adesso Blog

In an age when efficiency and rapid adaptability are crucial, process mining offers significant added value: it enables companies to optimise their business processes in a data-driven way. In this blog post, we explain in more detail how process mining can help – in virtually every implementation, regardless of industry or process.

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.

Foundation models are revolutionising the way we perform time series analyses. They are trained on large data sets and offer flexible and scalable solutions for complex predictions and pattern recognition. In my blog post, I introduce foundation models, show advantages and technical details and compare different models with each other.

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 the ever-evolving landscape of data management and analytics, staying ahead of the curve is critical to meeting the needs of modern digital businesses. With Microsoft Fabric entering its public preview phase in mid-May of 2023, this ecosystem is experiencing significant disruption. We partnered with our client to test these waters, embarking on a Proof of Concept (PoC) project to migrate their existing on-premises data warehouse to the cloud, using Microsoft Fabric.

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.