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    DATA SCIENCE

                      Data science is a field that studies data and the ways it can be transformed into valuable input and
                      resources to create business and IT strategies. This is a science that combines domain expertise,
                      programming  skills and knowledge  of mathematics  to  extract  insights  from the  large and
                      ever-increasing volumes of data collected by organisations.

                      WHAT IS BIG DATA?

                      Big data is a term used for any dataset that is large or complex to be processed by traditional
                      data management techniques such as RDBMS (Relational Database Management Systems). It
                      involves the methods of analysing large amounts of data and extracting knowledge from it. Data
                      science and big data have evolved from the traditional data management and are now treated
                      as distinct disciplines.
                      Any dataset can be considered as big data if it possesses at least one of the following four V’s:
                         Volume: Large volume of data
                         Velocity: Data movement at high velocity
                         Variety: Diversity in the types of data

                         Veracity: Data obtained from authentic sources

                                          Volume            Velocity         Variety          Veracity
                                       The Amount of Data  The Speed of Data  The Different   The Quality of Data
                                                                            Types of Data

                      CATEGORIES OF DATA

                      We come across different types of data and we need different tools to work on this data. Let us
                      take a look at the different types of data.

                      Structured Data
                      Structured data is highly organised and formatted to be easily searchable, typically in databases
                      using rows and columns (e.g., SQL databases). It follows a predefined schema, making it efficient
                      for querying and analysis. For example:
                         Inventory Management Systems: Structured data in inventory systems helps manage stock.
                        You can query the system to find out how many units of a specific item are available or when
                        to reorder based on stock levels.
                         Employee Records: In an HR database, employee information is stored in structured tables.
                        Each employee has a unique row in the table, and the structured format makes it easy to
                        generate reports on salaries, hire dates, or department staffing.

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