How not to fail your AI projects
Amid the success stories, numerous companies find themselves trapped in nightmarish situations, struggling to make AI work for them. What separates the winners from the losers?
The European AI act: a critical review of what you’ve heard in the news
In this blogpost we will describe some of the general implications for business and give some much-needed nuances to the messages that have been circulating in the media.
Building an Ethical Framework for Generative AI
In this blog, we explore the guidelines set by KU Leuven, shedding light on how to navigate the intricate landscape of generative AI responsibly.
Power BI & Collibra: A match made in heaven?
If you’re using Collibra and Power BI without a connection, then this ‘how to’ guide is a must-read! We’ll share some of the synergies between the two platforms and walk you through the integration process step by step.
Data Platform Next Step: Insights from a Microsoft Conference in Denmark
Discover the latest updates on Microsoft Fabric in data activation, the significance of delta tables, and the potential of integrating Fabric and dbt.
Three out of four Flemish companies still make no use of AI
Discover the challenges faced by Flemish organizations in adopting AI, from the knowledge gap to legal and ethical concerns.
Do You Speak Data🤔? A Case for Data Literacy
With data becoming an invaluable asset, the ability to understand, analyse, and utilize it is more critical than ever. We provide an insightful exploration of data literacy, shedding light on the roles of data consumers and data producers. Discover how data fluent cultures and robust data product ecosystems can transform your organization into a data literate powerhouse.
Microsoft Fabric: The Game-Changer in Data Analytics?
Microsoft introduced Fabric this week. Possibly and probably the game-changing solution that can transform data analytics and integration. We dived into what Microsoft has unveiled with Microsoft Fabric and how this can impact Data Engineers, Analysts and Scientists. But we also have some open questions that we will answer once we are finished testing this exciting technology.
A Culture of Support: How Datashift Helped Me Grow as a Data Engineer
When Pieter joined Datashift as a data engineer, he was initially taken aback by the new challenges ahead of him. Despite having prior experience as a data analyst, he knew that data engineering would require him to learn a whole new set of tools and technologies. However, Pieter quickly found that he could rely on his colleagues at Datashift for support and guidance. Read his complete story here.