Boost your Analytics with Machine Learning for SQL Nerds. Julie mssqlgirl.com
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1 Boost your Analytics with Machine Learning for SQL Nerds Julie mssqlgirl.com
2 1. Y ML 2. Operationalizing ML 3. Tips & Tricks 4. Resources
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4 automation
5 delighting customers
6 Deepen Engagement Predict Outcomes Automate Actions
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8 Language platform Statistics programming language Data visualization tool Open source Community 2.5+M users Taught in most universities Popular with new and recent grads Thriving user groups worldwide Ecosystem 10,000+ packages in CRAN Scalable to big data Rich application and platform integration
9 Challenges of using R Data movement Deployment Scale and performance Moving data from the DB to R Runtime becomes painful as data volumes grow Movement carries security risks How do I call the R script from my production application? Most R functions are single threaded and only accommodate datasets that fit into available memory
10 Analytic Server Separate Service or Embedded Logic
11 Pre SQL 2016 = messy
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13 In-database advanced analytics Pushing intelligence to where data lives Application Application Intelligence Database Database Intelligence Before Intelligence built in to the DB
14 SQL Server R Services solves problems Reduce or eliminate data movement with in-database analytics Deploy R scripts and models Achieve enterprise scale and performance Leverage built-in extensibility mechanisms to allow secure execution of R scripts Use familiar T-SQL stored procedures to invoke R scripts from your app Embed the returned predictions and plots Use parallelism query capabilities of in-memory and ColumnStore indexes Leverage RevoScaleR support for large datasets and parallel algorithms
15 Deploy predictive analytics Develop, explore and experiment in your favorite R IDE Train a model with sp_execute_external_ script and save in DB Deploy with sp_execute_external_ script and R code to predict with the model Make your apps intelligent by consuming predictions Develop Train Deploy Consume
16 SQL Server 2016 = clean
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25 SSMS custom reports
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28 Scenario: Website that sells products. Classify new reviews based on rating of old reviews Input Data: Product reviews with rating Training: Build model to learn classification of input data Prediction: Rate new product reviews using the text classification model
29 Scenario: Learn patterns from customer data to design campaigns & convert highest possible number of customers Input Data: Campaign leads, demographic information, channel information, product category, conversion outcomes from previous campaign(s) Training: Build models that will learn patterns for conversion of campaign leads. Evaluate decision tree models & pick the best one Prediction: Recommend best channel for campaign to optimize the conversion rate
30 Scenario: Detect potentially fraudulent transactions with low latency Input Data: Historical labelled credit transactions, risk factors for IP address/geographical data, transaction characteristics, account information Training: Build a model to learn patterns of fraudulent transactions Prediction: Probability of fraud for new transactions. Operationalize model using native scoring capability
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35 Please Support Our Sponsors SQL Saturday is made possible with the generous support of these sponsors. You can support them by opting-in and visiting them in the sponsor area. The 1st EVER #SQLSatLA on June 10 th 2017 Microsoft Technology Center
36 SoCal Local User Groups L.A. User Group 3 rd Thursday of each odd month sql.la Los Angeles - Korean Every Other Tuesday sqlangeles.pass.org Orange County User Group 2 rd Thursday of each month bigpass.pass.org SQL Malibu User Group 3 rd Wednesday of each month sqlmalibu.pass.org San Diego User Group 1 st & 3 rd Thursday of each month meetup.com/sdsqlug meetup.com/sdsqlbig Sacramento User Group 1 st Wednesday of each month The 1st EVER #SQLSatLA on June 10 th 2017 Microsoft Technology Center
37 California SQL Saturdays SQL Saturday in Sacramento 2017 (#650) When: Saturday, July 15, 2017 SQL Saturday in San Diego 2017 (#661) When: Saturday, September 23, 2017 The 1st EVER #SQLSatLA on June 10 th 2017 Microsoft Technology Center
Boost your Analytics with ML for SQL Nerds
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