Big data

…Big Data...
14404- FANSUPKAR TANIYA
14418- RAIS ZOYA

Big Data is the ocean of information we swim in every day vast
sources of data flowing from our computers, mobile devices, and
machine sensors. Big Data is being generated by everything around
us at all times. Every digital process and social media exchange
produces it, while systems, sensors, and mobile devices transmit it.
New sources of data come from a variety of machines, such as
website interactions, search engine optimizations, and social
business sites by using click-stream data. These changing business
requirements demand that the right information be available at the
right time.[1]
What is Big Data?

Big Data Versus Small Data
Small Data
• Usually designed to answer a
specific question or serve a
particular goal.
• Typically, small data is
contained within one
institution, often on one
computer, sometimes in one
file.
• In many cases, the data user
prepares her own data, for her
own purposes.
Big Data
• Usually designed with a goal in
mind, but the goal is flexible
and the questions posed are
protean.
• Typically spread throughout
electronic space, typically
spread through multiple
Internet servers, located
anywhere on earth.
• The data comes from many
differ sources, and it is
prepared by many people.

Small Data
• Ordinarily contains highly
structured data. The data
domain is restricted to a
single discipline or sub
discipline.
• Typically, the data is
measured using one
experimental protocol, and
the data can be represented
using one set of standard
units.
Big Data
• Must be capable of
absorbing unstructured
data (e.g., such as free-text
documents, images, motion
pictures, sound recordings,
physical objects).
• Many different types of
data are delivered in many
different electronic formats
by different people.[2]

Let’s look at
Big Data
in a different way.

Kilobyte
Byte : one grain of rice
Kilobyte : cup of rice

Megabyte
Megabyte : 8 bags of rice

Gigabyte
Gigabyte : 3 Semi trucks

Terabyte
Terabyte : 2 Container Ships

Petabyte
Petabyte : Blankets Manhattan

One ByteExabyte
Exabyte : Blankets west coast states

Zettabyte : Fills the Pacific Ocean
Zettabyte

Yottabyte : A EARTH SIZE RICE BALL! Yottabyte

HobbyistByte : one grain of rice
Yottabyte : A EARTH SIZE RICE BALL!

Desktop
HobbyistByte : one grain of rice

Desktop
Hobbyist
Internet

Desktop
Hobbyist
Internet
Big Data

Desktop
Hobbyist
The Future?[3]
Internet
Big Data

Volume...
100 terabytes of data are uploaded daily to Facebook ; Akamai
analyses 75 million events a day to target online ads; Walmart
handles 1 million customer transactions every single hour. 90%
of all data ever created was generated in the past 2 years.
Scale is certainly a part of what makes Big Data big. The
internet-mobile revolution, bringing with it a torrent of social
media updates, sensor data from devices and an explosion of e-
commerce, means that every industry is swamped with data-
which can be incredibly valuable, if you know how to use it.
3vs of Big Data

Velocity…
In 1999, Wal-Mart’s data warehouse stored 1,000 terabytes (1,000,000
gigabytes) of data. In 2012, it had access to over 2.5 petabytes (2,500,000
gigabytes) of data.
Every minute of every day, we upload 100 hours of video on Youtube, send
over 200 million emails and send 300,000 tweets. ‘Velocity’ refers to the
increasing speed at which this data is created, and the increasing speed at
which the data can be processed, stored and analysed by relational
databases. The possibilities of processing data in real-time is an area of
particular interest, which allows companies to do things like display
personalised ads on the web pages you visit, based on your recent search,
viewing and purchase history.

Variety…
Gone are the days when a company’s data could be neatly
slotted into a table and analysed. 90% of data generated is
‘unstructured’, coming in all shapes and forms- from geo-spatial
data, to tweets which can be analysed for content and
sentiment, to visual data such as photos and videos.
The ‘3 V’s’ certainly give us an insight into the almost
unimaginable scale of data, and the break-neck speeds at which
these vast datasets grow and multiply. But only ‘Variety’ really
begins to scratch the surface of the depth- and crucially, the
challenges- of Big Data.[4]

High Maintenance.
Skill needed to access Data.
Difficult to Handle.
Violates the Privacy Principle.[5]
Drawbacks of Big Data...

Government.
International development
 Manufacturing
Cyber-Physical Models
Media
Technology
Private sector
Science and Research.[6]
Applications of Big Data…

[1].Book: "Big Data for Beginners" by Alonzo Williams,Stepanie Foor.
[2].Book: "Principles of Big Data: Preparing, Sharing, and Analyzing Complex
Information" by Jules J. Berman.
[4].Book: "Understanding Big Data: A Beginners Guide to Data Science & the Business
Applications" by Eileen McNulty-Holmes.
[5].http://www.oii.ox.ac.uk/research/project/?id=98.
[6].https://www.google.co.in/#q=applications+of+big+data+wikipedia.
[3]. http://www.slideshare.net/dwellman/what-is-big-data-24401517?qid=6e8e2726-
6681-486c-880b-f973f6b61e2c&v=&b=&from_search=5

Big data

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