5 trends that are changing how we do big data
Source: Derrick Harris
In just a few years, big data has turned from a buzzword and concept best left for large web companies into a force that drives much of our digital lives. Here are five technological trends that will change how data is processed and consumed going forward.
It’s time to rethink the who, what, where, why and how of big data. After a surge of important news in the past couple weeks, we’re approaching a period of relative calm and can finally assess how the space has evolved in the past year. Here are five trends shaping up that should change almost everything about big data in the near future, including how it’s done, who’s doing it and where it’s consumed. Feel free to share the trends you’re seeing in the comments.
The democratization of data science
The amount of effort being put into broadening the talent pool for data scientists might be the most important change of all in the world of data. In some cases, it’s new education platforms (e.g., Coursera and Udacity) teaching students fundamental skills in everything from basic statistics to natural language processing and machine learning. Elsewhere, it’s products such as 0xdata that aim to simplify and add scale to well-known statistical-analysis tools such as R, or, like Quid that try to mask the finer points of concepts such as machine learning and artificial intelligence behind well-designed user interfaces and slick visual representations. Platforms such as Kaggle have opened the door to crowdsourcing answers to tough predictive-modeling problems.
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