2. INTRODUCTION
Big data refers to the dynamic, large and
disparate volumes of data being created by
people, tools and machines.
it requires new, innovative and scalable technology
to collect, host and analytically process the vast
amount of data gathered in order to derive real-
time business insights
Big data includes information garnered from social
media, data from internet-enabled devices,
machine data, video and voice recordings.
4. WHY BIG DATA ?
Growth of big data is needed
1. Increase of storage capacities
2. Increasing of processing power
3. Availability of data of different data types
4. Everyday we create 2.5 quintillion bytes of data.
5. Facebook generates around 10TB daily
5. HOW IS BIG DATA
DIFFERENT?
1. Automatically generated by machines
(eg sensor embedded in a machine).
2. Typically an entirely new source of data
(e.g use of the internet)
3. Not designed to be friendly (e.g text streams)
7. BIG DATA ANALYTICS
examining large amount of data
appropriate information
identification of hidden patterns, unknown
correlation
competitive advantage
better business decisions :strategic and
operational
effective marketing ,costomer
satisfaction,increased revenue.
10. TYPES OF TOOLS USED IN
BIGDATA
Where processing is hosted?
-----distributed servers/cloud (Amazon EC2)
Where data is stored?
------Distributed storage (Amazon S3).
What is the programming model?
---distributed processing( map reduce)
How data is stored & indexed?
-----High performance schema –free data bases( e.g MONGO
DB).
What operations are performed on data?
---analytic/semantic process
11. Merits of big data
Big data eliminates intuition.
Real time data is just not a storing petabytes of data in data
warehouse ,its ability to make better decisions and
meaningful actions at the right time.’
Fast forward to present and technologies like hadoop give
us scale and flexibility to store data before processing it.
Technologies such as MapReduce,Hive and Impala
enables us to run queries without changing the data
structures underneath.
12.
13. Risks of bigdata
Will be overwhelemed
Need the right people to solve the problem.
Costs esculate too fast
Need not capture all 100%
Many sources of big data is privacy.
Self-regulation.
Legal regulation.
16. BIG DATA IMPACT ON IT
Big data is troublesome force providing both opportunities
and challenges to IT organisations
4.5 million IT jobs in big data
India will require big data scientist in the next couple of years
in addition to the data analysts and data managers to support
big data space.
17. BIG DATA IN BANKING AND
SECURITIES
Challenges :
Early warning for securities fraud and trade
visibility.
Card fraud detection and audit trails .
Security exchange commission uses big data
to monitor financial market activity
Big data providers specific to this industry
include 1010 data Quartet FS, Nice Actimize.
18. BIG DATA IN COMMUNICATIONS
MEDIA AND ENTERTAINMENT
Collecting ,analyzing and utilizing consumer
insights.
Leveraging mobile and social media content .
Understanding patterns of real-time ,media
content usage
Big data providers specific to this industry include
SPOTIFY ,AMAZON PRIME,
SPLUNK,INFOCHIMPS.
19. BIG DATA IN HEALTH CARE
Rising medical costs.
Unavailability /inadequate /unusual data
Visual data allows faster identification and efficient
analysis of healthcare information for early detection of
chronic disorders.
Big data providers specific to this industry include
RECOMBINANT DATA ,HUMEDICA .
20.
21. BIG DATA IN RETAIL AND
WHOLESALE TRADE
Unutilized data derived from customer loyalty
cards ,POS scanners .
Optimized staffing through data from shopping
patterns’.
Timely analysis of inventory
Reduced fraud
Big data providers specific to this industry include
first retail,first insight ,epicor