Considering The Limitations of Big Data

 In Article

Everybody around us is always talking about the opportunities that big data presents and the new world of opportunities it creates – and for a good reason, too. As we have clearly recognised the value of big data before, we strongly support it and believe it is the future of analytics. There is, however, another side to the world of big data: namely, drawbacks and limitations.

Few like to think about the negatives of such a powerful tool, but to take the highest possible advantage and work it to the very maximum, it is useful to know where its weaknesses lie. Such a procedure could save the user time and resources, as well as predict how big data tools will behave and be better prepared for the glitches, blind spots and complications that will eventually, no matter how small, happen.

One of these is incorrect correlations. Whilst big data tools correctly calculate, analyse and show correlations, not all of them are significant and it is up to the interpreter to deduce whether the result is useful or not. An example of this is analysing conditions when AI functions the fastest, and finding a positive correlation between the speed and times of day: this doesn’t necessarily mean AI is faster at night because of the time, but because the network is less busy.

Another problem is whether the very large volume of data can be transferred efficiently, i.e. quickly and accurately while also making sure it is secure throughout the whole process. Processing many different types of files can also be complicated and not all platforms are compatible with all types: because of this, data can sometimes become muddled and unreadable or, in worst cases, the files can accidentally be destroyed.

Furthermore, big data has the inability to provide complete answers. Even using the most elaborate, developed tools to analyse big data, it cannot answer the question “why” and only shows the symptoms rather than the precise causes. As such, it creates more work and a further need to analyse the received data, which not all companies are prepared for.

Due to such limitations of big data any company dealing with it should be aware of both its advantages and disadvantages. In Dashboard’s case, we have considered these from the very beginning, which allows our analytics team to do an ‘above and beyond’ job with the data we handle.

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