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ARTICLE

Scientific and research data ticker data and financial transactions.

History of Big Data As time has passed big data has included 5 Vs:

Big data refers to data that is so large, fast or complex that
it’s difficult or impossible to process using traditional
methods.

The act of accessing and storing large amounts of
information for analytics has been around for a long time.
But the concept of big data 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

Big

Data Types of Big Data
Velocity Variety Big Data is essentially classified into three types:

Structured Data
Unstructured Data
Volume. Organizations collect data from a variety of Semi-structured Data
sources, including transactions, smart devices, industrial
equipment, videos, images, audio, social media and more. Structured Data : Structured data is highly organized and
In the past, storing all that data would have been too costly thus, is the easiest to work with. Its dimensions are defined
– but cheaper storage using data lakes, Hadoop (open- by set parameters. Every piece of information is grouped
source software framework for storing data and running into rows and columns like spreadsheets. Structured data
has quantitative data such as age, contact, address, billing,
applications on clusters of commodity hardware) and the
cloud have eased the burden. expenses, debit or credit card numbers, etc.

Unstructured Data: Not all data is structured and
Velocity. With the growth in the Internet of Things, data
streams into businesses at an unprecedented speed and wellsorted with instructions on how to use it. All unorganized
must be handled in a timely manner. RFID tags, sensors and data is known as unstructured data. Unstructured data is
stored in data lakes. Data lakes preserve the raw format of
smart meters are driving the need to deal with these
torrents of data in near-real time. data as well as all of its information. Data lakes make data
more malleable, unlike data warehouses where data is
Variety. Data comes in all types of formats – from limited to its defined schema.
structured, numeric data in traditional databases to
Semi structured Data: Semi-structured data falls
unstructured text documents, emails, videos, audios, stock
26 | 2022 | AUGUST | BANKING FINANCE