The Next Frontier for Innovation, Competition and Productivity
 ‘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
4 V‘s of Big Data
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
FinanceSmarter Healthcare
Multi-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
Potential Talent Pool -Big
Data
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.
Future of Big Data
 $15 billion on software firms only specializing in data
management and analytics. This industry on its own is worth
more than $100 billion and growing at almost 10% a year
which is roughly twice as fast as the software business as a
whole.
 In February 2012, the open source analyst firm Wikibon
released the first market forecast for Big Data , listing $5.1B
revenue in 2012 with growth to $53.4B in 2017
 The McKinsey Global Institute estimates that data volume is
growing 40% per year, and will grow 44x between 2009 and
2020.
Big Data Analytics
Technologies
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
Thank you 
Bigdatappt
Bigdatappt

Bigdatappt

  • 1.
    The Next Frontierfor Innovation, Competition and Productivity
  • 3.
     ‘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
  • 4.
    4 V‘s ofBig Data
  • 5.
    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
  • 6.
    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
  • 7.
    Applications for BigData Analytics Homeland Security FinanceSmarter Healthcare Multi-channel sales Telecom Manufacturing Traffic Control Trading Analytics Fraud and Risk Log Analysis Search Quality Retail: Churn, NBO
  • 8.
    Healthcare  80% ofmedical 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
  • 9.
    Market Size Source: WikibonTaming Big Data By 2015 4.4 million IT jobs in Big Data ; 1.9 million is in US itself
  • 10.
    India – BigData  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
  • 11.
    Potential Talent Pool-Big Data 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.
  • 13.
    Future of BigData  $15 billion on software firms only specializing in data management and analytics. This industry on its own is worth more than $100 billion and growing at almost 10% a year which is roughly twice as fast as the software business as a whole.  In February 2012, the open source analyst firm Wikibon released the first market forecast for Big Data , listing $5.1B revenue in 2012 with growth to $53.4B in 2017  The McKinsey Global Institute estimates that data volume is growing 40% per year, and will grow 44x between 2009 and 2020.
  • 14.
    Big Data Analytics Technologies 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
  • 15.

Editor's Notes

  • #5 Acco.to IBM
  • #8 Explain well. Quote practical examples
  • #15 NoSQL : approach to data management and database design that's useful for very large sets of distributed data.   Hadoop: free, Java-based programming framework that supports the processing of large data sets in a distributed computing environment Map Reduce: software framework that allows developers to write programs that process massive amounts of unstructured data in parallel across a distributed cluster of processors or stand-alone computers. Map, a function that parcels out work to different nodes in the distributed cluster. Reduce, another function that collates the work and resolves the results into a single value.
  • #17 No need to explain Mention some company names
  • #18 No need to explain Mention some company names