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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.

                               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. It is an interpreter-based language and possesses the features of an object-
                     oriented programming language.

                     STRUCTURED QUERY LANGUAGE (SQL)
                     SQL is used for managing and querying data stored in databases. Extracting information from the

                     database is the first step towards data analysis. It is a flexible and dynamic language and is used
                     in extracting, managing and manipulating data.

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