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Planning your Hadoop/NOSQL Projects
for 2011
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Agenda
Why Hadoop/NoSQL ± a primer!
Challenges of moving to big data solutions- Hadoop, MPP
and/or NoSQL
Requirement assessment and planning for the right solution
An extension to existing IT strategy or a complete migration?
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The Bottlenecks
Analyze Hadoop/NoSQL fitment
Ease its adoption for business benefits
Minimize risk
Make the transformation seamless and disruption free
Alignment with IT strategy
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Hadoop/ NoSQLFitment analysis
Best Fit
solution
Create POC
Operational CostAnalysis
Deployment Cost
Analysis
Team Training Cost
SolutionImplementation
Production
Readiness
Deployment
The Failure-proof Way
Costing ImplementationCriteria
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Hadoop/NoSQL Fitment Analysis
Challenges/Factors
Can my business problem be solved using
Hadoop/NoSQL?
R&D is costly and resources are limited
What is the best solution among so many options?
Can I utilize µClouds¶ for operational costs?
Approach
Identify core pain areas, diagnose and choose suitableBig Data solution
Leverage knowledge of experienced Hadoop/NoSQL
professionals for compute & data intensive solutions
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Challenges/Factors
Hadoop/NoSQL have numerous solutions- which is the
right one for me?
Would the solution be cost effective?
Approach
Provide early associated costing and deployment
strategies
Use technical expertise on Hadoop/NoSQL technologies
Compute intensive and/or Data intensive?
Maximize reuse of existing resources
Best Fit Solution Identification
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Challenges/Factors
How to make sure the solution can be implemented?
How to verify that the solution is cost effective?
Batch processing v/s real time solution?
Approach
Provide a working prototype addressing key issues
Does the solution work?
Is it cost effective?
Is it production ready?
V erification wit h POC
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Challenges/Factors
Cost involved in development, release and hosting?
Hosting cost on Cloud- Server, RAM, CPU, Storage
Any specific hardware?
Approach
Analyzing operational cost of hosting on Cloud
Impetus¶ Hadoop deployment toolkit
Leverage knowledge and best practices
Deployment Cost Analysis
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Challenges/Factors
Recurring hardware/software cost?
Support and maintenance cost?
Approach
Operational scalability & efficiency analysis
Operational cost analysis
Operational Cost Analysis
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Challenges/Factors
Is my IT/Ops team trained to manage development/
deployment?
Hire new resources or train existing team?
Approach
Hadoop is map-reduce APIs built atop of Java- can be
easily learned by programmer
Will not take long to train the team NoSQL database design and implementation training
T raining Cost Analysis
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Challenges/Factors
Can we use traditional development processes in
Hadoop/NoSQL?
How to ensure that proper quality guidelines are being
followed?
Approach
Development cycle ± use proven product development
lifecycle management process
Plan for seamless transformation and disruption free
operations
Solution Implementation
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Challenges/Factors
How to prepare for production readiness?
How to tune production environment?
How is engineering going to cope with complex
implementations?
Approach
Proper expertise needed for production deployment
Production readiness checks Production environment tuning/optimizations
Proper training/handover to engineering team for
production deployment
Production Readiness &Deployment
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The Big Picture
Business
Strategy
Infrastructure
Development
Testing
BI and
Analytics
Data
Warehousing
Enterprise
Architecture
Impact on
IT Strategy
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Extension to current IT Strategy
Existing code reusability(business logic)
Minor modifications in test strategy
No major changes in release and build management of
Hadoop/NoSQL module
Quick setup for development/test/production
environments
Migration
Complete DW platform Data storage and archival
BI and Analytics
Application redesign
W hat C hanges Do I Need T o Make?
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Hadoop is NOT a new technology but a different
programming paradigm
NoSQL is a non-normalized way of data modeling
The Bottom Line
Hadoop/ NoSQL is SIMPLE!
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Case Study
Our Approach
� Assessment of the products that actually require
Hadoop/ NoSQL
� Replaced low latency read-write to NoSQL� Continued the use of ETL and used HDFS
The Challenge
� Where to use Hadoop
� Low RoI on Hadoop infrastructure
� Issues in Hadoop optimization and performance The Client
Global leader in internetservices and media
Client was able to reuse existing investments
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Case Study
Our Approach
� Consultation to determine right Big Data solution
�Used our SPDMMmethodology to validate NFR
� Proposed a suitable NoSQL solution
The Challenge
� Product targeting an enormous user base
� Data size ranging in TBs/PBs
� Traditional solutions could not address the
required data sizes The Client
A Fortune-500 enterprise
NoSQL solution saved cost for the client
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Questions
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Thank youFor more information,
write to us at [email protected]
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