Big data refers to extremely large and complex datasets that are difficult to process using traditional database management tools. It is characterized by its volume, variety, velocity, and veracity. Big data is made up of both structured and unstructured data, with 90% being unstructured data from sources like social media posts, emails, and website clicks. Its volume is growing enormously, with 2.5 quintillion bytes of new data created every day.

1. Big Data

2. It wasn’t very long ago when a
terabyte was considered large.

3. But now, that seems like a rounding error.
Today, we create 2.5 quintillion bytes
of data every day.

4. We’re creating so much data so
quickly that 90 % of the data in the
world today has been created in the last
2 years alone.

5. Ok Got it..
So, What is Big Data??

6. Big data is a collection of data sets so large
and complex that it becomes difficult to
process using on-hand DBMS tools or
traditional data processing applications.

7. Big data is difficult/impossible to work in
DBMS packages,

8. Instead it requires "massively parallel
software running on thousands of
servers".

9. Big data is made of structured and
unstructured information.

10. 10% are structured and 90% are
unstructured like
emails, videos, facebook posts, website
clicks etc.

11. Four Vs of Big Data

12. Volume, Variety, Velocity
&
Veracity

13. The volume of data grows, we can learn more – but only
if we uncover the meaningful relationships and patterns.
Volume

14. From the endless streams of text data in social
networking and geolocation data, to structured wallet share
and demographics, companies are capturing a more
diverse set of data than ever.
Variety

15. The business is accelerating.
The data is coming faster than ever.
Data shelf life is short.
Velocity

16. Veracity addresses the inherent trustworthiness of data.
The uncertainty about the consistency or completeness of
data and other ambiguities can become major obstacles.
Veracity

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Created / Compiled / Curated By
Uttam Shrestha
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