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25.Big Data with Hadoop and Cloud Computing

25.Big Data with Hadoop and Cloud Computing

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25.Big Data with Hadoop and Cloud Computing

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    1. Big Data with Hadoop and Cloud Computing

    2. �Big Data Processing� relevant for Enterprises Big Data used to be discarded or un-analyzed & archived. Loss of information, insight, and prospects to extract new value. How Big Data is beneficial? Energy companies - Geophysical analysis. Science and medicine - Empiricism is growing than experimentation Disney � Customer behavior patterns across its stores, and theme parks Pursuit of a �Competitive Advantage� is the driving factor for Enterprises Data mining (Log processing, click stream analysis, similarity algorithms, etc.), Financial simulation (Monte Carlo simulation), File processing (resize jpegs), Web indexing

    3. Cloud Computing ~ brings economy to Big Data Processing Big Data Processing can be implemented by HPC & Cloud. 1) HPC implementation is very costly w.r.t. CAPEX & OPEX. 2) Cloud Computing is efficient because of its paper use nature. MapReduce programming model is used for processing big data sets. Pig, Hive, Hadoop, � are used for Big data Processing Pig - SQL-like operations that apply to datasets., Hive - Perform SQL-like data analysis on data Hadoop - processes vast amounts of data; (Focal point) Use EC2 instances to analyze �Big Data� in Amazon IaaS. Amazon MapReduce reduces complex setup & Magt.

    4. Cost Comparison of Alternatives

    5. Future Direction Current Experiments & Identified areas Social network analysis Managing Data center Collective Intelligence - Algorithms and Visualization techniques Predictive analytics Accelerators Exploration Apache Whirr - Cloud-neutral way to run services Apache Mahout - Scalable machine learning library Cascading - Distributed computing framework HAMA - define and execute fault tolerant data processing workflows Exploration of LAMP-like stack for Big Data aggregation, processing and analytics

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