1. 5/16/2018 3:45 AM
BRK3298
Building machine learning applications using R and Python in SQL Server 2017
Umachandar Jayachandran (UC)
Sumit Kumar
Program Managers
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2. Agenda Machine Learning Intro SQL Server Machine Learning Services
Customer scenarios
What’s coming?

3. Bringing intelligence to where data lives
Application
Application + Intelligence VS
Intelligence + Database
Database
Regular Database + App
Intelligence Database + App

4. Why Machine Learning in SQL Server?
5/16/2018 3:45 AM
Why Machine Learning in SQL Server?
Eliminate data movement
Leverage database security
Push ML compute to the database
R integration
Python integration
Operationalize ML scripts and models
Calling familiar T-SQL stored procedures
Model management in SQL Server
Data Scientist
Interacts directly with data
Analytics library
Enterprise grade performance and scale
Scale your R and Python analytics with multi- threading and parallel processing
SQL Server security, compliance, resource governance, query performance, always on secondaries
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100100
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100100
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010010
100100
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SQL Developer/ DBA
SQL Transformations
Relational data
Manage data and
analytics together
© 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.

5. Customer Story - PROS Pricing Optimization Segmentation
Expert
Target
Floor
Group customers, products & transactions into micro-segments of similar willingness-to-pay
Apply optimization algorithms to target the pricing envelope ‘sweet spot’ in every segment

6. Attribute Selection Tool
5/16/2018 3:45 AM
Before
After
SQL Server
Attribute Selection Tool
C++/R
SQL Server
Attribute Selection
sp_execute_external_script
‘R code’
Data tables
Data tables
Segmentation Tool
C++/R
Segmentation
sp_execute_external_script
‘R code’
Stored Proc
Scoring
sp_execute_external_script
‘R code’
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7. Customer stories ATTOM Data Solutions Acxiom Heartland Bank
ATTOM will be able to take advantage of a host of new capabilities, including machine learning and predictive analytics.
ATTOM Data Solutions
Real estate property insights
Acxiom
Migrating from SAS
Targeted marketing campaigns
Heartland Bank
Build financial models
With R Services, Acxiom is building better, more accurate models using larger data sets, which results in more precisely targeted marketing for customers.
The bank has moved its credit scorecard development, arrears analysis, investment forecasting, and analysis of intermediary and broker performance to the R Server platform.

8. 5/16/2018 3:45 AM
Hello Iris!
Demo
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9. SQL Server Machine Learning Services
R support (3.2.2 version)
Microsoft R Server (under Modern Lifecycle Policy)
SQL Server 2017
Native scoring using PREDICT function (+Linux support)
EXTERNAL LIBRARY DDL for R package management
Batch mode execution support for input data
R support (3.3.3 version)
Python support (Anaconda 3.5.2)

10. Azure SQL Database Machine Learning Services
Native scoring using PREDICT function
R support preview (3.3.3 version)
Available in West Central US Region
Premium & Premium RS Service Tiers
Base R packages & RevoscaleR package
Training & Scoring of Models that fit in memory
Trivial Parallelism & Streaming support
One concurrent execution of R script

11. Machine Learning Server
5/16/2018 3:45 AM
Machine Learning Server
Multi-platform support
Windows, Linux, Hadoop, SQL Server
Microsoft R Server
RevoScaleR, MicrosoftML, olapR, sqlrutils packages
Web services operationalization
Microsoft Machine Learning Server
R & Python support
revoscalepy, microsoftml python libraries
rxExecBy
Hadoop Licensing changes
5 nodes for every SQL Server EE core under Software Assurance
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12. Data Scientists - Data Exploration and Model Development
Microsoft Tech Summit FY17
5/16/2018 3:45 AM
Data Scientists - Data Exploration and Model Development
train <- RxSqlServerData(query, connectionString, computeContext)
rxLogit(formula, train) 2
Execution 1
Script
SQL Server
Data Scientist Workstation 3
Results
Machine Learning Services
Any R/Python IDE
R/Python Runtime
© 2016 Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

