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Unstructured Data
Unstructured data lacks a predefined format or organisation, making it more difficult to search
and analyse. It includes diverse data types like text, images, audio, and videos. For example:
Natural Language Data: It is a type of unstructured data and is very difficult to process. The
meaning of the same word changes depending on the mood of the speaker. For example, the
same word could have two different meanings when spoken joyfully or when uttered sadly.
Audio, video, and images: This type of data is the biggest challenge for data scientists because
finding objects and patterns turns out to be a challenging task for computers.

Semi-structured Data
Semi-structured data contains elements of both structured and unstructured data, with some
organisational properties but no rigid schema. It often uses tags or markers to separate data
fields. For example:
Graph-based or Network Data: The data that is generated from a relationship or connections
between objects is called graph-based or network data. Such type of data is found on social
media websites and is a natural way to represent networks.
Streaming Data: Streaming data can take any of the forms. It is not a different kind of data, but
it flows into the systems instead of being loaded into a data store in batches.

WHY DATA SCIENCE?

Data has become an important fuel on which industries function today. For companies to
grow and flourish, they need data to be analysed. This analysis then helps them measure their
performance and gauge the expectations of the market. Healthcare industries also use data
science to recognise microscopic tumours and deformities at an early stage of diagnosis. The
person responsible for dealing with data in order to assist companies in making proper decisions
is called a data scientist.

Tick ( ) if you know this.
▶ Big data refers is a term used for large dataset that is complex and is to be processed by
traditional data management techniques.
▶ Different types of data include structured, unstructured, semi structured, etc.

ROLE OF DATA SCIENTIST

A data scientist is someone who uses data sets to create a hypothesis and then works on the
data set to analyse the data, interprets it and makes sense of it. A data scientist is responsible for
dealing with all types of data. He/she uses various tools and practises to recognise patterns within
the data.

Introduction to SDGs and Data Science 119