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> Agenda
> Hadoop not standing alone
> Parallel and Complementary Stacks
> The Best of Both Worlds = Big Data Analytics + Traditional BI
> Big Data Analytics on Hadoop Use Cases
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> What Hadoop Adopters Are Saying
> How to make Hadoop successful with BI
• Raw unstructured – Web logs, machine
/sensor data, mobile social, video, etc.
• Structured data – traditional RDMBS, EDW’s
• Streaming vs. batch oriented
• Data governance and quality
> Cornerstone 1: Employ All Data
• Traditional models and assets
• Standard Hadoop components including
UDFs and SerDes
• Custom algorithms
• Models created in other systems such as
SAS/R
> Cornerstone 2: Use All Analytic Assets
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• Easy-to-use ad-hoc analysis, web-based forms
• Drag and drop
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• Common skills: SQL
• Powerful iterative analysis
• Analytical models and algorithms
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> Cornerstone 3: Provide Self-Service Access for All Users
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• Metadata, Queries, Results and Visualizations
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> Cornerstone 4: Build a Collaborative Environment
> Cornerstone 5: Be Open and Extensible
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> Cornerstone 6: Populate Best-of-Breed Reporting Tools
> How would an architecture look
> Summary
> Summary Get the Best of Both Worlds – Build a Bridge Inside Your Company
Big Data Analytics on Hadoop
Future, see intent
Drives Optimization
Just getting startedBI
Historical
Drives reporting
Entrenched
Be around for a long time
