Data Culture Series - Keynote & Panel - 19h May - London

DATA CULTURE SERIES – 19th May 2015London

? Who is using Data to drive the future of their business?

? Who is using Predictive Analytics / Machine Learning yet to

change their business model?

UK Business Lead for BI & Advanced Analytics

4

Jon Woodward : Connect & Follow

4

@JLWoodward

www.linkedin.com/in/jonathanwoodward

#DataCulture

SQL Server

PowerBI

AzureML

Hadoop

DataFactory

DocumentDB

Search

EventHub

Stream Analytics

Revolution R

Azure DW

Azure Data Lake

Industry transformation driving opportunities

2015…We have reached a Tipping Point

Of organizations will

consider cloud

deployment

50%

Of new licence spend will

be for Data Discovery &

Analytics

50%

Of BI & Analytics spend

will be driven by the

Business

50%

Of Users will be touched

by BI and Analytics

50%

Core to Vision

Start Justin

Digital Work & LifeExperiences

Data…Driving the Experience

UK Economy - data dividend

The Microsoft

data platformMobileReports

Natural

language queryDashboardsApplications

StreamingRelational

Internal &

externalNon-relational NoSQL

Orchestration

Machine

learningModeling

Information

management

Complex event

processing

Data Culture Series

Data Culture Exec

Session

Data Culture

Summit

4 events – final event 14th May, LondonCXO Level – Invite only

10 events; 1000 customersPower User, Analyst, Architect, Developer, DBA, Data Scientist

Final event this fiscal ( London)

Data Culture Summit

Date Location

19 May LONDON Data Culture series

Summer Break

Date Location

September 16th

/17th

London 2 Day Data Culture Event - http://bit.ly/MSFTDataCulture

Nov 10-11th

London Future Decoded - https://futuredecoded.microsoft.com/

Jan TBC 2 Day Data Culture Event

Value of Data

IoT

Business Apps

CMO, CFO, Sales

Business Case

For Data

CDO, CIO, CTO

Architect Level

Data Platform Workshop

Modernising your Data Platform

Data Developer

Multi-track - Hands-on

BI, Advanced Analytics , IoT, Data Services, Big Data

Dashboard in a

Day

Analyst

Hands on BI

#DataCulture

Microsoft Data Culture - UK

Time

10.00 – 10.30 Intro – Jon Woodward

10:30 – 11:30 KeynotePhillip Watson – Business Applications and DataNeil Miller – Revolution Analytics Overview

11:30 – 12:30 Immersion Tracks - Overview

12:30 – 13:15 Lunch & Expo

13:15 – 15:00 Immersion Hands on

15:00 - 15:15 Break & Expo

15:15 - 16:30 Immersion Hands on

16:30 – 17:00 Panel and l Close

Microsoft, HortonWorks, KPMG, Revolution

PHILLIP WATSONBusiness Applications and Data

Phillip WatsonSolution Specialist

2

1

R&D, Plan Source, Supply

BOM

24

An Example in Practise

26

“Understand, Unlock and Empower your organisation to gain a competitive edge through data driven insight”.

Date: Thursday, June 25, 2015

Time: 01:00 PM British Summer Time

Duration: 1 hour

Understand how information can underpin the delivery of exceptional customer care at the webinar “Care Everywhere –How to amaze, delight and exceed your customers’ high expectations”

Date: Thursday, June 25, 2015

Time: 01:00 PM British Summer Time

Duration: 1 hour

Take a look at the Business Intelligence capabilities that

Microsoft Dynamics AX can surface here

& Microsoft Dynamics CRM here

• If you want to discuss how business applications can

link with your decision making processes contact

Martin Lloyd on [email protected]

NEIL MILLERRevolution Analytics OverviewBigger Data with R

BIGGER Data?

