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Why Automate Data Analytics?

Updated: Jun 26, 2018



In today’s business world, big data is in charge. Companies are diving into untapped markets, boosting revenue, and managing their hiring and growth rates with increased perfection, all thanks to big data analysis. But big data is just that, big. It can all get to be a bit much sometimes and the next thing you know, your company’s data scientists are drowning in numbers and spreadsheets, unable to see the big picture.


It’s time to go automatic.


Of course you’ll still want a few sets of real, human eyes on any project, but utilizing some automated data analysis tools can work wonders for your results. Think of it like the advent of the modern cash register. There’s still an employee at the helm, but they’re no longer manually typing in meal prices and calculating tax. There’s a system doing that for them.


So what are the basic benefits of automated data analysis?


  • All access pass


Automating you data analysis means everyone in your company who needs to see it will have simultaneous access to data information. There’s no waiting for data or miscommunications.


  • Data sharing


It’s important that data from all departments be considered during analyses. If data is dealt with manually, you’ll often find different areas of a company will sort their own data separately. With this sequestering of data, you’re unlikely to get the complete picture, and it’s easy to make huge policy mistakes when you’re making decisions half-blind like this. Your big data is essentially useless in this scenario. Automated solutions do away with the needless spreading out of data sources.


  • Error reduction


This one is simple. The fewer human hands that touch a data project, the lower the odds of multiple errors popping up. People are only human.


How to get started


It’s wisest to partner with an analytical company if you’ve not already. There are a lot of automated analytical tools out there of varying cost and quality. A company like qbix will have access to and working knowledge of all the best tools for keeping your data in check. They’ll also be able to aid you in error reduction and tapping into previously unused data.


Incomplete or poorly-optimized data is almost worse than no data. Relying exclusively on manual data interpretation can lead a company to the wrong conclusions and prevent analysts from seeing all the information the data has to offer. Incorporating an automated data analysis into your company’s data plan should be a top priority in today’s data-driven market.

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