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The Challenges Inherent in Big Data

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In recent years big data has become crucial to businesses. Access to larger pools of information and ever-evolving analytical tools that can be used to sieve through it all has offered companies the opportunity to learn more about everything from customer behaviour through to the efficiency of their own business processes.

However, it is still a relatively new industry and, as such, presents a number of challenges that need to be kept in mind at all times. Here we will look at a few of them.

Presenting the Data

The capability to analyse big data is really only the first step. If this data can’t be presented in an easily understood format that provides clear and usable information for senior leaders, it still can’t be used as effectively as it ought to be. Many have responded to this concern by examining ways to present data that is visually affecting and offers defined measures on which action can be taken. Modern big data analytics is as much about presenting information visually as it is discerning it in the first place. The challenge now is ensuring that these visual systems are able to maintain pace with the increasing volume of data that is available.

The Speed

Higher volumes of data also means more information is entering systems at a faster rate than ever before. This has the potential to overwhelm those who are not prepared for it, leading them to sifting through reams of information, even when it has been analysed. To counter this, it is crucial for organizations to define what they actually want out of the reams of data that is available to them. Questions need to be asked, such as “what do we need to improve?” and “what data will help us get there?” before the speed of incoming data can be adequately managed. A secondary concern is that this increased speed also places greater demand on physical systems, which means more needs to be invested into maintenance and upgrading.

Data Quality

Data services will always need to focus on presenting accuracy and timeliness. Information goes out of date very quickly and inaccurate data can lead to mistakes being made that cost businesses. These issues are magnified with big data thanks to the sheer volume of information. A proactive approach is required, which is why many companies are now turning to detailed data management systems that add an extra layer of analysis to the information.


Despite all this, the principle challenge of big data is the confusion that surrounds it. Many organizations are still unsure of what it refers to, which means they can’t take advantage of it. In short, big data is large volumes of data that can be used to identify patterns and trends, which is useful for businesses in gauging human interactions with what they are doing. Many businesses are absolutely inundated with data every day and this happened before the concept of big data materialised. However, thanks to improved computational power and analytics, this data can now be used to the benefit of businesses.


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