R

Revolution R

Enterprise

Revolution Analytics Proprietary

(A Zettabyte has 21 zeros)

(40,000,000,000,000,000,000,000)

(= 3 million books per person)

Volume

Variety

Velocity

Revolution Analytics Proprietary

But…

• Wider data sets (many more variables / features)

• Real time scoring (steaming data in fast…) Revolution Analytics Proprietary

THE PERFECT STORM

+ Computing Power

+ Bigger Data / More Data

+ Pace of Business+ Customer Expectations

+ Data Science

+ Computer Science

+ Management Science

Better

Business

Decisions

Better

Business

Outcomes

Revolution Analytics Proprietary

- Robert Gentleman & Ross Ihaka, 1993

- Version 1.0 in 2000

- 3.0+ Million Global Users

- 6200+ “Packages”

- R in Universities = New Talent

- Open Source = Access To Innovation

- Programming Agility

- Huge range of predictive analytics

We love R!

Revolution Analytics Proprietary

Source: www.rexeranalytics.com

Revolution R Enterprise solves these problems!

?

Revolution Analytics Proprietary

OUR COMPANY

The leading providerof advanced

analytics software and services

based on open source R, since 2007

OUR PRODUCTS

REVOLUTION R: The enterprise-grade

predictive analytics application platform

based on the R language

Revolution Analytics Proprietary

Language

Interpreter and

Standard R

Algorithm Suites

Development &

Deployment Tooling

Big Data Distributed

Execution Platform

R +

CR

AN

Revo

R

DistributedR

ConnectR

ScaleR

DevelopR DeployR

Revolution R Enterprise Big Data Big Analytics

Ready

– Enterprise

readiness

– High performance

analytics

– Multi-platform

architecture

– Data source

integration

– Development tools

and Integration

tools

Enterprise Technical

Support

Revolution Analytics Proprietary

Revolution Analytics Proprietary

File NameCompressed

File Size (MB) No. RowsOpen Source R

(secs)Revolution R

(secs)

Tiny 0.3 1,235 0.001 0.05

V. Small 0.4 12,353 0.21 0.05

Small 1.3 123,534 0.03 0.03

Medium 10.7 1,235,349 1.94 0.08

Large 104.5 12,353,496 60.69 0.42

Big (full) 12,960.0 123,534,969 Memory! 4.89

V.Big 25,919.7 247,069,938 Memory! 9.49

Huge 51,840.2 494,139,876 Memory! 18.92

22 years of US

flight data

124m rows, 29

variables

Linear

Regression

model - arrival

delay as

function of

day-of-week Tests run on 4 core machine, 16GB RAM and 500GB SSD

Revolution Analytics Proprietary

DistributedR

ScaleR

ConnectR

DeployR

In the Cloud Cloud

Workstations & Servers DesktopsServer

Clustered Systems Microsoft HPCLinux

EDW Teradata

HadoopHortonworksClouderaMapR

+ HD Insights

+ SQL Server vNext

+ Azure ML

+ Power BI

Revolution Analytics Proprietary

In-database analytics at massive scale

Data Scientist

Interact directly with data

SQL Server

Data Developer/DBAManage data and

analytics together

ExtensibilityExample Solutions

• Fraud detection

• Sales forecasting

• Warehouse efficiency

• Predictive maintenance

010010

100100

010101

Relational Data

Analytic LibraryNative functions

T-SQL Interface

Benefits Faster deployment of ML models

Faster performance

(Move compute to the data)

Improved scalability

In-DB Analytic Scenarios Real-time fraud detection

Customer churn analysis

Product recommendations

R

R Integration

coming!

Microsoft Confidential. Preliminary Information. Dates and capabilities subject to change. Microsoft makes no warranties, express or implied.

Revolution Analytics Proprietary

Assemble and standardize

all of a marketer’s data into

a Hadoop cluster

Apply the rigor of a medical

researcher with patented

methodology

Know whom

to reachIdentify and attribute

the revenue drivers

Revolution Analytics Proprietary

More info at:

http://www.revolutionanalytics.com/content/datasong%E

2%80%99s-big-data-analytics-platform-marketing-

optimization-helps-clients-understand

Features

Ensemble of models used:

SVM, Random Forests, and Neural Networks.

Then Logistic Regression used to assess pass

/ fail

Pass

Or

Fail

Pre-processing

crop and align to

fixed size.

More info at :

http://info.revolutionanalytics.com

/30apr15-iot-and-the-

manufacturing-floor.html

Revolution Analytics Proprietary

HOG (Histogram

Orientated

Gradients)

Feature Selection Each value is a composite

(histogram) of multiple

pixels

Hadoop

Edge & Data Node2 x Data Node

• Use new 3rd party data-sources of categorical data to automatically

create new variables (features). e.g consumer spend across various

categories, locations etc.

