Page 117 - Data Science class 11
P. 117

assessing data




                                                                                       02










                        Learning outcome



                      2.1  Introduction                                    2.2  Story Versus Facts
                      2.3  Trial Assessment                                2.4  Activity-1






            2.1 IntroductIon

            In the previous chapter, you have learnt how the data science has evolved over time and built its ecosystem. If the
            ecosystem is to be built for a longer period, then ethical guidelines must be introduced to increase the confidence
            of the stakeholders about building up the business of their organisation. You also learned about data governance
            requirements to properly handle the business of any organisation.
            In this chapter, you will learn how to make distinction between story and fact. In general, there may be situations
            where you have to inspect a story of certain product and then be able to verify it with respect to certain facts. In
            pursuit of analysing the data quality, you shall further learn about Forecasting and Randomisation in the next two
            chapters.


            2.2 Story verSuS factS

            Facts are something that actually exist in reality and always represent the truth.
            Stories are a narrative; either true or fictitious, about things, ideas, beliefs, objects, products or services.
            Generally stories are made for the benefit of any organisation. These stories distort the facts about the idea, product or
            service in such a manner that the user or customer gets attracted. The fabricated stories may contain disproportionate
            weight either in favour or against the idea of things, products or services.
            Data analysis process follows certain phases such as business problem statement, understanding and acquiring the
            data, extract data from various sources, applying data quality for data cleaning, feature selection by doing exploratory
            data analysis, outliers identification and removal, transforming and creating data.
            Industry experts have found that proper decisions can be taken only if the data is understood in a proper way. So,
            for this Data story telling is the best technique to be adopted. This is because data scientists can use this tool to
            make their findings more relatable, memorable and impactful. Data storytelling is a combination of three important
            components, which is data, visuals and narrative. With this we can communicate complex information in a way that is
            accessible and engaging to the audience.




                                                                                              Assessing Data   115
   112   113   114   115   116   117   118   119   120   121   122