By: Bartłomiej Michalski, Big Data Architect at Future Processing

Finding ways to outperform the competition is key to business success. That’s why innovation and creative strategies are always at the forefront for most organisations. However, finding ways to constantly remain competitive isn’t easy, which is why more companies are turning to Big Data for the answers. 

Data is the new currency, as processing and drawing non-obvious conclusions can help inform organisations on key decisions on which business development is made, allowing them to generate a competitive edge. Almost every company, public administration unit or individual, generates data that can be analysed and the amount and type of data that is being generated is vast and fast. This can also be known as Big Data and can include anything from consumer behaviour to industry trends. In fact, over 90% of the world’s data has been created in the last two years alone. 

However, it is no longer about who has access to the most data, as this can even hinder a business and they could get overwhelmed. Nowadays for a business to truly gain an edge, they need to know how to extract the maximum amount of information from the data that will best inform business decisions. And here’s the tricky part. To maximize the benefits of data, it is not enough to collect large volumes of data. The quantity does not directly translate into the usefulness of this data. Care should be taken to collect appropriate and reliable data. The data set may turn out to be useless in terms of obtaining an answer to our problem.

This is what Data Solutions deals with – a dynamically developing field applicable in economy, public and social spheres, where we can not only help build a ready-made solution, but also advise whether it is feasible and how much it will cost to create this solution and its subsequent maintenance.

Role of data in business development

Data is at the centre of nearly every business decision made. Every company function relies on detailed data analysis to provide accurate intelligence, enabling management to develop a more outlined, proactive approach. This could be the HR department analysing data to generate the best recruits for the business, to executives analysing market trends to help evaluate the direction of the organisation.

Making decisions not based on data is relying only on luck and ignoring the enormous potential that is practically at your fingertips. As we well know, everyone’s luck runs out sooner or later, so why take the risk? What is the cost of making the wrong decision in your company?

What is important, is we do not have to acquire all this data because it is simply around us. This is where data science comes in, as it is used to translate this data into usable useful knowledge using different algorithms. An example is data processing from electric meters. We use different electrical devices every day, at different times of the day, in different ways. This data can be used to better adjust the tariff to the consumer’s needs. Predict when a consumer is going on vacation, when he uses much more electricity. This data can also be used to predict potential problems with the electrical infrastructure. Thanks to this, we can avoid costly interruptions in the supply of electricity and unforeseen repairs. We can start thinking in different categories: anticipating problems, avoiding costs, and saving.

Additionally, one of the effects of the pandemic is the significant growth of the entire online shopping sector. In this case, the prediction of events based on the analysis of Big Data, allows companies to gain a real advantage over the competition in the form of developing personalised recommendations by algorithms, contributing to the growth of online sales. The world’s largest companies have built and continue to build their position thanks to the data they collect and continue to collect. They know how to use the hidden potential in a useful way. For example, Amazon develops algorithms and methods to predict product suggestions (recommendations) and product demand (forecasts). Big Data processing also leads to the automatic extraction of customer behaviour patterns, which, for example, in the case of companies providing transport services (such as Uber), is the basis for calculating rates for rides.  

Big Data processing also leads to the automatic extraction of customer behaviour patterns. Sometimes it’s not easy to understand how the client thinks. Finding non-obvious patterns of his behaviour is critical in order to be able to communicate with him more effectively. Here, machine learning algorithms can help us a lot, as they can help us find these non-obvious patterns of behaviour.

Big Data allows organisations to better understand their customers’ wants and needs, which in turn helps them make their products more popular and even their brand awareness, leading to increased sales and higher ROI rates. Through the use of knowledge gained from this data, they can cater to the shopper’s needs and be ahead of their competition.

Facilitating decision-making in a situation where such a decision must be made quickly, because the competition has adapted to the changing needs of the market, may be something that may affect our being or not.

Effective collection and analysis of data 

While those who adopt Big Data initiatives might have an initial advantage over companies that are slower to adapt, that’ll change as more organisations catch on. Businesses need to make sure they not only have this data, but that they have the tools and capacity to truly understand its worth. I would even say: Businesses do not want to collect data, but to make good decisions based on information from these data sets.

Companies capture Big Data in a variety of ways from multiple sources. Some collection methods are highly technical in nature, while others are more deductive using sophisticated software in the process. 

Solutions related to data processing, for example, from the Big Data family or machine learning algorithms, enables the collection and analysis of data at the level of advanced analytics. What is very important, the cost of creating such a solution, e.g. based on the cloud, and then using it, can be adapted to the needs and capabilities of the company. Maintaining such a solution is no longer associated with the need to maintain the entire, expensive infrastructure in the company, while it is only used for a while. The tools are much more effective and useful than a few years ago.

In the end, the key is not how much data we have, but whether we can extract the maximum amount of information from it and gain a competitive edge. I have no doubt that without the help of technology gaining access to the knowledge hidden in the data would take much longer, if possible. Thinking back to 2020, technology has played an important role in the rapid production of the COVID-19 vaccine. Data processing technology is and will be very helpful in different areas and will be crucial as the world continues to move forward to create a competitive edge as higher levels of competition across many industries increase.