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Managing a business enterprise is impossible if the manager is not at ease with dealing with data. While soft skills and EQ are important, when push comes to shove it is data on the table that really matters. Data driven decisions are the backbone of any efficient enterprise.
It is said that data is the new oil because of its intrinsic value. This is why the most powerful companies on the planet, like Google, Facebook, Netflix, Amazon owe their immense clout to the huge amount of data that they have accumulated about people and their behaviour. Gathering, storing, managing these multi-terabytes (or more) of data is loosely referred to as Big Data. But using this data to draw inferences about the past and more importantly making predictions about the future is Data Science.
Managers in the past were not unaware of or indifferent to the importance of data. Many of them have been using spreadsheets like Excel to assist them in their daily work. However the volume of data in the current business ecosystem is so large that spreadsheets are no longer adequate. Spreadsheets is a legacy technology, almost a relic, from an era that businesses have left behind. This technology simply cannot scale-up to handle the kind of Big Data that today's internet based businesses generate on a daily basis.
Data Science uses many next generation tools to handle Big Data and Python is one such tool that is very widely used today. This book will help managers who do not have a background in computer programming to learn Python to the extent that they will be able to use it in their daily work. The book takes a totally hands-on approach based on the Google Colab platform and the only requirement is that the reader-user must have a computer connected to the internet and the Google Chrome browser. Readers will also walk through two detailed exercises that will demonstrate how these tools can be used to analyse retail sales data and to get started with basic technical analysis of share prices, using NSE data.