Trifacta’s Wrangler tool is challenging the traditional methods of data cleaning and manipulation. Though, Microsoft excel is paid but you can still try various other spreadsheet tools like open office, google docs, which are certainly worth a try! No matter how many tools you know, excel must feature in your armory. which are powerful enough to inspect data from all possible angles. It supports all the important features like summarizing data, visualizing data, data wrangling etc. With larger than ever community support, tutorials, free resources, learning this tool has become quite easier. Even today, most of the problems faced in analytics projects are solved using this software. If you are transitioning into data science or have already survived for years, you would know, even after countless years, excel remains an indispensable part of analytics industry. These tools doesn’t require you to code explicitly but simple drag – drop clicks do the job. Now a days, ample of tools are available in the market which are free & quite interesting to work with. I have written this article to help you acknowledge various free tools available for exploratory data analysis. The most important skill to master data exploration is ‘curiosity’, which is free of cost yet isn’t owned by everyone. You can’t make predictions unless you know what happened in the past. Do you know why? Because, I could have chosen one of several non-coding tools available for data analysis, and could’ve avoided the suffering.ĭata exploration is an inevitable part of predictive modeling. My situation was similar to a guy who didn’t know swimming but was manhandled into deep ocean, who somehow saved himself from drowning but ended up gulping lot of salty water. Sometimes a lot more than one can ever think! Because I had never ever coded even in my entire life. It’s just a matter of time until we discover it and start believing in ourselves. We all have limitations, but should we stop there? No. Some of these tools are even better than programming (R, Python, SAS) tools.Īll of us are born with special talents. Some of them are also quite popular like Excel, Tableau, Qlikview, KNIME, Weka and many more.Plenty of open source and proprietary tools exist which automate the steps of predictive modelling like data cleaning, data visualization, etc.A coding background is not mandatory for data analysis and predictive modelling.

Tools for data analysis