Fortnite dives deep in data lakes - and others should too

By Folake Dosu  |  October 10, 2018

fortnite-data-lakes

Through user-friendly analytics, data lakes are becoming more accessible and democratic for those less technically inclined.

Talk of video game sensation Fortnite is pretty much impossible to escape (and now, this website is no exception). With millions of players comes millions of data points and the game’s parent company, Epic Games, has the Herculean task of processing and analyzing them.

As Forbes reports, Epic Games achieves this by using a data lake, which their director of platform Chris Dyl confirmed during a recent AWS summit. While data lakes are sometimes maligned as “unmanageable data swamps,” this reference validates their value to organizations. Forbes reveals that a survey of hundreds of organizations found that most are bullish on data lakes, particularly in its accessibility to non-technical users. The understanding is that democratizing data gives them a competitive edge.

While data lakes are not a new technology, traditionally they have been intimidating to less technically inclined members of an organization, such as managers and field employees, who need out-of-the-box data analytics solutions.

Markets and Markets believes the data lakes market could reach nearly $9 billion by 2021, up from only $2.5 billion in 2016.

Data lake technology has progressed to being practically inscrutable for anyone who is not a data science PhD to workable for business users with math or SQL experience. The survey suggests that data lakes have reached a level of usability: nearly two thirds of respondents reported that they felt business users can use tools to explore data to get the views they want, and half said business users can blend data sets located within or outside the lake. Meanwhile, the market seems to echo their sentiments: Markets and Markets believes the data lakes market could reach nearly $9 billion by 2021, up from only $2.5 billion in 2016.

Data lakes will not reach their full potential at organizations without closing the usage gap for non-technical business users. Accessible analytics is the answer and these three tips can help make that happen:

  • Avoid moving big data. Not only is that a costly time-waster, but democratizing data requires analytics and other tools to stay with the data.
  • Getting rid of your existing security model would complicate implementation or result in data loss. Instead, seek unified security models and tools.
  • Even though data accessibility is with business users in mind, think from the developer’s point of view. Thanks to Rails, building apps is easier than ever. Build apps instead of reports for democratized data. 

Champions of democratized data should prioritize data lakes in their organizations. Data lakes permit data analysis of all forms as well as enable machine learning, search, streaming, batch and BI use cases independent of special-purpose systems.
 

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