• Split and analyze features in parallel to measure predictive quality for

credit-risk and default

• Champion / Challenger: Select top ‘n’ new features and compare

against existing features in credit risk models.

• Introduce new “Golden” features once proven to enhance model

• Legacy solution took several months to code with 6 week run process

(with manual intervention). Unsuitable for production runs!

• Revolution code implemented in Hadoop using massive parallel

processing machine-learning to automate feature selection.

• 6 weeks processing reduced to a < 24 hour automated execution

process

External 3rd Party

Data Sources

Customer Credit

Process

Revolution Analytics Proprietary

What next?

• If you are using R (or SAS, SPSS, Matlab…) today and need scale,

speed, support and get on the road to Microsoft Advanced

Analytics come and talk to us!

• [email protected]

• [email protected]

• More info? www.revolutionanalytics.com

Revolution Analytics Proprietary

Tracks Rooms

DATA CULTURE SERIES – 19th May 2015London - Panel

Ric Howe - [email protected] Microsoft

Tim Marston - [email protected] HortonWorks

Andrew Morgan - [email protected] KPMG

Neil Miller - [email protected] Revolution Analytics

#DataCulture

Ric (Microsoft) Q : With all the recent announcements at //Build and Ignite, what aspects should we be most excited about

#DataCulture

Andrew M (KPMG)Q : Does Data Science really require Data Scientists

#DataCulture

Tim M (Hortonworks)Q : if Hadoop is the answer to Big Data, where is it heading…what is the future vision

#DataCulture

Neil M(Revolution)Q : Analytics and R is such as hot topic –how should be start?

Trial : Revolution R Open

Trial : Hadoop (HDInsight, HDP)

57

Get Hands on…

Trial : SQL Server 2014

Trial : PowerBI

Trial : Machine Learning (AzureML)

SQL Saturday – Manchester , July 25th

SQL Relay , October 12-22nd – 8 Locations

PASS BA*, London , November

PASS Summit*- US, October 27-30th

SQL Saturday – Edinburgh , June 13th

58

Community Events

58

* See Jen Stirrup for Discount

59

Future Decoded https://futuredecoded.microsoft.com/

60

SQL London Chapter (Tonight)

6:00 - 6:10 PASS Chapter Updates

6:10 - 7:10pm Allan Mitchell (MVP) - DocumentDB

7:10 - 7:40pm Break & Networking

7:40 - 8:40pm Tobiasz Koprowski (MVP) - WASD for Beginners

Linked In: http://www.sqlpass.org/linkedin

Facebook: http://www.sqlpass.org/facebook

Twitter: @SQLPASS

PASS: http://www.sqlpass.org

Learn More: Microsoft Azure

• Microsoft Azure Consulting Sessions – Apply Now to 27th May• Contact our Azure advisory team at [email protected]

• Tech Days Online – Azure Special: 2nd-4th June• Developer showcases, demos and deep technical learning with MS experts

• http://aka.ms/tdoazure

Learn More: Internet of Things & Data

• Developing for Internet of Things: http://aka.ms/iotworkshop• Download the Hands On Lab• June 11th Reading: 1-Day IoT & Data “Hackathon” hands on learning• Waitlist registrants receive 1st priority for next event

• Machine Learning without a PhD• Watch the Webinar http://aka.ms/azuremlwebinar• Download the hands on lab http://aka.ms/machinelearninglab

• Join the IoT Community Group: 9th June Focus Group• Connect with Microsoft and others in IoT. • Contact [email protected]

Get Ready for September..

Date Location

16 September READING

10 November LONDON

27 November READING

3 December LONDON

27 January LONDON

24 February LEEDS

24 March EDINBURGH

8 April BIRMINGHAM

12 May READING

19 May LONDON

Have a great Summer….

UK Business Lead for BI & Advanced Analytics

64

Jon Woodward : Connect & Follow

64

@JLWoodward

www.linkedin.com/in/jonathanwoodward

#DataCulture

THANK YOU

?