The Database Pro’s Guide to the Team Data Science Process

Why SentryOne? CC

Deep Functionality

Unrivaled Scalability

Unmatched Expertise

Top-Rated Customer Support

Unmatched Expertise

• Fastest Diagnosis• Automation• Highest granularity• Jump-to navigation• Highly configurable

• 100% customer satisfaction on tickets• 50% of tickets resolved in <1hr• 8.8/10 Trust Radius score• NPS 50% higher than the industry

• Proven• Leading Edge Technology• End-to-end full

environmental view• Lowest overhead

• Microsoft-only focus• 8 Microsoft MVPs• Community Commitment• Built by experts

Visibility Across the Microsoft Data Platform

Monitor, diagnose, and optimize SQL Server

performance.

Find and fix SSAS performance problems.

Monitor resource utilization (memory, CPU, network,

storage) of VM environments.

Boost Windows Server and Hyper-V virtualized environment

performance.

See performance for Microsoft Analytics Platform System, data

movement and queries.

Accelerate Azure SQL Data Warehouse performance with

visibility into workload impacts.

Keep Azure SQL Databases running at peak efficiency with

metrics and DTU usage.

Drive Productivity with 60+ SSIS components for connectivity,

execution performance, and security.

Inspect and compare schemas, objects, and data.

Automatic documentation, object lineage, impact analysis, data

dictionary and environment compare.

SSIS and SSRS Monitoring and package deployment in

Visual Studio.

SSIS script development and sharing.

Automated data-centric application testing and data

verification.

SQL plan analysis and advanced query tuning.

Development Operations BI Administration

The One Platform for Physical, Virtual, and Cloud Performance.

Free e-booksIn these books, you will find useful, hand-picked articles that will help give insight into some of your most vexing performance problems. These articles were written by several of the SQL Server industry's leading experts, including Aaron Bertrand, Paul White, Paul Randal, Jonathan Kehayias, Erin Stellato, Glenn Berry, and Joe Sack.

http://www.sentryone.com/ebooks/

WebsitesSQLPerformance.com provides innovative and practical solutions for improving SQL Server performance.

SentryOne.com/Resources offers an inside look into the world of SentryOne with videos on query tuning and product demos, white papers, ebooks, and tech briefs.

Blogs.SentryOne.com is where you can find all of our team members’ blogs as well as important information about the latest updates to SentryOne software, SQL Server and server

performance issues.

Free Resources

Your Presenter

Kevin KlinePrincipal Program Manager, SentryOneMicrosoft Data Platform MVP since 2003

Contact InfoTwitter : @KeklineEmail : KKline@SentryOne.comBlog : http://blogs.SentryOne.com/author/kevinkline/LinkedIn : https://www.linkedin.com/in/kekline/

Agenda

• What to expect:• How to get started with Machine Learning and the Cortana AI Suite

• Good practices

• What to study next

• What NOT to expect:• Enough skills to get a job with Ml or AI

• Full depth and breadth of SQL Server ML Services

• Statistics knowledge

What’s Machine Learning?

http://dilbert.com/strip/2013-02-02

Machine learning explores the study and construction of algorithms that can learn from and make predictions on data. Such algorithms operate by building a model from example inputs in order to make data-driven predictions or decisions, rather than following strictly static program instructions. –Wikipedia.org/wiki/Machine_learning

Ok, Really?

• ML will answer questions like:• Is this A or B?

• Is this weird?

• How much – or – How many?

• How is this organized?

• What should I do next?

Great write-up at https://www.sqlmelody.com/tdsp-lifecycle-business-understanding/

Generally Speaking…

• Traditional programming combines code + data running on CPU(s) to produce output.

• ML combines data + output running on CPU(s) to produce a program. • The program is the ML algorithm

which then becomes the input on future iterations.

• Remember the goal is to make predictions and forecasts.

The Team Data Science

Lifecycle

The Team Data Science

Lifecycle

Play the game “Then what would you do?” to its conclusion.

The Team Data Science

Lifecycle

Lambda Architecture

20% of Job / 80% of Work

Azure baby!

The Team Data Science

Lifecycle

The Team Data Science

LifecycleMicrosoft & Community gives away the store to make this as easy as possible!

The Team Data Science

Lifecycle

Common Roles in TDSP

Applying Algorithms to TDSP

Walkthru Into the Process

Input Data

Preprocess Data

Split Data

Algorithm Selection

Train the Model

https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/

Check out the Azure AI Gallery to make life much easier!

In-database Analytics

Train the Model

Train the Model

• https://towardsdatascience.com/metrics-to-evaluate-your-machine-learning-algorithm-f10ba6e38234

Tips and Tricks• When installing…

• DON’T• Run R / Python script as-is

• Embed secrets in scripts

• Do data transformations that can be achieved in SQL

• Access network resources

• Process/transform files as part of the stored procedure call

• Embed the R/Python code directly in applications

• DO• Develop/Test from RTVS, PTVS,

RStudio or other IDE SQL

• Compute Context from client

• Data processing & transformations in SQL Server

• Data integration using SQL Server features

• Model management in database

Tools and Resources• Get the project templates:

• https://github.com/Azure/Azure-TDSP-ProjectTemplate

• Microsoft wants this to be easy!• https://github.com/Azure/Azure-TDSP-Utilities includes:

• IDEAR – Interactive Data Exploration, Analysis, and Reporting tool • AMAR – Automated Modeling and Reporting tool

• Lots of docker containers that are pre-assembled

• Learning resources:• The Team Data Science Process - https://aka.ms/tdsp• Learn AI - http://learnanalytics.microsoft.com/• A Plethora of learning resources!

https://blogs.technet.microsoft.com/machinelearning/2017/01/25/a-plethora-of-microsoft-training-options-on-ai-machine-learning-data-science-including-moocs/

More Goodies

• Getting started SQL + ML tutorials: http://aka.ms/sqldev

• SSMS Reports for R Services: http://bit.ly/2r525gu

• Build 2017: Serving AI with Data (SQL Server 2017): http://bit.ly/2rbEDlZ

• SQL Server Samples on GitHub: • R Services http://bit.ly/2s7tBNV• ML Services http://bit.ly/2rbLNGz

• Using RTVS: http://bit.ly/2rbrXLU

• Build 2017 session recordings on Channel 9: http://bit.ly/2puyVun

• Microsoft Virtual Academy online: http://aka.ms/mva

Tools and Resources, Non-Microsoft

• What’s your ML test score? A rubric for ML production systems • https://ai.google/research/pubs/pub45742

• Lessons learned turning machine learning models into real products and services • https://www.oreilly.com/ideas/lessons-learned-turningmachine-learning-

models-into-real-products-andservices

Summary

Download Plan Explorer!http://sentryone.com/plan-explorer

Like our products?• Please consider giving us a

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Let’s connect!• Facebook, LinkedIn, Twitter

at KEKLINE.