Five Problems with Big Data by Melanie Wieland

Are there problems pertaining with Big Data? Of course. Nothing in the world is perfect. Just like many issues, small amounts of Big Data are able to be managed, maintained, and verified with analytical means. However, Big Data is NOT small. Therefore, problems naturally have arisen. According to Nate Silver, the founder of data-driven journalism site FiveThirtyEight (owned by ESPN), at the HP Big Data Conference in Boston in August of this year, there are five problems accompanying Big Data. They are: where to put it, big bias, false positives, big complexity, and that’s not what I was looking for.


Where to put it?

Not only do you have to store and analyze big data, but you also have to factor in other aspects. Such as: buying hardware, cloud storage, latency issues, and how often you have to access it.


Big bias?

The more data that is available, the bigger the chance of a sway in statistics and/or information.


False positives?

Big Data “thinking fast” and not analyzing the data fully, can lead to false positives and faulty information/responses.


Big complexity?

The more data available, sometimes makes it harder to find true value from the data.


That’s not what I was looking for…

Big Data systems can attempt at creating alternative “faster” shortcuts. However, many times it’s not the answer or relevant/adequate information you are searching for.


All in all, the more information in Big Data, the bigger the problems are created from its complexity.

Work Cited

Butler, Brandon. “5 Problems with big data”. Cloud Chronicles. Network World, Inc. 1994-2015. 20 August 2015. <;


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