Introduction to Big Data

1. BIG DATA
SUBTITLE

2. What is Big Data?
• It describes large volume of data both structured and
unstructured that inundates a business on a day-to-day
basis.
• Big data can be analyzed for insights that lead to better
decisions and strategic business moves.

3. History
• The concept gained momentum in the early 2000s when
Industry Analyst Doug Laney articulated the now-
mainstream definition of big data as the three V's
• Volume
• Velocity
• Variety

4. Contd..
• The concept gained momentum in the early 2000s when
Industry Analyst Doug Laney articulated the now-
mainstream definition of big data as the three V's
• Volume
• Velocity
• Variety

5. Contd..
• VELOCITY: Data streams in at an unprecented speed and
must be dealt with a timely manner. RFID tags, sensors
and smart metering are driving the need to deal with
torrents of data in near-real time.

6. Contd..
• VARIETY: Data comes in all types of formats- from
structured, numeric data in traditional databases to
unstructured text documents, email, video, audio, stock
ticker data and financial transactions.

7. Uses of Big Data
• Public sector sevices.
• Healthcare services.
• Banking sectors.
• Fraud detection.
• Learning services.
• Transportation services.
• Insurance services.
• Industrialized and Natural resources.

8. IoT and Big Data
• Big Data and the IoT work in conjuction.
• Data extracted from IoT devices provides a mapping of
device interconnectivity.
• IoT is also increasingly adopted as a means of gathering
sensory data, and this sensory data has been used in
medical and manufacturing contexts.