BIG DATA & DATA ANALYTICS

Submitted By:
Nagaraja G
Final CSE
SJCET,Yerrakota
BIG DATA
&
DATA ANALYTICS

Content
1. Introduction
2 Overview
3 Why Big Data
4 Application of Big Data
5 Risks of Big Data
6 Benefits & Impact of Big Data
7 Conclusion

Introduction
 Big Data may well be the Next Big Thing in the IT world.
 Big data burst upon the scene in the first decade of the 21st
century.
 The first organizations to embrace it were online and startup
firms.
 Big data can bring about dramatic cost reductions,
substantial improvements in the time required to perform a
computing task, or new product and service offerings.

Overview
 ‘Big Data’ is similar to ‘small data’, but bigger in size
 But having data bigger it requires different approaches:
 Techniques, tools and architecture
 An aim to solve new problems or old problems in a better
way
 Big Data generates value from the storage and processing
of very large quantities of digital information that cannot be
analyzed with traditional computing techniques.

Characteristics of Big Data
Volume
• Data
quantity
Velocity
• Data
Speed
Variety
• Data
Types

Storing Big Data
 Selecting data sources for analysis
 Eliminating redundant data
 Establishing the role of Data models
Selecting Big Data
 Choosing the correct data stores based on your data
characteristics
Processing Big Data
 Integrating & Mapping data
 Connecting and extracting data from storage
 Transforming data for processing

The Structure of Big Data
Structured
 Most traditional data
sources
Semi-structured
 Many sources of big
data
Unstructured
 Video data, audio
data
7

Why Big Data
 Growth of Big Data is needed
 Increase of storage capacities & Processing power
 Availability of data(different data types)
 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

Why Big Data
 FB generates 10TB
daily
 Twitter generates 7TB
of data Daily
 IBM claims 90% of
today’s stored data
was generated in just
the last two years.

Big Data sources
Exploiting known
security vulnerabilities
Systems
Back doors
Large and growing files
(Big data files)

Data generation points Examples
Mobile Devices
Readers/Scanners
Science facilities
Microphones
Cameras
Social Media
Programs/Software

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

Application Of Big Data analytics
Homeland
Security
Smarter
Healthcare
Multi
channel
Telecom
Manufactur
ing
Traffic
Control
Trading
Analytics
Search
Quality

Risks of Big Data
 Will be so overwhelmed
 Need the right people and solve the right problems
 Costs escalate too fast
 Isn’t necessary to capture 100%
 Many sources of big data is privacy
 self-regulation
 Legal regulation
14

Leading Technology Vendors
Example Vendors
 IBM – Netezza
 EMC – Greenplum
 Oracle – Exadata
Commonality
 MPP architectures
 Commodity Hardware
 RDBMS based
 Full SQL compliance

How Big data impacts on IT
 Big data is a troublesome force presenting opportunities
with challenges to IT organizations.
 By 2015 4.4 million IT jobs in Big Data ; 1.9 million is in
US itself
 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.

Potential Value of Big Data
 $300 billion potential
annual value to US health
care.
 $600 billion potential
annual consumer surplus
from using personal location
data.
 60% potential in retailers’
operating margins.

India – Big Data
 Huge market opportunities for IT services (82.9revenues)
and analytics firms (17.1 % )
 Current market size is $200 million. By 2015 $1billion
 The opportunity for Indian service providers lies in offer
services around Big Data implementation and analytics for
global multinationals
 Gaining attraction

Benefits of Big Data
 Real-time big data isn’t just a process for storing petabytes or
exabytes of data in a data warehouse, It’s about the ability to
make better decisions and take meaningful actions at the
right time.
 Fast forward to the present and technologies like Hadoop
give you the scale and flexibility to store data before you
know how you are going to process it.
 Technologies such as MapReduce,Hive and Impala enable you
to run queries without changing the data structure
underneath.

Benefits of Big Data
 Our newest research finds that organizations are using big data
to target customer-centric outcomes, tap into internal data and
build a better information ecosystem.
 Big Data is already an important part of the $64 billion
database and data analytics market
 It offers commercial opportunities of a comparable scale to
enterprise software in the late 1980s
 And the Internet boom of the 1990s, and the social media
explosion of today.

Conclusion
 $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 & DATA ANALYTICS

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