1. Business Proposal
Presented by:
Saptadeep Dutta, Gurgaon - ODC
February, 2015
For internal use

2. The Proposal
Build a low cost data analytics solution proprietary to A1
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For A1 internal use

3. 3
In other words…

4. …an all purpose, home grown, proprietary analytics solution running on Google cloud
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For A1 internal use
…that’s easy on the pocket

5. Rationale (Why?)
• Add a product to our line of business
• Tap into the growing data-analytics (DA) market
• Help us reach sectors like Pharma, Retail, Banking etc.
• Existing solutions have a high TCO and support needs
• Most low cost DA solution providers are mid-sized
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For A1 internal use

6. For A1 Internal Use
The proposed disruption
“Industry comparable solution at a significantly lower cost”
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7. Challenges
• Well established competitors More on competition…
• We do not have the first mover advantage
• Several players
• An unchartered space
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For A1 internal use

8. 8
Opportunity groups……
For A1 internal use

9. BigData Database
•Data modeling
•Filtering
•Troubleshooting
•Data management
Presentation
•Groovy UIs
•Native Apps
•Responsive Web Apps
Analytics
•Math/Stat modeling
•Data Science
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For A1 internal use
Complete DA Solution
DA layers of opportunities

10. Business model and tech-stack: At a glance
• Differential pricing, depending on revenue structure: SaaS or PaaS or SaaP
• Revenue model could be Freemiun or Pay-As-You-Go
• Structure selling propositions so as to have perpetual earning potential
Business
• nDB for Database
• Python toolkits like NumPy etc for analytics
• HTML5, jQuery, iOS/Swift, Android, etc. for presentation
• Google Appengine for hosting More on tech…
Tech.
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For A1 internal use
Acronyms: PaaS: Platform as a service, SaaP: Software as a Product, SaaS: Software as a service, TCO: Total Cost of Ownership

11. For A1 Internal Use
Proposed Revenue Model
• License the complete solution on Pay-As-You-Go basis
• License of one of more groups
SaaS
• Dry-lease the platform
• License platform as a product but retain the right to sell copies
PaaS
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• Position as an end-to-end product that includes Analytics services also
SaaP

12. Why use Google?
• Is high on reliability - low on cost
• Is secure
• Supports all data analytic needs
• Offers high scalability
• Supports almost all programming languages
• Has high availability
• Has a relatively shorter learning curve
Why not to use Google?
• nDB does not run in-premise, so migration to an in-premise cloud will require some effort
• Remark: Remote possibility that a BigData using business would want to migrate to in-premise cloud
• Cloud usage price is fixed as per Google’s pricing policy.
• Remark: This is common to all except Apache Hadoop
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For A1 internal use
Why/Why not Google?

13. Competition*
Open source: Apache Hadoop
• Positives:
• The leader
• Been there for a very long time
• Negatives:
• Hardware resource intensive
• Steep learning curve
Proprietary:
SAS/SAP/Salesforce/Oracle:
• Positives:
• Good support
• Been there for a very long time
• Negatives:
• High TCO, fixed cost
• Steep learning curve
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For A1 internal use
*This is a partial list, more research needed

14. Tech…

15. BigData Database
Presentation
Toolkits
Analytics
Toolkits
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For A1 internal use
DA in action

16. DA in action: BigData Database
• Distinctly different from traditional databases
• Often referred as NoSQL* databases
• Popular NoSQL databases:
• nDB (Google)
• hBase (Hadoop)
• MongoDB (MongoDB Inc)
• DynamoDB (Amazon)
BigData
Database
*NoSQL: Not only Structured Query Language
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For A1 internal use

17. • Typically a coding centric component
• Collection of APIs and visual tools to interact with
and analyze extremely large collection of data stored
in NoSQL databases. APIs implement math and
statistical functions
• Answers questions such as:
• How many male surfers between 2pm to 3pm in
the age group less then 30 years?
• Standard deviation of the number of product X
bought by individuals
Analytics
Toolkit
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For A1 internal use
DA in action: Analytics Toolkit

18. • Styles the view of the result of the analysis on
web or devices
• Web app toolkits: HTML5, AngularJS, jQuery, etc.
• Mobile App: iOS, Android, Swift, etc.
Presentation
toolkit
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For A1 internal use
DA in action: Presentation toolkit

19. TBD Slides
SWOT analysis
of the proposal
Marketing and
operational
plan
Strategy
Road map and
schedule
Case studies
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For A1 internal use

20. Tidbits
• Three specific implementations of Data-analytics:
• Descriptive Analytics,
• Predictive Analytics and
• Prescriptive Analytics
• Domegemegrottebyte is the highest multiple of bytes, coming after
Terabyte, Petabyte, Exabytes, Zettabyte, Xenottabyte, Shilentnobyte
• AT&T is thought to hold the world’s largest volume of data in one
unique database – its phone records database contains 2 trillion rows
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For A1 internal use