9 tools that make data science easier

New tools bundle data cleanup, drag-and-drop programming, and the cloud to help anyone comfortable with a spreadsheet to leverage the power of data science.

6 tools that make data science easier
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The math of data science is complex and powerful, a daunting hurdle for anyone who wants to unlock the insights it can offer. The unavoidable housekeeping and basic maintenance that go along with it, though, have never been easier. New tools and better support software are revolutionizing the discipline by delivering assembly lines for data that are ready to pump out the answers we seek.

Just as standardized parts helped launch the industrial revolution, data tools vendors have produced a collection of powerful, adaptive analytical routines, and they’ve standardized the interfaces, making it easier to build custom pipelines out of these interchangeable tools.

Data scientists used to wring their hands preparing data for analysis by crafting custom routines in Python, Java or their favorite language so that sophisticated statistical tools in R or SASS could do their job. The marketplace now offers tools that bundle together several hundred well-engineered routines into a package that does much of the repetitive and unpleasant data cleanup and standardization for you.

These new tools open the opportunity for anyone who’s comfortable working with a spreadsheet. They won’t make all prep work disappear, but they’ll make it easier. There’s less need to fuss over data formats because the tools are smart enough to do the right thing. You can often just open the file and start learning.

The tools also unlock the cost-saving power of the cloud. Data scientists no longer need powerful computers to crunch big data sets. Instead we can rent even bigger, faster machines in the cloud by the second, increasing processing speed while saving money by returning the hardware to the pool when the reports are done.

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