This slide deck was presented at #DataOnCloud event Seattle. DataOnCloud is an invite-only event for CIOs and top IT innovators. DataOnCloud enables key decision makers to discuss about real life adoption scenarios, challenges and best practices for leveraging Big, Small and Line Of Business Data on Cloud. Aditi Technologies, a 'cloud first' technology services company organized #DataOnCloud, an event series focused on orchestrating data on cloud and navigating the complexity around integration, security, platform selection and technology solutions. Aditi Technologies partnered with Microsoft for this 2-hour, CXO roundtable event in global technology hubs - London, New York, Seattle and San Diego

1. DATA ON CLOUD.

2. Agenda
Data On Cloud
Data problems. Why Cloud. Myth busting. Solution Roadmap
By Michael S. Collier, Principal Cloud Architect, Aditi Technologies
Crunch Big Data with Windows Azure HDInsight
Process Big Data on Cloud using 100% Apache Hadoop
By Matt Winkler, Principal Program Manager, Microsoft
Q&A Panel
Discover Risks, Strategies & Roadmap for Cloud adoption

3. Housekeeping
FriendsConnectWho am I? Participation

4. Trusted, Respected, Technology Leader
2012 Partner of the year
Windows Azure , Finalist
2011 Partner of the year
Windows Azure SI, Finalist
2010 Partner of the year
Windows Azure , Winner
 Best companies to work for
 Top 10 IT Workplace
 Global Cloud MVPs
 Top 50 Cloud influencers
 1:114 hiring ratio
The Best ‘OF’
Vendor Award
 52% of our customers rate us 5/5.
 45 + active customers.
 170+ engagements.
 1600 people, globally
 18 years, 12 locations

5. ww.aditi.com
WE HELP OUR CLIENTS
MOVE THEIR BUSINESS
TO THE CLOUD

6. ww.aditi.com 7
USER EXPERIENCE
MODERNIZATION
MOBILE AND
MULTICHANNEL
DATA AND
ANALYTICS
SOCIAL BUSINESS
SAAS ENABLEMENTINFRASTRUCTURE
MIGRATION
CLOUD OPSCLOUD
INTEGRATION
BUILD WITH AGILE
ENGINEERING
PLAN AND
ARCHITECT
CONTINUOUS
DEPLOYMENT AND
SUPPORT
OUR SOLUTIONS CATER TO OUR CUSTOMER’S MARKETS
TEST AUTOMATION
INCREASE MARKET REACH REDUCE COST OF SERVING MARKETS ACCELERATE TIME TO MARKET

7. ww.aditi.com 8
HOW DO YOU MAKE A GYM MORE STICKY ?
3
CHANNELS
WEB, SOCIAL,
MOBILE
HELPING AMERICA’S #1 FITNESS
CHAIN REACH MORE CUSTOMERS
AND DRIVE MORE LOYALTY WITH
INTEGRATED MARKETING
HOW DO YOU INTEGRATE YAHOO AND BING?
HELPING MICROSOFT ADCENTER
TEAM INTEGARET YAHOO AND
BING SEARCH ENGINE WITHOUT
IMPACTING ADVERTISERS.
151
MILLION
CUSTOMER
IMPACTED
9
MONTHS
TO GO LIVE
WE HELP OUR CUSTOMERS NAVIGATE TRANSFOMATIONS
HOW DO YOU MANAGE 3 MILLION INSTANCES ?
HELPING XBOX TEAM MANAGE
PROCESSING AND PLAYER DATA
ACROSS 3 MILLION CONCURRENT
WEEKEND GAMERS
#1
LARGEST AZURE
INSTANCE
IN THE WORLD
3
MILLION
PLAYERS
HOW DO YOU SELL A PLANE ?
HELPING REDESIGN CUSTOMER
EXPEREINCE IN ‘INTERACT AND
BUY A PLANE’ BRIEFING CENTER.
3
MONTHS
TO DELIVER
185
MILLION USD
AVG SKU PRICE
HOW DO YOU MAP AN OCEAN FLOOR ?
LIVE
ANALYTICS ON
TB OF DATA
HELPING ANALYZE LIVE
GEOSPATIAL DATA FROM OCEAN
FLOOR
300
MILLION USD
IN FUNDING
HELPING LADBROKES IMPROVE
GAME MARGINS BY 4% POINTS
THROUGH TEST AUTOMATION
AND PERFORMANCE TESTING
4
YEARS OF CO-
ENGINEERING
HOW DO YOU NOT LOSE MONEY ON HORSES?
120
PEOPLE IN 9
MONTHS

