Is data really the new oil?

Rian Durandt, HOD Business Intelligence & Data Analytics at Digiterra

Everyone has that drawer at home where they throw everything that doesn’t have a place – like old USB cables, coins, batteries, keys they don’t use. Big data has become the digital shoebox equivalent to that drawer.

This means we are now data-rich, but information poor. Across the world, businesses are drowning in data as it continues to grow at a rapid and unprecedented pace.

The global datasphere is constantly expanding and predicted to increase another 61% by 2025.

The beginning of the big data era saw a “whose is bigger than whose” competition erupts in the marketplace due to the misconception that having more data must result in better decisions. However, it’s not the data itself that results in good business decisions, but rather the information gleaned from that data.

The difference between data and information

Data is simply a set of values, figures or statistics. If we take two measurements, for example, 22 and 23, that’s data.

Information, on the other hand, is data put into context. Looking at the first numerical value, 22, we can give it context by noting that this measurement was recorded on a specific date, let’s say the 7 January 2010. We can then give it additional context, for example, a measurement of temperature, and give it geographical context, say London.

The data now becomes information as we are able to interpret it and draw a conclusion about what it means – it might be that this temperature in that specific location is unorthodox for that time of year.

But, information can also be perceived incorrectly if not enough context is applied to the data. Adding new context, such as the fact that the unorthodox measurement of temperature was actually recorded inside of an office and not outside on the street, completely changes the meaning of the information.

An ordinary business person could maybe put two or three pieces of context to an information set – when, what, where, who – but they likely don’t know enough about all of the data that surrounds them to put it neatly into an information set.

So, yes, we are data-rich, we start all of our data warehousing or business intelligence projects by gathering vast amounts of data, but we don’t necessarily have the context or the background knowledge around that data to inform decision-making.

What is good data?

With companies throwing any and all kinds of data into a shoebox of miscellaneous facts and figures, how can we stop being digital hoarders and sort the wheat from the chaff?

Well, organisations need to evaluate whether the cost of storing all of that data is greater than the value that could one day be derived from that information. However, it’s not always easy to know whether today’s data will be useful information tomorrow.

I’m not saying that organisations should not collect data, they can collect all the data they want to, but here’s the caveat – organisations should only collect data as long as it can be demonstrably useful to that organisation at a specific point in their business process.

This means they must not only be able to point out when and where they will be using that data, but also who would be using it and how that person is going to use it to add value. If a business can quantify how much value there is in a specific set of information, they’ve hit the jackpot.

If businesses don’t have the right information at the right time, decisions are made with “gut feelings”. But, if they could access the right information at the right time by looking at the business process, mapping the data that is required at that specific time, then filling those gaps, organisations would finally unleash the full potential of their data. And that’s how data becomes information.

At Digiterra, our approach to building a Business Intelligence solution is not about bringing all a business’ hobbled masses and then figuring it out. We start with the business process – what is it that company really does? Who within the company is doing it and what is that person using to make it happen?

When we map the data that a business needs at each point of its processes, we shall have the right data at the right time in an understood context that business can act on to create value.