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| from Sabrina Schuck

Reporting for Everyone – Making Accessibility a Success

From 2025 onwards, accessibility in reporting will increasingly become a legal requirement – especially for public reports. In this article, Sabrina explains which tools can support you and how to design reports that are accessible to everyone.

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| from Patrick Lanzinger

Kafka vs. Kinesis: Which Solution is Right for Me? A Comparison Using Sensor Data.

Data in motion, but which system is the right fit? Apache Kafka and AWS Kinesis are among the leading technologies for processing large data streams. Whether it's sensor data, log analysis, or real-time dashboards – find out which tool is the best choice for your project.

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| from David-Sebastian Kalb

AI in Platform Solutions – Already a Real Asset Today

Platform solutions form the foundation of modern IT landscapes – but it is only through the targeted use of artificial intelligence, particularly generative AI, that they realise their full potential. This article offers a practical perspective on how AI supports the entire lifecycle of platforms – from initial concept and development through to day-to-day operations.

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| from Youssouf Nabé

AWS Cloud Services in Professional Sport: Data Analytics, Streaming and More

Discover how modern sports organisations use AWS Cloud Services to analyse real-time data streams, optimise game strategies, and reimagine the fan experience. From Bundesliga stadiums to scouting the next big talent – this is how the cloud is transforming professional sport.

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| from Kristina Bogner

BI Battle: Tableau vs. QuickSight

Tableau or QuickSight – which BI tool comes out on top? Discover how the two platforms perform across seven disciplines and find out which one best meets your requirements!

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| from Philon Fuchs

2025 Amazon QuickSight: The Future-Oriented Business Intelligence Solution?

Discover everything you need to know about Amazon QuickSight in this blog post. We highlight its advantages and disadvantages, explore who can benefit from this AWS solution, and provide practical tips for implementation to help you maximize the value of your data.

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| from Sakar Gurubacharya

From API to S3 Data Lake: ETL Solutions in AWS

Learn how to build a scalable ETL pipeline using AWS to seamlessly extract, transform, and load data from external APIs into an S3 data lake for advanced analytics. Discover key tools like Boto3, Glue, and Athena.

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| from Alexandra Terwey

Relevance of Historised and Scalable Data Architectures for ML and AI

Learn how scalable and historised data architectures like Data Vault form the foundation for efficient data processing and future-proof applications in Machine Learning and AI.

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| from Almuth Hattwich

Is dbt the right ELT tool for you? 10 important considerations at a glance

This article will guide you through 10 important aspects to consider when evaluating whether dbt aligns with your needs and infrastructure.

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| from Rico Erhard

Event-Driven Architecture: Basics, advantages, and challenges

Discover in Rico's article the fundamental characteristics of event-driven architectures and how they enable powerful, resilient data-driven applications.

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| from Tobias & Julius

Managed GenAI in the Cloud: AWS Bedrock vs. Azure AI Studio

In this article, we present and compare two managed GenAI platforms: AWS Bedrock & Azure AI. Tobias and Julius explain what's new at the interface between artificial intelligence and the cloud.

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| from Valentin Dachtler

Reduce, reuse, recycle – Principles for Data Governance and Data Cataloguing in the age of Data Mesh and AI

These principles are crucial for data management and cataloguing in a data mesh architecture and the use of AI. Solid data management is essential in order to create a clear and standardised database. A robust data governance framework prevents the creation of data silos and optimises the benefits and cost efficiency of data.

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