Data analysis and insight

Access to vast amounts of data – both the data you have yourself, but also data that is made available by others, but little use of these for decision support – and even less for automation of decisions and processes. This is the reality for many businesses in both the public and private sectors. The data is stored in different systems and formats, and is therefore inaccessible across these silos. Traditional data warehouses are also not designed to handle today’s explosive data growth, run advanced analysis or scale quickly and cost-effectively. But the road to a more computer-driven business does not have to involve huge IT projects, be very long or expensive.

Data warehouse in the cloud – the road is not long

Most businesses have the capacity to store large amounts of data on different platforms, but the real challenge remains: How to extract relevant information from all the data to contribute to insight and decision support? Can the data contribute to the automation of decisions and processes? This is rarely possible without resorting to predictive analytics. Predictive analysis provides companies with powerful analysis tools as a basis for decisions and process improvements, most often through the use of machine learning (ML). The ultimate goal is to develop analyzes that combine lessons from the past with predictions about the future, to predict actions in real time.

Predictive analysis – can the future be predicted?

Even companies with traditional IT architecture / infrastructure can get started with data analysis quickly. By using modern data warehouse solutions in the cloud, you solve many challenges, and can adapt the solutions completely to the business’ needs. From here, the road is short to better insight and decision support – and to the use of machine learning to optimize the business.

Microsoft and Google offer serverless data warehouse solutions that allow you to connect existing professional systems to take advantage of data analytics capabilities. The time from data to value is drastically reduced and you can easily scale up if needed. By using serverless data warehouse, you can focus on the analysis and spend less time managing the infrastructure. Read how the public transport company in Rogaland, a county in Western Norway, Kolumbus, did this.

Computas’ experience

Through the use of artificial intelligence and expert systems, Computas has over 30 years of experience in making businesses in both the public and private sectors more data-driven. In recent years, cloud technologies such as Microsoft Azure and Google Cloud have been an accelerator in this area, and we have built up expertise and experience on these platforms.

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