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Bigdatappt 130621045034-phpapp01
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Transcript of Bigdatappt 130621045034-phpapp01
• ‘Big Data’ is similar to ‘small data’, but bigger
•…but having data bigger it requires different approaches:• Techniques, tools and architecture
•…with an aim to solve new problems•…or old problems in a better way
Why Big Data
• Key enablers of appearance and growth of Big Data are
–Increase of storage capacities
–Increase of processing power
–Availability of data
–Every day we create 2.5 quintillion bytes of data; 90% of the data in the world today has been created in the last two years alone
Big Data Analytics
• Examining large amount of data
• Appropriate information
• Identification of hidden patterns, unknown correlations
• Competitive advantage
• Better business decisions: strategic and operational
• Effective marketing, customer satisfaction, increased revenue
Applications for Big Data Analytics
Homeland Security
Finance Smarter HealthcareMulti-channel
sales
Telecom
Manufacturing
Traffic Control
Trading Analytics
Fraud and Risk
Log Analysis
Search Quality
Retail: Churn, NBO
Healthcare
• 80% of medical data is unstructured and is clinically relevant
•Data resides in multiple places like individual EMRs, lab and imaging systems, physician notes, medical correspondence, claims etc
• Leveraging Big Data• Build sustainable healthcare systems• Collaborate to improve care and outcomes• Increase access to healthcare
Market Size
Source: Wikibon Taming Big Data
By 2015 4.4 million IT jobs in Big Data ; 1.9 million is in US itself
India – Big Data
•Gaining attraction
•Huge market opportunities for IT services (82.9% of revenues) and analytics firms (17.1 % )
• Current market size is $200 million. By 2015 $1 billion
• The opportunity for Indian service providers lies in offering services around Big Data implementation and analytics for global multinationals
India will require a minimum of 1 lakh data scientists in the next couple of years in addition to data analysts and data managers to support the Big Data space.
NoSQL : non-relational or at least non-SQL database solutions such as HBase (also a part of the Hadoop ecosystem), Cassandra, MongoDB, Riak, CouchDB, and many others.
Hadoop: It is an ecosystem of software packages, including MapReduce, HDFS, and a whole host of other software packages