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adesso BLOG

10

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  • Data

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Methodology

Metadata-driven data pipelines are a game changer for data processing in companies. These pipelines use metadata to dynamically update processes instead of manually revising each step every time a data source changes. As with data pipelines, metadata maintenance can be a bottleneck in the maintenance and further development of a pipeline framework. In this blog post, I use practical examples to show how the Jsonnet template language makes it easier to maintain metadata.

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Methodology

14.02.2024 By Mohammad Qasem

An introduction to the EU Data Act

Picture Mohammad Qasem

European legislators have imposed strict regulation on the digital space in recent years. In addition to the much-discussed EU IoT Act, other important regulations such as the Data Governance Act and the Data Act have come into force. The Data Act in particular has attracted special attention due to its impact on IoT device manufacturers, service providers and start-ups. The Data Act, which entered into force on 11 January 2024, will apply from September 2025. In my blog post, I discuss its objectives, effects and requirements for all stakeholders.

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Methodology

In an increasingly digitalised world, the systematic collection, interpretation and use of data is becoming a factor in success. If a company fails to do this, it will lose a key tool needed to stay competitive and innovate in the age of digitalisation. In my blog post, I explain why data governance is important for companies and how adesso can support them in this area.

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Digital Experience

A look at the past 125 years shows that there are plenty of exciting sales models that help every organisation to better understand the current sales and decision-making behaviour of modern customers and to align their marketing measures accordingly. Each of these models presents interesting ideas and approaches to the world of data-driven marketing that can help companies refine their understanding of end customers and understand them better. I will show you which models in my blog post.

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Industries

03.02.2023 By Stephen Lorenzen, Maximilian Hammes and Jonas Schnorrenberg

Are business intelligence maturity models relevant for the energy sector?

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Business intelligence (BI) maturity models are used to find out how far along a company is in terms of digitalisation and data use. In our blog post, we will explain how maturity models help with classification, whether the Interaction Room is an alternative way to apply them and, if it is, whether it can be used as a basis to successfully improve BI in the holistic consultancy process.

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AI

12.12.2022 By Tim Strohschneider

Artificial intelligence continues to gain ground

Picture Tim Strohschneider

The demand for innovative AI-based transformer models is hard to ignore. Great advancements in development have been made in recent years, especially in areas such as machine translation and speech and text recognition. This blog post will describe how transformer technologies are used in language models.

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Industries

10.10.2022 By Uwe Pohlmann and Fernando Arévalo

A Preamble for Machine Data Collection on the Shop Floor

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Finding patterns in data is a task that keeps data scientists as well as domain experts busy. For companies, data is a critical business asset that adds value. To this end, store floor connectivity plays an essential role. I explain what this is all about in my blog post using a (fictional) example.

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Industries

29.08.2022 By Roland Scheuch

The Health Data Use Act

Picture Roland Scheuch

This blog post explains why the use of data in the health sector makes sense and which concepts and framework conditions need to be created for this.

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Industries

17.05.2022 By Vanessa Stahl and Juan Carlos Peñafiel Suárez

Why validating computer systems is important and the advantages that come along with it

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The path to successful digitalisation in the laboratory requires the use of IT systems. While a large part of the documentation and data volume for manual process steps is kept on paper, an increased level of digitalisation also entails an increased volume of data. This makes it all the more important to ensure that the IT systems that are used are validated so that the data that’s generated and processed is subject to the required quality criteria.

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