Let us begin with a short tale; we hear that Data Scientists tell stories through data. But have you ever imagined how they arrive at that? Data Science is a field that uses different processes and algorithms to extract valuable insights from tons of data.
Companies and organizations get confused about how data science applies to them. The question often heard is “So if I give you all this data, what can you give me?” In reality, this should be the other way round “What is it that you as a company want to find using this huge data?”, “Are you looking for qualitative or quantitative results?” and most importantly “What are your Key Performance Indicators (KPI’s) ?”.
If we get an understanding of the above questions, we can head right into analyzing the data. The first step would be to understand how we got this data and try to find out the methods used to extract the same. Then break it down to see all the information gathered. This data is then cleaned (unwanted information is removed) and passed through suitable algorithms, where we have different parameters to check the credibility of the data received.
After many tests, the data starts to make sense from an analytical point of view. The body of the story is still scattered at this point, so to organize, the framework is drawn using visualization tools. And now we are ready to tell the tale or insights from the data received.
Why do businesses need this? In this competitive world to stay at the top, you need to know where you are and how far you can go. Data Science helps figure these complex questions out to an extent through forecast models and prediction models. Choosing the right algorithm is an integral part of the whole process.
Data Science is evolving as you read this; a lot of tests and trials done before they are published there. It is fascinating to see what tales’ data can unfold.