Connected data

CLOUD

MOBILE

IntelligenceCloudData

Machine

Learning

PPT R

EM

12

Churn

analysis

Social network

analysis

Recommenda-

tion engines

Location-

based

tracking and

services

Weather

forecasting

business

planning

Fraud

detection

Equipment

monitoring

Personalized

Insurance

cloud computing

2011 2016 5x increase

data explosion

90% of the data in the world today has been created in the last two years alone

Action

Value

From data to decisions and actions

EXAMPLE SOLUTIONS

Advanced Analytics scenarios

Data Science Team

Data Engineering

Data Science

Application Development

Business Acumen

Data Management

Data

Dividend

People

+

Data Sources

Apps

Sensors and devices

From Data To Action On Premises

INTELLIGENCEDATA ACTION

Automated SystemsMicrosoft R Server & SQL R Services

Apps

Cortana Intelligence

Cortana Intelligence Suite

Intelligence

Dashboards &

Visualizations

Information

Management

Big Data Stores Machine Learning

and Analytics

CortanaEvent HubsHDInsight

(Hadoop and

Spark)

Stream

Analytics

Data Intelligence Action

People

Automated Systems

Apps

Web

Mobile

Bots

Bot

FrameworkSQL Data

WarehouseData Catalog

Data Lake

Analytics

Data Factory Machine

LearningData Lake Store

Cognitive

Services

Power BI

Data

Sources

Apps

Sensors

and

devices

Data

Easily build, deploy, and share predictive analytics solutions

• Simple, scalable, cutting edge. A fully managed cloud service that enables you to easily build, deploy, and share predictive analytics solutions.

• Deploy in minutes. Azure Machine Learning means business. You can deploy your model into production as a web service that can be called from any device, anywhere and that can use any data source.

• Publish, share, monetize. Share your solution with the world in the Gallery or on the Azure Marketplace.

Machine Learning

and Analytics

HDInsight

(Hadoop and

Spark)

Stream

Analytics

Data Lake

Analytics

Machine

Learning

1993

Research project in Auckland, NZ

1995

Open source

1997

R-core

2000

R-1.0.0

2003

R Foundation

2004

First UseR!

2009

New York Times

2015

R-3.2.0

R Consortium

Photo credit: Robert Gentleman

What is

• A statistics programming language

• A data visualization tool

• Open source

• 2.5+M users

• Taught in most universities

• Thriving user groups worldwide

• 8000+ free algorithms in CRAN

• Scalable to big data

• New and recent grad’s use it

Language

Platform

Community

Ecosystem

• Rich application & platform integration

IEEE Spectrum July 2015

Language PopularityIEEE Spectrum Top Programming Languages

R Usage GrowthRexer Data Miner Survey, 2007-2013

Rexer Data Miner Survey

#9: R

DatasizeIn-memory

In-memory In-Memory or Disk Based

Speed of AnalysisSingle threaded Multi-threaded

Multi-threaded, parallel

processing 1:N servers

SupportCommunity Community Community + Commercial

Analytic Breadth

& Depth 7500+ innovative analytic

packages7500+ innovative analytic

packages

7500+ innovative packages +

commercial parallel high-speed

functions

LicenceOpen Source

Open SourceCommercial license.

Supported release with indemnity

Copyright Microsoft Corporation. All rights reserved.

Useful linksAzure ML lab: https://aka.ms/azure-ml-lab-content

Azure ML Studio: https://studio.azureml.net/

Learn R: http://tryr.codeschool.com/

Free Microsoft online training:

Introduction to R for Data Science: https://www.edx.org/course/introduction-r-data-science-microsoft-dat204x-3

Programming in R for Data Science: https://www.edx.org/course/programming-r-data-science-microsoft-dat209x-2

Analyzing Big Data with R server: https://www.edx.org/course/analyzing-big-data-microsoft-r-server-microsoft-dat213x

Machine learning cheat sheet: https://docs.microsoft.com/en-us/azure/machine-learning/machine-learning-algorithm-cheat-

sheet

Spurious correlation: http://www.tylervigen.com/spurious-correlations