13. Machine Learning Services
Microsoft Data Amp
5/16/2018 3:45 AM
Application Developer - Model Operationalization 2
Execution
Stored Proc call
Results 1 3
The stored procedure contains R or Python code and executes in-database
SQL Server
Application
Machine Learning Services
exec sp_execute_external_script
@language = ‘Python’
, @script =
-- Python code --
R/Python Runtime
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14. Hospital Length of Stay
5/16/2018 3:45 AM
Hospital Length of Stay
HeaIthcare ISV building intelligence into their application
Allow hospitals to optimize resource allocation
Dashboard that shows Predictions against actuals
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15. Operationalize Length of Stay Predictions
Problem
Predict accurately how long a newly admitted patient will stay in the hospital
Solution
Build a model using anonymized patient data
Operationalize model using T-SQL stored procedures
Train Model using Anonymized data
Anonymized Patient information
Key variables are number of previous admissions, diagnostic codes, lab results
Operationalize Model in Azure SQL Database
Deploy model to production database
Use model to predict length of stay

16. Predict patient length of stay
5/16/2018 3:45 AM
Predict patient length of stay
Demo
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17. Realtime Predictions using Native Scoring
5/16/2018 3:45 AM
Realtime Predictions using Native Scoring
PREDICT function
No dependency on R or Python runtime
Enabled on SQL Server in Windows & Linux
Usage
Single or small number of rows scoring
Highly concurrent scoring scenarios
Predict during INSERT, UPDATE, MERGE statements
Requirements
Models built using RevoScaleR or revoscalepy
rxLinMod, rxLogit, rxBTrees, rxDTree, rxDForest
Serialized using rxSerializeModel (R) or rx_serialize_model (Python)
© Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

18. PREDICT syntax PREDICT ( MODEL = @model | model_literal,
5/16/2018 3:45 AM
PREDICT syntax
PREDICT ( MODEL | model_literal,
DATA = object AS <table_alias> )
WITH ({ {column_definition } [,...n ] } )
INSERT INTO loan_applications
(c1, c2, c3, c4, risk_score)
SELECT d.c1, d.c2, d.c3, d.c4, p.score
FROM PREDICT(MODEL DATA as d)
WITH(score float) as p;
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19. Fraud Detection using PREDICT
Problem
Detect potentially fraudulent transactions with low latency
Solution
Build a model to learn patterns of fraudulent transactions
Train Model using Sample data
Historical labelled credit transactions, risk factors for IP address/geographical data, transaction characteristics, account information
Operationalize scoring using PREDICT
Use model to get probability of fraud for new transactions
Use PREDICT to score transactions during INSERT

20. Fraud detection using PREDICT
5/16/2018 3:45 AM
Fraud detection using PREDICT
Demo
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21. Deploy predictive analytics
Make your app/reports intelligent by consuming predictions
Deploy your ML scripts with sp_execute_external_ script and predict using the models
Train models with sp_execute_external_
script and save the models in database
Develop, explore and experiment in your favorite IDE
Develop
Train
Deploy
Consume

22. Roadmap Machine Learning Services in Azure SQL Database Future release
5/16/2018 3:45 AM
Roadmap
Machine Learning Services in Azure SQL Database
Configuration & Monitoring
R support
MicrosoftML Package
Package installation / management using CREATE EXTERNAL LIBRARY DDL
SQL Compute Context support from client or R script executing on the server
Parallel execution for R Server models
Python support
Future release
Machine Learning Services in SQL Server on Linux
Failover cluster support
Partitioning support for input data
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23. Call to action Resources BRK3261
5/16/2018 3:45 AM
Call to action
Resources
SQL Server Samples – R Services & ML Services
SSMS Reports for ML Services
SQL Server Machine Learning Services (aka.ms/mlsqldev)
Getting started ML tutorials
SQL Server Developer Tutorials (aka.ms/sqldev)
Getting started SQL tutorials
BRK3261
Performance Patterns for SQL Server Machine Learning Services
© Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.

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5/16/2018
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© 2012 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista 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. What is Machine Learning?
5/16/2018 3:45 AM
What is Machine Learning?
Uses data mining and learning techniques to train models using historical data to predict future outcomes
Examples
Predict store sales based on historical performance
Predict default of a loan based on loan/transaction history
Predict sentiment of a new tweet or review or call log
Classify customers into groups based on transaction characteristics
Classify images and extract features from images
© Microsoft Corporation. All rights reserved. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.