Business Intelligence and Big Data

The more the digital transformation progresses, the more important the topic of big data becomes. Already today, the amount of data that accumulates in social networks, for example, is unimaginably large. According to statista.com, approximately 815 million users used the platforms in 2019. According to projections, this figure could rise to 1.2 billion by 2023. The amount of information that accumulates per second with such user numbers cannot be handled with conventional IT processing methods. Big Data is therefore concerned with new processes that can cope with the demands of such systems.

With Big Data, the more complex the data sets are, the greater the potential information gain. If logistics companies equip their trucks with sensors, for example, these constantly provide information on location, consumption, etc., which can then be used to calculate efficient routes. Thanks to machine learning, efficient routes could be calculated, for example. The routes can be optimised for the lowest consumption, shortest downtimes or parts wear. However, a company also pays a price for the higher complexity of the data volumes. The IT systems must be designed for the corresponding data volumes. It must therefore be weighed up in which framework Big Data makes sense.