanced Business Intelligence, including KPIs
Data Mining
Discovers patterns in data
Patterns can be used to surface knowledge about data, and may be used for predictive analytics

15. Introduction to SQL Server Data Mining
Hides the complexity of an advanced technology
Includes a full suite of algorithms to automatically detect and store patterns found in your data:
Can handle large volumes of data, and complex data
Data can be sourced from relational and BISM data sources
Uses standard programming interfaces:
XMLA
DMX
Delivers a complete framework for building and deploying intelligent applications

16. SQL Server Data Mining Algorithms
Microsoft Naïve Bayes
Quick and approachable algorithm
Used for classification
Microsoft Decision Trees
Popular data mining technique
Used for classification, regression and association
Microsoft Linear Regression
Finds the best possible straight line through a series of points
Used for prediction analysis

17. SQL Server Data Mining Algorithms Continued
Microsoft Neural Network
More sophisticated than Decision Trees and Naïve Bayes, this algorithm can explore extremely complex scenarios
Used for classification and regression tasks
Microsoft Logistic Regression
A particular case of the Neural Network algorithm
Microsoft Clustering
Finds natural groupings inside data
Supports segmentation and anomaly detection tasks

18. SQL Server Data Mining Algorithms Continued
Microsoft Sequence Clustering
Groups a sequence of discrete events into natural groups based on similarity
Microsoft Time Series
Used to predict future values from a time series
Was improved in SQL Server 2008 to produce more accurate longer term forecasts
Microsoft Association Rules
Commonly used for market basket analysis to learn what products are purchased together

19. SQL Server Data Mining Algorithms Continued
Classify
Decision Trees
Logistic Regression
Naïve Bayes
Neural Networks
Estimate
Linear Regression
Cluster
Clustering
Forecast
Time Series
Associate
Association Rules

20. SQL Server Data Mining Visualizations
In contrast to OLTP and analytic queries, data mining queries typically extract information that the user is not aware of
End users do not typically query data mining models directly
Visualizations can effectively present data discoveries
SQL Server provides algorithm-specific visualizations that can:
Test and explore models in SSDT and SSMS
Be embedded into Windows Forms applications
Developers can construct and plug-in custom data mining viewers

21. SQL Server Data Mining Programmability
C++ App
VB App
.NET App
Any App
OLE DB
ADO
ADO.NET
AMO
Any Platform, Any Device
WAN
XMLA
Over TCP/IP
XMLA
Over HTTP
Analysis Server
OLAP
Data Mining
Server ADOMD.NET
Data Mining Interfaces
.NET Stored Procedures
Microsoft Algorithms
Third-Party Algorithms

22. Demonstrations Peter Myers Bitwise Solutions Pty Ltd
Creating, training, testing data mining models with Visual Studio 2012
Embedding a data mining visualization into a Windows Forms application
Authoring a Reporting Services report based on a data mining model, and embedding the report into a Windows Forms application
Automating data validation with data mining in a Windows Forms application
Enhancing an E-commerce Asp.NET Web application with market basket analysis
Peter Myers
Bitwise Solutions Pty Ltd

23. Message for Developers
Take your application to the next level by embedding data mining results, including prediction results!
Embed custom visualizations into Windows Forms applications to allow users to explore and understand the discovered model patterns
Integrate predictions:
Targeted advertising
“Those that bought this book also purchased these books”
Help validate or repair user entry

24. Related content Breakout Sessions
11/28/ :48 AM
Related content
Breakout Sessions
DBI-B403: Fraud Detection: Notes from the Field [Fri 4:30PM]
© 2013 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

25. Resources Learning TechNet msdn http://channel9.msdn.com/Events/TechEd
11/28/ :48 AM
Resources
Learning
Sessions on Demand
Microsoft Certification & Training Resources
TechNet
msdn
Resources for IT Professionals
Resources for Developers
© 2013 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

26. Evaluate this session Scan this QR code to evaluate this session.
11/28/ :48 AM
Required Slide
*delete this box when your slide is finalized
Your MS Tag will be inserted here during the final scrub.
Evaluate this session
Scan this QR code to
evaluate this session.
© 2013 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

27. 11/28/ :48 AM
© 2013 Microsoft Corporation. All rights reserved. Microsoft, Windows and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.
The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.
© 2013 Microsoft Corporation. All rights reserved. Microsoft, Windows, and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.