Big Data

INTRODUCTION:

“Big Data” has become an extremely popular term, due to the well-documented explosion in the

amount of data being stored and processed by today’s businesses. Big data is about more than

just the “bigness” of the data. It may be defined as:

“Big Data is too large amount of data to manage using typical database software tools.”

2012 - 2.7 Zettabyte (10^21)

2020 - 35 Zettabyte (10^21)

Per day

Twitter- 7 TB

Facebook- 10 TB

FACTORS:

BigData

Volume

Velocity

Variety

Value

WHERE SEEN:

Data warehouses

OLTP(Online Transaction Processing)

Social networks

Scientific devices

FILTERING BIGDATA EFFECTIVELY:

Focus on important pieces of data.

LOAD

Usable data loading

TRANSFORM

Usable set of data

EXTRACT

Raw feed of data

WHY BIGDATA:

Taking better decisions.

Product arrangement

Locating the dead zone.

Generates financial values across sectors.

RISKS:

Will be so overwhelmed.

Costing.

Privacy.

RISK MITIGATION:

Need the right people & solve the right problems.

It isn’t necessary to handle 100% data all the time.

Formulate legal regulations.

CONCLUSION:

Banking industry was very hard to handle even a decade ago. But there are thousands of banks

now. So, the volume of “Big” will change but Big Data will continue to evolve.

Acquire

Organize

(Distill) Analyze

Decide