An indispensable Python : Data sourcing to Data science.

Data analysis echo system has grown all the way from SQL’s to NoSQL and from Excel analysis to Visualization. Today, we are in scarceness of the resources to process ALL (You better understand what i mean by ALL) kind of data that is coming to enterprise. Data goes through profiling, formatting, munging or cleansing, pruning, transformation steps to analytics and predictive modeling. Interestingly, there is no one tool proved to be an effective solution to run all these operations { Don’t forget the cost factor here 🙂 }.  Things become challenging when we mature from aggregated/summarized analysis to Data mining, mathematical modeling, statistical modeling and predictive modeling. Pinch of complication will be added by Agile implementation.

Enterprises have to work out the solution: “Which help to build the data analysis (rather analytics) to go in Agile way to all complex data structure in either of the way of SQL or NoSQL, and in support of data mining activities” .

So, let’s look at the Python & its eco system (I would prefer to call Python libraries as echo system) and how it can cover up enterprise’s a*s for data analysis.

Python: functional object orientated programming language, most importantly super

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