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    DATA VISUALISATION

                                       3                                        AND ANALYSIS

                      PRIMARY PREVIEW

                         Organising and Visualising Data for Smarter Decision Making
                         Understanding Data                                Simple Methods of Data Collection
                         Data Sources                                      Understanding Digital Data
                         Data Formats and Storage                          Data Visualisation
                         Interpreting Data                                 Data Analysis
                         Thinking Like a Data Analyst

                      Every day, you come across information such as test marks, weather updates or the number of
                      steps counted by a fitness band. These are all examples of data, which play an important role in
                      your daily life.

                      In today’s digital world, data surrounds you. Whether you’re using a mobile phone to message
                      friends, browsing  the  internet  to  research for a project,  shopping  online  for new clothes  or
                      checking the weather to decide what to wear, data is being created. Schools track your marks and
                      attendance, hospitals monitor patients and scientists collect measurements during experiments;
                      all of this is data. However, data alone doesn’t provide much value. It becomes truly useful when

                      it is organised, understood and presented in a clear and meaningful way.

                      ORGANISING AND VISUALISING DATA FOR SMARTER DECISION MAKING

                      Imagine you are the captain of your school’s cricket team. After a match, you have a detailed list
                      of everything that happened during the game, such as:

                       Every ball bowled: This shows which bowler bowled each delivery, the number of balls bowled,
                         wickets taken or runs conceded.

                       Every run scored: This tracks how many runs each batsman scored in each over, including
                         singles, boundaries or extras.

                       Every catch dropped: This records the catches that fielders dropped, which could have led to
                         dismissing a batsman.
                      This long list of information is called raw data. It is like a collection of facts, but without much

                      meaning on its own.

                      44         Artificial Intelligence (CT & AI)-VII

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