This document provides an overview of big data. It defines big data as large volumes of data that come in many varieties and are created quickly. It notes that while 5 billion gigabytes of data were created from the beginning of recorded time until 2003, that same amount was being created every two days by 2011 and every 10 minutes by 2013 due to the growth of data from sources like the internet and smartphones. The document also outlines some of the common tools used to analyze big data, potential benefits and challenges, as well as which industries are most impacted.

1. Big Data
a small introduction

2.  WHAT IS BIG DATA?
 BIG INWHAT?
 DATA USAGE.
 BIG DATATOOL KIT.
 TOWHOM DOES IT MATTER?
 CRITIQUES.
 BENEFITS.
 CONCLUSION.

3. This data is “big data.”

7.  BIG INVOLUME.
 BIG INVELOCITY.
 BIG INVARIETY.
 BIG INVERACITY.

8.  There are huge volumes of data in the world:
+ From the beginning of recorded time until 2003,
+ We created 5 billion gigabytes of data.
+ In 2011, the same amount was created every two days
+ In 2013, the same amount of data is created every 10
minutes.

9.  originated as a tag for a class of
technology with roots in high-
performance computing
 pioneered by Google in the early
2000’s
 Includes technologies, such as
distributed file and database
management tools led by the Apache
Hadoop project;
 Big data analytic platforms, also led by
Apache; and integration technology
for exposing data to other systems and
services.

10.  A/B testing
 Data fusion
 Crowdsourcing
 genetic algorithms
 machine learning
 natural language processing
 neural networks
 pattern recognition
 anomaly detection
 predictive modeling

11.  Research Community 
 Business Community - New tools, new
capabilities, new infrastructure, new business
models etc.,
 Private sectors.
 Government sectors.
 Media.

21.  Big risk on security and privacy.
 Challenges arise:expensive,need to spend a
lot to get it working.
 A lot of analyzing:uncover patterns,apply
algorithms,connections relationships.
 Big data is difficult to handle.

23.  BIG CAN BE SMALLTOO.
 BIG DATA LANDSCAPE IS HUGE.
 RIGHTTOOL FOR RIGHT JOB.
 ANY COMPANY CAN GET BENEFIT FROM
BIG DATA.

25. ANY QUERIES???