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Overview of Big Data
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Big Data Analytics: Source of Competitive Advantage and Enabler for Blue Ocean Business Models
Suresh [email protected]
Outline
• Objectives• What Is Big Data?• Challenges with Legacy BI applications• Applications of Big Data• Business Models• Technology• Market for Big Data• Risks & Limitations of Big Data• Conclusions
Objectives• To identify ways by which Big Data can become source of
competitive advantage for businesses Shortcomings of Legacy Business Intelligence (BI) applications Identification of industries/sectors which can benefit from Big data an-
alytics
• To identify strategies to capture and create value from Big Data Business drivers for Big Data Identification of business models around Big Data
• To identify various technologies for capturing and analyz-ing Big Data Identifies different approaches to store Big Data (e.g., HDFS, Cas-
sandra, MangoDB etc. ) Big Data Platform (Apache Hadoop project)
• To identify markets for Big Data products
Outline
• Objective and Methodology• What Is Big Data?• Challenges with Legacy BI applications• Applications of Big Data• Business Models• Technology• Market for Big Data• Risks & Limitations of Big Data• Conclusions
What Is Big Data?
Big Data is a term that describes large volumes of High Velocity, Complex and Variable data that require advanced techniques and technologies to enable the Capture, Storage, Distribution, Management, and Analysis of the information
Big Data analytics is the process of examining and interrogating big data as-sets to derive insights of value for decision making
1 Kilobyte 1,000 bits/byte1 megabyte 1,000,0001 gigabyte 1,000,000,0001 terabyte 1,000,000,000,0001 petabyte 1,000,000,000,000,0001 exabyte 1,000,000,000,000,000,0001 zettabyte 1,000,000,000,000,000,000,000
Characteristics of Big Data The “BIG” in big data isn’t just about volume
How Is Big Data Different?
1) Automatically generated by a machine (e.g. Sensor embedded in an engine)
2) Typically an entirely new source of data (e.g. Use of the internet)
3) Not designed to be friendly (e.g. Text streams)
4) May not have much values– Need to focus on the important part
Outline
• Objective and Methodology• What Is Big Data?• Challenges with Legacy BI applications• Applications of Big Data• Business Models• Technology• Market for Big Data• Risks & Limitations of Big Data• Conclusions
Challenges with Legacy BI applications
• Management of unstructured data is a very large problem
• Performance of conventional databases (RDBMS) degrades
with increase in data volume
Outline
• Objective and Methodology• What Is Big Data?• Challenges with Legacy BI applications• Applications of Big Data• Business Models• Technology• Market for Big Data• Risks & Limitations of Big Data• Conclusions
Sectors which can benefit from Big Data
Common Big Data Customer ScenariosGain competitive advantage by moving first and fast in your industry
IT infrastruc-ture opti-mization
Legal discovery
Social net-work analysis
Traffic flow optimization
Web app op-timization
Churn analysis
Fraud detection
Natural re-source explo-ration
Weather forecasting
Healthcare outcomes
Life sciences research
Advertising analysis
Equipment monitoring
Smart meter monitoring
Outline
• Objective and Methodology• What Is Big Data?• Challenges with Legacy BI applications• Applications of Big Data• Business Models• Technology• Market for Big Data• Risks & Limitations of Big Data• Conclusions
Big Data Framework Big Data is Big Business
CrowdsourcingSentiment Ana-lysis, Network Analysis
Cluster Analysis, Multidimensional Analysis
Predictive Model-ing
Outline
• Objective and Methodology• What Is Big Data?• Challenges with Legacy BI applications• Applications of Big Data• Business Models• Technology• Market for Big Data• Risks & Limitations of Big Data• Conclusions
Technology Driven mainly by Open Source initiatives
Apache™ Hadoop project
Apache™ Cassandra project
Apache™ HBase project
Apache™ Hive project
Apache™ Solr project
Outline
• Objective and Methodology• What Is Big Data?• Challenges with Legacy BI applications• Applications of Big Data• Business Models• Technology• Market for Big Data• Risks & Limitations of Big Data• Conclusions
Market for Big Data Growth rate of Big Data industry is much higher than average
growth rate of IT industry
Outline
• Objective and Methodology• What Is Big Data?• Challenges with Legacy BI applications• Applications of Big Data• Business Models• Technology• Market for Big Data• Risks & Limitations of Big Data• Conclusions
Risks of Big Data Will be so overwhelmed
– Need the right people and solve the right problems
Technological considerations– Open source– Scalability & Performance issues
Many sources of big data is privacy– Self-regulation– Legal regulation
The Need for Standards Become more structured over time Fine-tune to be friendlier for analysis Standardize enough to make life much easier
Outline
• Objective and Methodology• What Is Big Data?• Challenges with Legacy BI applications• Applications of Big Data• Business Models• Technology• Market for Big Data• Risks & Limitations of Big Data• Conclusions
Conclusions Big Data is a large and fast growing market Leveraging Big Data for insights can enhance productivity and
competitiveness for companies Harnessing Big Data will enable businesses to improve market in-
telligence For IT professionals it means lot of new job opportunities in the
area of data analytics
Thank you