The term ‘Big Data’ has been gaining more and more popularity over the past few years. Nonetheless, in what ways is this mechanism different from ordinary data sets? What are the benefits of its implementation? What are the risks?
A company needs to adapt to the market in order to function smoothly and grow. You cannot go about this blindly, as this is the direct path to failure. For this reason, entrepreneurs have always collected and analysed data. Based on complete calculations of production costs, they were in a position to optimise expenses later on, to determine margins independently for various goods, taking into account the demand. In the age of the internet and the socio-economic changes occurring faster than they ever have before, it has become obvious that selective data collection and manual analysis, even using computer software, is not enough.
Big Data means a set of huge amounts of unstructured data, too large and complex to be analysed with conventional tools. Modern technologies such as artificial intelligence are used for processing here. To put it in a nutshell, unlike the previous solutions focused on recording selective matters such as demand for specific products over successive months, with Big Data you have a stream which also includes seemingly irrelevant information. This allows you to find patterns and relationships between various, seemingly unrelated factors. Smartphones, various sensors or wearable devices are used to collect such enormous amounts of data, to name but a few.
- Rapid acquisition of knowledge. An analysis of large amounts of data from various sources allows you to find specific patterns that you can then use to maximise profits. Conventional research into customer behaviour and motivation requires more time than one conducted using Big Data. Until now, data had to be extracted manually first (e.g. through surveys). Today, a smartphone connected to the internet does this automatically. It collects and sends back data about the age group to which the buyers of services or goods belong. Then, you don’t need to manually scan through sheets for analysis, which also consumes time – with the help of AI algorithms, it is done in real time.
- A broader view of the examined issues. The amount and type of data collected through the various sensors is almost unlimited. This allows you to look for correlations between seemingly unrelated matters when you attempt to analyse them. Unlike conventional methods, here you are not limited by the mental horizon of the individuals responsible for compiling the data.
- Quick response to competitor activity. By using Big Data, you can monitor in real time not only the real time standing of your company, but also the activities carried out by other companies. This is perfectly illustrated by the example of online shops – when the price of an item drops significantly in one of them, most of the other major players on the market implement a similar change within a few moments. The whole process can be repeated several times in one day, which would not be possible without constant observation of the competition and real-time analysis of their activities.
- Minimising losses in the company. Everyone makes mistakes occasionally, which can lead to financial losses, for instance. Besides, there is always the risk that an external factor will change and start acting to your disadvantage overnight. With Big Data, the response time to these situations is significantly reduced. Once specific measures have been implemented, you don’t need to wait for monthly reports to know whether the decision you have made was the right one. The analysis, which is carried out in real time, around the clock, allows to detect potential dangers or financial losses before they even become noticeable. This allows you to quickly repair a mistake or adapt to a changing situation while reducing the negative consequences.
- The need to incur investment costs. Introducing Big Data into a company involves implementing the right infrastructure to acquire data from various sources, then filtering out the redundant stuff and analysing whatever remains. This requires using very powerful computers, for example through Cloud Computing, and purchasing the appropriate software, which is also not cheap. At the same time, simply implementing Big Data does not mean that everything will simply start just happening ‘on its own’ and the company will start generating huge profits overnight.
- Storage difficulties. Big Data consists of unstructured data, so it cannot be comfortably accommodated in traditional databases. The multitude of sources, on the other hand, makes it easy to exceed the limits of analytical capacity. In other words, there is more data than you can process, which in turn requires discarding some of the collected material before it can even be processed. This problem is widespread, even Google is facing it.
- Security. The more data is collected and transferred, the greater the risk of unnoticed leakage. For this reason, it is extremely important that a company using Big Data has a thoughtful and effective cyber security policy. This involves measures aimed at protecting not only the company, but also its customers, for example through data anonymisation – that is, measures taken to ensure that no specific person can be linked to the data.
- Excessive trust. Big Data is based on advanced algorithms and artificial intelligence. It can detect correlations that are so complex that they would be very hard to observe with smaller data sets or simpler analysis tools. Still, correlation does not imply cause and effect. It is easy to perceive that two values change in a similar way over a short period of time, but this does not at all prove that one thing results from the other. It is important to bear this in mind as you analyse the results generated by Big Data machines.
Yes. Undoubtedly, modern data analytics technologies make it now possible to significantly increase a company’s productivity and profitability. That said, this involves costly investments that do not offer a 100% guarantee of maximising profits in the short term. You should bear this in mind and make the decision to invest in Big Data consciously, knowing not only the potential returns but also the risks.