Why Big Data

1. Understanding Big Data

2. Overview
Why Big Data
Big Data Users
What is Big Data

3. Big Data
Big data is a popular term used to describe the exponential growth and availability of data, both structured and
unstructured. And big data may be as important to business – and society – as the Internet has become. Why?
More data may lead to more accurate analyses.
More accurate analyses may lead to more confident decision making. And better decisions can mean greater
operational efficiencies, cost reductions and reduced risk.

7. Big Data
Mainstream definition of big data as the three V’s of big data:

8. Big Data

9. Big Data
• Volume: Many factors contribute to the increase in data volume. Transaction-based data stored through
the years. Unstructured data streaming in from social media. Increasing amounts of sensor and machine-to-
machine data being collected.
• Velocity: Data is streaming in at unprecedented speed and must be dealt with in a timely manner. RFID
tags, sensors and smart metering are driving the need to deal with torrents of data in near-real time.
Reacting quickly enough to deal with data velocity is a challenge for most organizations.
• Variety: Data today comes in all types of formats. Structured, numeric data in traditional databases.
Information created from line-of-business applications. Unstructured text documents, email, video, audio,
stock ticker data and financial transactions. Managing, merging and governing different varieties of data is
something many organizations still grapple with.

10. Big Data
Let us consider two additional dimensions when thinking about big data:
• Variability: In addition to the increasing velocities and varieties of data, data flows can be highly
inconsistent with periodic peaks. Is something trending in social media? Daily, seasonal and event-triggered
peak data loads can be challenging to manage. Even more so with unstructured data involved.
• Complexity: Today's data comes from multiple sources. And it is still an undertaking to link, match, cleanse
and transform data across systems. However, it is necessary to connect and correlate relationships,
hierarchies and multiple data linkages or your data can quickly spiral out of control.

11. Big Data

12. Why Big Data ??
The real issue is not that you are acquiring large amounts of data. It's what you do with the data that counts. The
hopeful vision is that organizations will be able to take data from any source, harness relevant data and analyse
it to find answers that enable
1) cost reductions
2) time reductions
3) new product development and optimized offerings
4) smarter business decision making.

16. Big Data Ecosystem

18. Big Data platform typically works by storing data first into clusters , then process the data through
MapReduce workflows which executes by Mapping the input data through independent chunks processed
by appropriate algorithms, the output from Map phase then moves to Shuffle/Sorting phase & finally the
output from Shuffle phase comes to Reduce phase as input.
Typical Big Data MapReduce workflow:

21. Big Data users in Next Five Years

22. Big Data users in Private Sector
• Ebay.com uses two data warehouses at 7.5 petabytes and 40PB as well as a 40PB Hadoop cluster for search,
consumer recommendations, and merchandising.
• Amazon.com handles millions of back-end operations every day, as well as queries from more than half a
million third-party sellers. The core technology that keeps Amazon running is Linux-based and as of 2005
they had the world’s three largest Linux databases, with capacities of 7.8 TB, 18.5 TB, and 24.7 TB.
• Walmart handles more than 1 million customer transactions every hour, which are imported into databases
estimated to contain more than 2.5 petabytes (2560 terabytes) of data – the equivalent of 167 times the
information contained in all the books in the US Library of Congress.
• Facebook handles 50 billion photos from its user base.

23. Big Data users in Private Sector
• FICO Falcon Credit Card Fraud Detection System protects 2.1 billion active accounts world-wide. The volume of
business data worldwide, across all companies, doubles every 1.2 years, according to estimates.
• Windermere Real Estate uses anonymous GPS signals from nearly 100 million drivers to help new home
buyers determine their typical drive times to and from work throughout various times of the day.

24. Thank You..
Queries are welcome
Praneet Samaiya