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Big data – interpreting unstructured information

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Big data – interpreting unstructured information

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One of the main points emphasized when describing big data is that it processes large volumes of unstructured data.

Some experts on this subject disagree with this. Log files and click streams are not actually unstructured, according to them. They lack clarity and have variable structures at times, they opine. It is a different matter, however, that even if this data was structured and stored traditionally, it is not possible for normal databases to handle them without incurring a lot of expenditure.

The ability to process the huge mass of information is itself is a challenge. If the processors of big data interact efficiently with users of information, it leads to more data being produced.

In addition, crucial information about consumers and their buying patterns is itself a vast piece of information that needs to be addressed.

Information contained about customer behavior in detailed surveys, emails, forums, and in other ways is still unstructured data. It is one of the most effective methods of evaluating behaviors.

In fact, there is not much of a difference between data that is structured and one that is unstructured. Structured data gives you information as to what type of transaction took place and where. Meanwhile, unstructured information explains why certain things took place. The incapability to process and evaluate unstructured data prevents many big data analysts from giving us a clear and a concise picture.

Gathering unstructured data and then dissecting it is a major challenge. Another problem is human perceptions, which are diverse. They also vary from one geography to another and are reinterpreted over time. Gathering unstructured data and understanding what it means needs the intervention of experts and the right software.  

Major threat to assess big data is due to the speed at which we receive information and at what rate it is possible to evaluate it in meaningfully. To top it, its complexity is another major challenge that needs addressing. Most analytics would need study and ability to relate one piece of information to another across the total setting.

Service providers in the unified information access (UIA) space have gathered and analyzed unstructured data over the years. They offer technology for supporting infrastructure of big data by inserting unstructured data into an analysis model, which is submitted in perspective to get rid of the missing dots in business applications and business procedures.

Included in the technology are the necessary text analytic competencies, which help convert unstructured data into intelligible information that can be used.

The UIA service providers, thus, plug the gaps existing in big data by providing volume, variety, velocity, etc.

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