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Data  literacy  is  essential  because  it  enables  individuals  to  make  informed  decisions,  think  critically,  solve
                 problems, and innovate.

                                                 Data                              Literacy



                                                                          Ability to read, comprehend,
                                          Raw facts or figures
                                                                           analyse, and communicate.


                                                  Data literacy is the ability to understand,
                                                interpret, analyse, and communicate with data.



                                                                                #Digital Literacy

                           Video Session

                      Scan the QR code or visit the following link to understand the Data Literacy:

                      https://www.youtube.com/watch?v=yhO_t-c3yJY
                      1. What are the takeaway from the given video?



                      2.  What is the definition of data and data literacy, and how do these concepts impact our
                        ability to understand and use information effectively?









                         Data Pyramid and Its Different Stages


                 The data pyramid is a conceptual model that illustrates the hierarchical structure of data processing, depicting
                 the progressive transformation of raw data into actionable wisdom. It starts with raw data, which initially has
                 no use. Through processing and analysis, this data evolves into meaningful information, then knowledge, and
                 ultimately wisdom. This transformation enables informed decision-making and a deeper understanding of the
                 world around us.






                                                                         Wisdom       Why?



                                                        How?            Knowledge


                                                                       Information             Who? What?
                                                                                             When? Where?


                             Raw Data and Information                      Data

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