1. Microsoft Predictive Analytics
Carl Speshock, MBA
Catapult Systems
Houston BI/DM Local Practice Lead
Managing Consultant

2. Why Predictive Analytics?
Agenda
Introduction
Why Predictive Analytics?
Microsoft’s Offering
Discussion

3. Introduction

4. Carl Speshock, MBA Catapult Systems BI/DM Practice Lead Managing
Over 32 years in IT/Computer Engineering/Defense Industry
2 years as Full-Time Employee (FTE) of Intel Corporation
Over 22 years with Microsoft SQL Server/BI Solutions
Roles: DBA, BI/DM Developer, Lead, Engineer, BI Architect, etc.
BI/DM
Practice Lead
Over 18 years as a resident of Houston
Author of two IT books and multiple articles
Managing
Consultant
8 years as Full-Time Employee (FTE) of Microsoft Consulting Services
BA, BS, MBA and Phd education

5. Why Predictive Analytics (PA)?

6. Before Why: What is Predictive Analytics(PA)?
Historical/External
data + algorithms
Descriptive analytics: answers the questions what happened and why did it happen via mining historical data
Predictive analytics: answers the question what will happen.
This is when historical performance data is combined with rules, algorithms, and occasionally external data to determine the probable future outcome of an event or the likelihood of a situation occurring.
Prescriptive analytics not only anticipates what will happen and when it will happen, but also why it will happen
suggests decision options on how to take advantage of a future opportunity or mitigate a future risk and shows the implication of each decision option
Prescriptive analytics ingests hybrid data, a combination of structured (numbers, categories) and unstructured data (videos, images, sounds, texts), and business rules to predict what lies ahead and to prescribe how to take advantage of this predicted future without compromising other priorities. Prescriptive analytics automatically synthesizes big data, multiple disciplines of mathematical sciences and computational sciences, and business rules, to make predictions and then suggests decision options to take advantage of the predictions.
What will happen?

7. PA as a Solution: Business Pain Points
Why no Predictive Analytics (PA) currently utilized?
No Tools
Business Culture/
Maturity Model
No Dashboards
Deployment Time
Not Trained
Executive
Sponsorship
Existing Environment
Funding

8. PA Solution Priority: Why Now?
Powerful Data-Related
Compete Tool
Data-Driven
Organization
Industry/Business Domain-wide Value/ROI
Compete Urgency
Predictive business performance metrics will increase adopters’ profitability 20% by 2017 (Gartner)

9. PA Solution Priority: Data is Changing
MGXFY13
4/13/2018
PA Solution Priority: Data is Changing
Consumerization of IT
10x increase every five years
85% from new data types
Data explosion
4.3 connected devices per adult
27%
using social media input
“By 2015, organizations integrating high-value, diverse, new information types and sources into a coherent information management infrastructure will outperform their industry peers financially by more than 20%.”
– Gartner, Regina Casonato et al., “Information Management in the 21st Century”
© 2012 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. Microsoft PA Solution Viability
Offerings in Place
End-to-End Solution
On-Premise, Cloud, or Hybrid
Integration with Environment

11. PA Solution Viability: On-Premise and Cloud
Traditional
NON-VIRTUALIZED
Private
CLOUD: On-premises Cloud
Public
CLOUD: Off-premises Cloud
On-Premise Physical Servers
Windows Server 2012
SharePoint/Office 2013
SQL Server 2012/2014
SQL Server PDW
HDP 2.0 for Windows Server 2012
Virtualization/ Virtual Machines
Windows Server 2012 Hyper-V
SharePoint/Office 2013
SQL Server 2012/2014
Windows Azure
SharePoint Online
O365 Power BI: Power-View Predictive Analytics (In Preview)
Azure HDInsight
VHDs: SharePoint 2013/Office 2013/SQL Server 2012/2014 Hosted VHDs
Hybrid Cloud
Portions of applications and data on-premises and off-premises

12. PA Solution Opportunity Overview
Social Mining
Risk Prediction
Multi-Domain
Versatile
Multi-Device
Customer Sentiment
Fraud Detection
Multi-Product
Multi-Levels
Discover
Analyze
Visualize
Predict
Share
Find
Mobile
Familiar Tools | On Premise/Cloud | Strategic

