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Agenda
Data On Cloud Data problems. Why Cloud.
Process Big Data on Cloud using 100% Apache Hadoop
By Michael S. Collier, Principal Cloud Architect, Aditi Technologies
Q&A Panel Discover Risks, Strategies & Roadmap for Cloud adoption
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
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
What Do We Mean By Cloud?
• On-demand self service
• Broad network access
• Resource pooling
• Rapid elasticity
• Measured service
Meet your data challenge…
High Volume
Data Growth Quality of
Data
Increased
Frequency of
Data Collection
Data Beyond
Relational
Valuable Insights Budget for Growth Globally Accessibility
Volume Velocity Variety Veracity
Security Reliability
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
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 4 team 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
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
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
How Cloud Helps Solve the Data Problem
↑ Ability to add storage dynamically
↑ Increase computing power on demand
↑ Use global distributed data centers for localized processing High Volume
Data Growth
VOLUME
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
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
How Cloud Helps Solve the Data Problem
↑ Clean, usable data
↑ Leverage compute power for post
processing
↑ Purchase data from marketplaces
VERACITY
Quality of
Data
Aggregate
Fragmented
data sources
Non relational
information Unclean data DATA SOURCE
Relational
historic data
DATA INJECTION Classify data into tables,
blobs, SQL Database Enable blob storage as
HDFS for HDInsight
Enrich
Filter data using
MAPREDUCE REFINE
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
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
Starting the Journey
Data & Cloud Quickstart
• Half-day with an Architect
• Detailed review of data challenges and cloud maturity
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