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PURE
The number of roles for data scientists has grown by 650% since 2012. About 11.5
Million jobs will be created by 2026 according to the U.S. Bureau of Labour Statistics. FACT

SOLVING PROBLEMS WITH DATA SCIENCE

Big data is different from traditional business intelligence tools. It can work with different data

forms and it is designed to acquire, manage and analyse huge amounts of data at optimum
velocity and gain accurate insight.
Big data is not about analysing large amounts of data but ensuring that the data is reliable,
auditable, and authentic as well as providing the correct insight. There are two approaches to
advanced analytics using big data:

DESCRIPTIVE ANALYTICS

It is a technique of interpreting historical data to derive insights and patterns. It tells us what
happened in the past. Stock analysis is an example of descriptive analytics because while
predicting stock data, the previous pattern is analysed and then that analysis is used to make a
prediction.

PREDICTIVE ANALYTICS

It uses machine learning to derive insights and predict possible outcomes. In artificial intelligence/
machine learning, the outcomes are probabilistic that basically help us predict what could happen.
Weather forecasting is an example of predictive analytics.

uiz Bee Which type of data is a combination of different types of data?
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TOOLS FOR DATA SCIENCE

Traditional statistical methodologies are used by data scientists which form the backbone
of machine learning algorithms. Deep learning algorithms are also used to generate robust
predictions. The following tools and programming languages are used by data scientists to analyse

data and draw insights from it:

R SCRIPTING LANGUAGE
R is a scripting language that is used for statistical computing and is widely incorporated in data
analysis modelling.

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