A BRIEF HISTORY OF DATA

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 When you generally think about words like data, analytics , and analysis it is very easy to visualize big computers, engineers, or even bankers- you wouldn’t imagine a doctor. Sorry if the previous statement sounded a little presumptuous to me, but it needed to be used as it would set a good opening for this blog. Today as a part of analytics in real life we will attempt to take a closer look at analytics from a medical perspective. The use of data in medical research is probably the most critical function in analytics. This ranges from establishing what are acceptable ranges for key blood parameters to identify the pattern in the spread of viruses- a recent conversation about the R-value of Covid is one such example. The collection of data and its use in medical science can be the subject of many exciting blogs. So let’s look at some examples of what are some of the most common data models used in medical science: Predictive analytics Probably one of the most important models in ...

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  REPORTING Vs ANALYTICS: The chessboard has 32 pieces and 64 boxes and given the scale of production of chess boards, it can be assumed that there are quite a few people in the world who would know how the pieces move and how chess is played. However, there are only a few people who can really play chess in a manner that is worth watching. We are going to wildly extrapolate the same thing to working with data. Yes, there is an enormous amount of data and there is a sizable population of the workforce across different industries who have the word analyst in their designation. So the question is what really differentiates a report from analysis and what differentiates an analyst from a data cruncher/visualizer. This our experience tells us is a challenge that dogs the analytics industry. The ability to write a piece of SQL code makes you an analyst as much as having a telescope makes you an astronomer. We profusely apologize for the overtly critical and pompous tone of this blog- bu...