adesso Blog

Energy suppliers are faced with the challenge of managing complex supply chains and optimising costs. With intelligent cloud data platforms, AI-supported analyses and automated purchasing processes, they can secure decisive competitive advantages. Find out how this works in practice and what success stories are available in our latest blog post – to coincide with our appearance at the EUROPEAN ENERGY Supply Chain Summit 2025 in Berlin.

Data is the basis for informed decisions. In the past, decisions were often made based on gut feeling. Today, data-driven approaches enable informed bottom-up decisions. However, it is only with well-thought-out visualisation that this data can reach its full potential. This blog post explains why dashboards play a crucial role in this context.

It goes without saying for every driver that if a strange noise occurs, the reason must be identified. The standard procedure is to go to the garage to identify the cause of the fault. Although this costs a certain fee, the damage to be expected without an inspection may far exceed such a financial outlay. This is a typical instance of predictive maintenance, a sub-area of predictive analytics: preventing damage before it has a full impact. In industry, the principle is the same, only on a larger scale where thousands - if not millions - of devices produce immense amounts of data.

Microsoft Fabric has the potential to revolutionize the way you build, extend, and maintain enterprise data architectures. Years ago, the concept of "Platform as a Service” (PaaS) rather than "Infrastructure as a Service” (IaaS), brought a simplification to building architectures. With Fabric, Microsoft now offers the next, logical step: Turnkey "Software as a Service” (SaaS) modules can be assembled with a few clicks into a powerful, easily extensible, and scalable enterprise data architecture. Find out more in my blog post

In this blog post, we will explore the requirements specific to data science projects, explain how to choose the right agile approach and take a closer look at the current state of research.

Agility and data science have both taken on a larger role in recent years. The use of agile methods and frameworks can be a key factor in the success of a company. In this and future blog posts, I will be focusing primarily on the question of whether and how agile approaches can be integrated into the field of data science. We will begin by taking a look at basic things you need to know about data science and agility.

In this blog post, we would like to present the Visual Studio Code extensions that are indispensable in our day-to-day work as experts in the fields of machine learning, data engineering and AI. If you do not have the appropriate extensions, Visual Studio Code would not be a full-fledged integrated development environment (IDE). But with the right ones, you can save yourself a lot of work and become more productive as a developer.

Reports and key performance indicators (KPIs) create transparency that is of great use for many departments at a company. Using dashboards is recommended since they are a cost-effective tool for grid operators in view of the limited budgets available to them. In our blog post, we will be focusing on dashboards that provide grid operators with business and financial KPIs.

Data innovations and data analytics use cases are an issue in the energy industry. Grid operators are sitting on mountains of unused data, meaning they are unable to properly exploit synergy effects and efficiency potentials. This blog post will explain how fully integrated processes, systems and data can help speed up the energy transition.