9. What Do We Mean By Cloud?
• On-demand self service
• Broad network access
• Resource pooling
• Rapid elasticity
• Measured service

10. Cloud Computing Models

11. Compute Options
Application Control

13. Is this true?
…is King
King of your . . .

14. Meet your data challenge…
High Volume
Data Growth Quality of
Data
Increased
Frequency of
Data Collection
Data Beyond
Relational
Valuable InsightsBudget for Growth Globally Accessibility
Volume Velocity Variety Veracity
Security Reliability

15. From Where Does this Data Come?
Device + Sensors Social Feeds
Relational
Databases
Trading Desks Web Logs
Document Stores
Use of Data?
 KPI Dashboards
 Trading Stations
 Alert/Notifications
 Personalized Web
NoSQL or Table
Storage

16. 343 Industries Gets New User Insights from Big
Data in the Cloud
BI insight about the game to internal and external customers
Provide details for the leaderboard, game stats, feedback, & play patterns
 Windows Azure based storage for unstructured data – game data pushed
into BLOB storage.
 Analyze and query data using HDInsight, based on Apache Hadoop
 Ability to generate reports in Excel by leveraging Hive ODBC driver
 Connect Halo 4team directly to customers through weekly updates &
customized marketing campaigns.
 Enhances user experience through increased agility & faster response times
 Provides in-game analysis to identify cheaters

17. Financial Services Company Reduces Costs &
Increases Reliability of Services
Reduce ever-increasing on-going capital investments
Increase reliability of services serving over 100,000 members in Illinois
 Windows Azure based provisioning of server Virtual Machines (VMs)
 Replication of Windows Azure Active Directory and extension on Cloud
 Single sign-on authentication using Active Directory
 Implementation of Disaster Recovery solution
 Storage scalability
 Reduced costs
 Disaster recovery & backup solutions

20. How Does Cloud Solve the 4V’s?
High Volume
Data Growth Quality of
Data
Increased
Frequency of
Data Collection
Data Beyond
Relational
Volume Velocity Variety Veracity

21. How Cloud Helps Solve the Data Problem
↑ Ability to add storage dynamically
↑ Increase computing power on demand
↑ Use global distributed data centers for
localized processingHigh Volume
Data Growth
VOLUME

22. How Cloud Helps Solve the Data Problem
↑ Use Azure networks to collect data with
very low latency
↑ Leverage CEP on Windows Azure to do real
time event processing
↑ Distribute notifications and alerts
VELOCITY
Increased
Frequency of
Data Collection

23. How Cloud Helps Solve the Data Problem
↑ Windows Azure supports Relational,
NoSQL and Blob storage
↑ Ability to process and enrich all kinds of
data using HDInsights
↑ Combine relational and non relational
data in one service
VARIETY
Data Beyond
Relational

24. How Cloud Helps Solve the Data Problem
↑ Clean, usable data
↑ Leverage compute power for post
processing
↑ Purchase data from marketplaces
VERACITY
Quality of
Data

25. Approach for USING DATA with the CLOUD

27. Aggregate
Fragmented
data sources
Non relational
information
Unclean dataDATA SOURCE
Relational
historic data
DATA INJECTION Classify data into tables,
blobs, SQL Database
Enable blob storage as
HDFS for HDInsight

28. Enrich
Filter data using
MAPREDUCEREFINE
TRANSFORM
CLEANSE
Apply transformations Segment data based on
multiple variables
 Remove duplicates
 Eliminate non required information
Leverage HIVE to use
HDInsights as a DW
Prepare and load it into
relational format if required
Load data into
clusters using PIG

29. Analyze
ANALYZE
VISUALIZE
Access HDFS data using
Excel data explorer
Implement Embedded
visualizations using Power view
Leverage machine learning
Deliver alerts and notifications
Implement statistical algorithms
like Naïve baiyes,Clustering
Process real time business
events using StreamInsight
Visualize

30. How Do We Make Sense of this Data?
Right PersonRight TimeRight Data

31. Starting the Journey
Data & Cloud Quickstart
• Half-day with an Architect
• Detailed review of data
challenges and cloud
maturity

32. Web | Blog | Facebook | Twitter | LinkedIn