Microsoft and Revolution Analytics -- what's the add-value? 20150629

Microsoft and Revolution

Analytics: What’s the

Add-Value?MARK TABLADILLO PH.D. – MICROSOFT MVP

JUNE 29, 2015

Mark Tab

Consulting

Training

Teaching

Presenting

SQL Server MVP

Linked In

@MarkTabNet

Outline

1) an overview of current data science technologies from Microsoft;

2) a description of the R language;

3) a brief review of the add-value for R with Azure Machine Learning, and

4) a description of the performance architecture and demo of the

language constructs developed by Revolution Analytics

Current Data Science Technologies

• SQL Server License (Win OS)

• Business Intelligence or Enterprise

SQL Server Analysis Services Data Mining

• Excel 2007 or Higher

• X64 betterExcel Data Mining Add-In

• Free or Paid Tiers

• Any OS

Microsoft Azure Machine Learning

• Open Source

• Mono-Project, Visual StudioF#

• SQL Server 2016Revolution Analytics

Data Scientist

Interact directly with data

Built-in to SQL Server

Data Developer/DBAManage data and

analytics together

Built-in advanced analyticsIn-database analytics

Example Solutions

• Fraud detection

• Sales forecasting

• Warehouse efficiency

• Predictive maintenance

Relational Data

Analytic Library

T-SQL Interface

Extensibility

?R

R Integration

010010

100100

010101

Microsoft Azure

Machine Learning Marketplace

New R scripts

010010

100100

010101

010010

100100

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010010

100100

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010010

100100

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100100

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AML

Gallery

ML

Studio

SSMS /

RSSRS /

CR

Excel /

PVPower

BI.com

Fisher’s Iris flower datasetmachine learning

Description of

the R Language

R

RSTUDIO

RATTLE

Growth and Demand for R

R is the highest paid IT skill

Dice.com, Jan 2014

R most-used data science language after SQL

O’Reilly, Jan 2014

R is used by 70% of data miners

Rexer, Sep 2013

R is #15 of all programming languages

RedMonk, Jan 2014

R growing faster than any other data science language

KDnuggets, Aug 2013

More than 2 million users worldwide

R Usage GrowthRexer Data Miner Survey, 2007-2013

70% of data miners report using

R

R is the first choice of more

data miners than any other

software

Source: www.rexeranalytics.com

R with Azure

Machine

Learning

Revolution

Analytics

2007: The Beginning

13

2008: Revolutions Blog14

R in the News

15

2009

New York Times:Data Analysts Captivated by R’s Power

2009

Revolution R Enterprise

version 3

First R Debugging IDE

16

2010: User Group Sponsorships

17

141 R User Groups

Rows of data 1 billion 1 billion

Parameters “just a few” 7

Time 80 seconds 44 seconds

Data location In memory On disk

Nodes 32 5

Cores 384 20

RAM 1,536 GB 80 GB

Double

45%

1/6th

5%

5%Revolution R is faster on the same amount of data, despite using approximately a 20th as many cores, a 20th as

much RAM, a 6th as many nodes, and not pre-loading data into RAM.

Bottom Line: Revolution R Enterprise Performance = Greatly Reduced TCO

*As published by SAS in HPC Wire, April 21, 2011

Logistic Regression:

18

2010: Head to Head with SAS

2011: RHadoop

19

github.com/RevolutionAnalytics/RHadoop

2013Shaking up the industryA Gartner Magic Quadrant

Visionary

20

2014: Technical Support for Open Source RAdviseR™ from Revolution Analytics

21

Technical support for open source R, from the R experts.

10x5 email and phone support

Support for R, validated packages, and third-party software connections

On-line case management and knowledgebase

Access to technical resources, documentation and user forums

Exclusive on-line webinars from community experts

Guaranteed response times

Also available: expert hands-on and on-line training for R, from Revolution Analytics AcademyR.

http://www.revolutionanalytics.com/adviser

http://revolutionanalytics.com/academyr-training-

education

SummaryWATCH FOR SQL SERVER

2016

Abstract

Microsoft has been a leader in the enterprise analytics space for years. In 2014, Microsoft had already created R language functionality within Azure Machine Learning. On April 6, 2015, Microsoft and closed on a deal to acquire Revolution Analytics, a company focusing on scalable processing solutions initiated by the well-known R language. Many data science projects and initial demos do not need high-volume solutions: however, having a high-volume answer for the R language allows for planning or working toward the largest data science solutions.

This presentation describes the add-value for the Revolution Analytics acquisition. The talk covers 1) an overview of current data science technologies from Microsoft; 2) a description of the R language; 3) a brief review of the add-value for R with Azure Machine Learning, and 4) a description of the performance architecture and demo of the language constructs developed by Revolution Analytics. Most of the presentation will be focused on sections two and four. It is anticipated that these technologies will be partially if not fully integrated into SQL Server 2016.