Data is critical to decision making in the new world of Information Technology. As it is, the real currency of the modern age is information. This means that data, from which we derive information, has become the driving force of commerce. Yet there is a big assumption that is being made here; that data equals to information. This assumption is not always true. If data is not set within a certain context, we cannot learn anything from it and therefore it is useless. Let’s delve a little deeper into this issue of data and context.
Growth Of Big data
In our rapidly evolving world, there is a push to collect more and more data. Big companies have come up with the sole purpose of collecting and selling data. Known collectively as big data, these companies use both legal and illegal methods to collect personal data and may sell them to advertisers and other interested parties. The growth of this industry has focused more on the quantity of data that is churned out and neglected an important facet of the context of the data.
Lots of Data, Little Context
Here is an example of how context matters in data. A real estate company can acquire data that shows that a certain number of people frequently visiting a certain area. This data can be easily collected from, among other sources, people who are not using the right tools to secure their data. On the face of it, the data would show the real estate company that it has a large potential market in the area.
The catch however is that this data might not show how many of those people are earning an income that would allow them to purchase real estate properties from the said company. It might also not show how many of those people already own properties and thus might not be interested in acquiring more. There could even be people in the data pool who have no interest in buying property in the location.
In other words, without refining the data to give context, that information is useless to the company. At best, it will lead to a wasteful, untargeted campaign with very low conversion rates.
Data Without Context Is Not Useful
The problem with the rush for big data today is that it focuses on quantity rather than quality of the data therefore negating its usefulness. Worse, this drive for more and more data, creating a backlash that diminishes the potential that data has for creating better solutions to global problems. In other words, not only is it not delivering now, it is messing up the potential for data to deliver in the future.
To make data useful, we have to start focusing on the quality of the data. Data companies need to offer more context to the data they give so that accurate and useful information can be distilled from it.
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