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As humans, we are used to legitimizing our present from the past, or explicitly attributing its current structure to a history. Even and especially with regard to the specific form of current code and system architectures, such a look is able to shed light on the proverbial darkness. One fact that appears particularly interesting in this context is that of the Legacy Code. But what exactly is legacy code? And why can he be so annoying, not to say dangerous? This short blog post will therefore focus on residual issues and the appeal: “Continuous tidying up is extremely worthwhile! ”

Our author and software developer Andrés has been working on code quality and clean code for many years. To achieve high code quality, he has a seemingly simple but effective method: read books. You can find out why he recommends this and which books you should read here.

The digital economy has long since become one of the most important foundations for pretty much every business. Since crime in these areas is also increasing, measures must be taken to ensure basic security. One such method that can ensure safety is to simulate an emergency using so-called “penetration testing.” To introduce the topic, we conducted an interview with Sascha Zinke from Splone.

Numerous attacks on companies, authorities and socially relevant organizations show just how fragile IT infrastructures can actually be. EU NIS 2 promises to remedy the situation and ensure safe conditions.

All too often, when we think about cyber security, we only think of large corporations and massive databases that need to be protected. My following short story shows that it can also affect “small fish”, which addresses the dangers of extensive networking as well as offering the prospect of situational reconciliation with the associated risks.

The ubiquitous data that depicts our reality requires appropriate storage space. Proper database design is the basis for the efficient administration, processing and analysis of data in our information society and within its corresponding systems. Data is not just data! They all require treatment appropriate to their intended use. This starts with an adequate database design. But what exactly does this undertaking look like?

Can I trick ChatGPT? So get generative AI to provide me with information or give me answers that either do not comply with community guidelines or that are formulated in the way a human would deliver them: flappy, full of humor and so highly speculative in many places that it hurts?

A successful company is characterized above all by a clear structure with regard to the flow of information. Because whatever business model may be in the foreground, the flow of information and data is an important issue in any case. So-called data silos prevent needs-based processing. How can you counteract data silos? And what can be done to avoid creating such data silos in the first place?

Our world is getting smaller. At least in perception, this saying is correct. Those distances that once seemed insurmountable are now being transformed into routes that can be overcome ever faster and more comfortably. The transport sector and the logistics sector not only connect people, but goods must also be transported over ever longer distances. The question of how AI can be used in logistics is a consistent one, which is why we want to address this topic below.

The enhancements of AI have already been well received in a number of industries and corresponding departments. But even in those sectors where there is still relative peace, a lot will certainly change in the near future. One such case is the financial sector, in which AI played a major role only 8% of the time in 2022. However, forecasts show that this is about to change. Financial AI is going to change a lot...

In view of constant change, including and especially in technological terms, it is important to establish adequate procedures within changing contexts. Binding guidelines and corresponding laws are an attempt to ensure a minimum level of security, but do not fundamentally impede progress. The latest hype about AI — a veritable AI spring — is also circulating in this regard: the new EU AI Act is the right and important step...

In order to correctly understand what a company's data says, it is advisable to look at the benefits of data visualization. Business intelligence is a field that can be used precisely for this purpose: By converting dry numbers into an appealing and easy-to-understand graphical form, it is possible to understand complex relationships quickly and easily.

Few issues have had such a huge impact in the context of digitization as the introduction of cloud computing and corresponding solutions. They have gradually changed the entire distribution structure of software products and have also had an impact on the specific design of storage structures and databases. But what comes after the cloud? Or did she come to stay?

While many young start-up entrepreneurs are striving to launch as innovative a product as possible or to create a fresh, extremely contemporary public image, companies in established industries that have far less appeal know the importance of stabilizing efforts. Especially in an accelerated present, this always means taking a look at the acquired data and pursuing a correspondingly coherent data strategy.

An increasingly complex world requires ever more accurate analyses of ever larger volumes of data. Big data is here to stay! Accordingly, there is also a need for constantly updated access to the incredibly large amount of data. Data science is the melodious name of a veritable research program that has set out to introduce a certain level of security into uncertain areas.

Wherever we move, act, or simply stay, we produce data. Representing our common living environment as information that can be collected and ultimately always potentially evaluated offers the opportunity for delicate intervention. It is obvious that different enforcement methods correspond to different types of generated data. But how exactly do the different types of data differ?

The multi-purpose open source community called Hugging Face offers a number of interesting intervention options for experts and those who want to become one to approach a general idea of AI in resonance with Natural Language Processing (NLP).

Anyone who is busy programming important tools and/or applications today as part of continuing digitization will sooner or later be confronted with the question of how generative AI can help in this process. What are the options for discharge without the threat of serious errors? So how can a routine use of generative AI be established that is able to deliver added value for everyone?

Anyone who has worked in content creation over the past few months will certainly have stumbled across ChatGPT at one time or another, will be gratefully accepted the help of this tool, then viewed critically again, or even experienced it as a reason to shake their heads with resignation. Since we do not want to block ourselves from progress, the following article is intended to satisfy all those who are primarily interested in efficiency in their work.

Innovations don't happen in a vacuum. They must prove themselves in resonance with the environment in which they are embedded and require a targeted development process. Artificial intelligence (AI) is one of the recent phenomena undergoing such a process. An important indicator that should be paid much attention to is the level of AI maturity. But what is that anyway? And why is it worthwhile to keep an eye on general developments?

Process mining is an advanced technology that is becoming increasingly important in today's business world. In this article, we'll go into detail about what process mining is and how it can help companies analyze, optimize, and closely monitor their processes.

Dealing with almost overwhelmingly large amounts of data is a matter of course in almost every economic activity these days. Whether this is mandatory customer data or whether your own business model is based on the processing of other sensitive information is ultimately irrelevant: In any case, it is important to maintain a flawless handling of intangible data.

The era of artificial intelligence (AI) has long since begun and companies are faced with the exciting task of integrating this innovative technology into their business processes. In this article, we will try to show how companies can use AI for their processes, the benefits of such integration, and how such an undertaking can lead to sustainable success.

The world of artificial intelligence (AI) is constantly evolving and offers numerous new opportunities and potential. One of these exciting developments is generative AI. It enables companies to exploit the full potential of their employees and the process routines established as it were.

A breath of fresh air is blowing through the current economic world. “Artificial intelligence” (AI) is shaking up many traditional securities and is already beginning to promise changes today, which will result in massive reinterpretations of both cherished and annoying routines.

We also address issues of technological change beyond our core business. Competence doesn't just mean action, but also and especially getting detailed information. In this sense, it's worth taking a curious look outside the box.