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                    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?
                                          _________________________________________________________________







                           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:








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