Data Rich, Information Poor


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In this day and age, information is vital for companies and is used continuously at all levels of the organization, so much so that as technological capabilities for collecting and analyzing data improve, companies react with proportional demand. The standard pattern is of colossal data integration projects which unify internal systems, external systems and the data of third-parties and providers. These, in turn permit companies to submit queries and manage all of their information from a single point, in systems that come under the discipline of Business Intelligence, and attempt to control what we not refer to as Big Data.

However, the data is (or at least should be) only the first step. Just as quantities of data available to us are growing, so too is the understanding of managers that being rich in data but poor in information, still leaves you desolate. Therefore, in terms of transforming our available data into something actionable, one wonders if we have improved or worsened the situation.

There is no doubt that our abilities to access data are much greater today. The majority of systems are prepared to make information available at any given moment, and to be integrated into other platforms. From the data that we find in the original repositories, to the tool to exploit them, analyze them and visualize, we them have experienced continued improvements. From the technical and usability point of view, we can confirm that the velocity their development has greatly advanced, and will presumably continue to grow among a similar line.

On the other hand, it might be thought that the tools have exceeded the capacity of organizations to really take advantage of them. We often have more data than we know how to, or can use. Often we are victims to our own misconceptions and struggle to focus on only the valuable and relevant data, after all: if we can have all of this information- why reject it, right?

The problem resides in that the majority of companies mainly invest in and focus on implementing complex and costly integration systems, but forget the most important step: to provide the organization with the capabilities necessary to exploit this information in an adequate form and therefore give value to the investment.

This then opens a gap in the organization: while certain levels are now more satisfied with their capacity and ability to access and automate data thanks to the new tools and its possibilities, in other levels it seems as if translating this avalanche of data into useful information, which will help them to make good decisions is just as complex, or perhaps more so than before. This may be due to the following problems:

  • Complete solution: in order to use the data in the most effective form it is critical to understand it, its origin and the form in which it is collected, in order to be able to provide it in an actionable form.
  • Lack of data confidence: general distrust in data may occur where weaknesses in systems are evident. Enhanced by the complexity of these systems required to bring together tons of information, undertake massive tasks daily and which need a great amount of maintenance work
  • “Paralysis by analysis”- where the cost of making a decision is greater than the benefit that making the decision will bring us, we may fail to act. This is the result of over-analyzing the results of problems encountered.

Unfortunately, the largest repositories, more data and better tools will not be able to solve these problems, and in some cases it is probable that they will accentuate them.


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Víctor Pérez

Degree in Computer Science and product manager at MediaSQ, technology enthusiast and passionate about Web Analytics ecosystem: tools, techniques and methodologies.

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