13. PA Solution Use Cases Data Mining Text Mining Web Analytics
Multi-Domain

14. PA Solution: Industry Support
CIO Magazine 2013 State of the CIO Survey Results

15. PA Vendors - Competitive Space
Gartner Report
Generalist
Open-Source
Specialist
Veterans/
New Comers
Desktop/Cloud
Expensive/Free
Fast-Movers

16. Microsoft Predictive Analytical Tools
Predictive Analytics w/Big Data

17. Big Data/Predictive Analytics – Overview
Sources
Models
Target

19. Big Data Terabytes/Petabytes: unstructured/structured
Windows Azure - HDInsight
Terabytes/Petabytes: unstructured/structured
Public Cloud: HDInsight for Azure
On-premise: SQL Server PDW and HDP 2.0 for Windows
Large Data Sets: In-Memory Engine
Fast Load and Query Times
Excel 2013 Power Query/PowerPivot/ Power View/Power Map Self-Service
Polybase - TSQL
Appliance of Racks

20. Near Real-Time Streaming Data
Sources
Engine
SQL Server 2012 – StreamInsight or Parallel Data Warehouse (PDW)
Target

21. Excel- Predictive Analytics/Data Mining
Desktop (Excel Add-in 32/64-bit) with server-side SQL Server Analysis Services Engine
Big Data Sets to Increase Accuracy of Models
Choices of DM Algorithms
Classification algorithms
Regression algorithms
Segmentation/Clustering algorithms
Association algorithms
Sequence analysis algorithms
Data Mining Scenarios:
Increase Customer Retention
Identify Most Profitable Customer
Improve Marketing Campaigns
Forecast the Sales of Products for Next Year
Classification algorithms predict one or more discrete variables, based on the other attributes in the dataset.
Regression algorithms predict one or more continuous variables, such as profit or loss, based on other attributes in the dataset.
Segmentation algorithms divide data into groups, or clusters, of items that have similar properties.
Association algorithms find correlations between different attributes in a dataset. The most common application of this kind of algorithm is for creating association rules, which can be used in a market basket analysis.
Sequence analysis algorithms summarize frequent sequences or episodes in data, such as a Web path flow.

22. Excel Data Mining Add-In Features
Business User Tool
SQL Server Add-In
SSAS Dependency
Server Side Model

23. SQL Server Data Tools – SSAS Project
Custom Models
Server Side Hosting
IT Developed
Model Viewers

24. SQL Server Data Tools – SSIS Project
Data Loading
Server Side Hosting
IT Developed
Schedulable

25. SQL Server Management Studio
Original DM Tool
Management Tool
IT Utilized
Model Viewers

26. Visio – Microsoft Data Mining Template/Shapes
Business User Tool
Part of SQL Server DM Add-In
SSAS Dependency
Server Side Model Viewing/ Presentation

27. Scalable | Manageable | Trusted
MGXFY13
4/13/2018
Microsoft Power BI for Office 365 Self-service BI with the familiarity of Office and the power of the cloud
Insights in Excel 1 Billion Office Users
Collaborate in Office in 4 enterprise customers on Office 365
Discover
Analyze
Visualize
Share
Find
Mobile
Q&A
Scalable | Manageable | Trusted
© 2012 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.

28. Microsoft Power BI for Office 365
MGXFY13
4/13/2018
Microsoft Power BI for Office 365
Graphical File organizer
Enable Excel Files for Power BI
250 MB workbooks
© 2012 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.

29. Power BI for O365 - Power View PA Preview
MGXFY13
4/13/2018
Power BI for O Power View PA Preview
In Preview
No SSAS Dependency
O365 Power BI Only
HTML 5
Tableau Compete
© 2012 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.

30. THE END!!!!

31. Visit the Sponsor tables to enter their end of day raffles.
Turn in your completed Event Evaluation form at the end of the day in the Registration area to be entered in additional drawings.
Want more free training? Check out the Houston Area SQL Server User Group which meets on the 2nd Tuesday of each month. Next meeting is May 13th. Details at

32. Discussion