Peter Elleby - Big Data, Big Noise, Big Hope - No Miracles
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Transcript of Peter Elleby - Big Data, Big Noise, Big Hope - No Miracles
Peter Elleby
Greenlight
‘Big Data, Big Noise, Big Hope – No Miracles
Big Data, Big Noise, Big Hope – No Miracles
27/06/2013
Big Data - Volume, Velocity, Variety
As American created about 4lb of rubbish every day.
If the rest of the world produced as much, this would be 10M tons daily, or 4T tons annually.
How do you define “Big Data”?
Applications involving collections of data of a size, that makes them impossible to process in a cost effective manner using traditional database management tools
and data processing applications.
Traditional Data Management and Data Processing
OLTP OLAP
Application Operational Decision Support
Horizon Days & Weeks Months & Years
Refresh Immediate Periodic
Data Model Entity-Relationship Multi-Dimensional
Schema Normalized Star (de-normalized)
Emphasis Update Retrieval
Space Small Large (History)
Core Big Data Strategies
• Distribution of Data• Network of Lower Cost Devices
• Compression of Data• Using Processing Power to Reduce Bandwidth Requirements
• Representation of Data• Focus on Algorithm rather than Data Model
• Change of Emphasis• From Completeness to Relevancy
Big Data Application - Hydra
Big Data Application Characteristics - Hydra
• Time Series Data• Storage of State versus Events
• Data Aggregation• Statistical Significance
• Dynamic Clustering• Ontologies of Keywords and Phrases
• Data Refinement• Statistical Process Control and Regression Modelling
Brewers Theorem (the CAP Theorem)
The CAP theorem states that any networked shared-data system can have at most two of three desirable properties:• consistency (C) equivalent to having a single up-to-date
copy of the data• high availability (A) of that data (for updates)• tolerance to network partitions (P)
“sacrifice consistency to gain faster responses in a more scalable manner”
A Practical Everyday Example
S1 S2 SN...
The Takeaways
• The Aims of your Application determines whether you are dealing with Big Data
• The frameworks or technologies best suited to achieve your goals are determined your application