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Challenges in Building and Maintaining Data Products for AI and ML (Part 2)

Building and maintaining data products for AI and ML is not just about collecting data—it is about ensuring data quality, scalability, and accessibility. Without addressing these challenges, AI models will produce unreliable results, and organizations will struggle to use data effectively. Two of the biggest challenges in this area are data quality and scalability. Ensuring […]

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What Are Data Products and Why Do They Matter for AI and ML? (Part 1)

Architecture / Dominique Ronde

I still remember the days in the early 2010s, when the term „big data“ was widely discussed in the tech industry. Companies were encouraged to collect as much data as possible, seeing it as a key resource (or the new oil as we called it those days) for the digital economy. However, focusing only on

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GDPR Compliance with Apache Kafka: Handling Data Deletion Requests Effectively

Stream Pipelines / Dominique Ronde

Introduction The General Data Protection Regulation (GDPR), or Datenschutz-Grundverordnung (DSGVO) in German, mandates that organizations must be able to delete a user’s personal data upon request. Failure to comply with this requirement can result in severe fines, reaching up to 4% of a company’s global revenue or €20 million, whichever is higher. For companies using

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