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To improve data quality for better AI stop fixing it

Unlocking enhanced AI quality requires a shift in focus. Instead of fixating on data correction, redirect efforts towards refining the processes that generate it. Embrace flaws as pathways to process improvement. Let data remain an unaltered representation of reality, nurturing a culture of evolution for better AI outcomes.

Unleashing the Power of Low-Code

Speed, agility, and scalability are paramount to meet business expectations. Low code has quickly gained popularity as a powerful tool that complements full code solutions, enabling data teams and business users. Here are the benefits of low-code in data consultancy and its impact on the development cycle.

Latest podcasts

How to unboss your data platform

Axel Goris (Founder at dataXPdesign) on: what is needed to create a healthy data platform using his self-service development framework: “unboss, enable and accelerate”. Axel explains how to shift the workload from IT to the business, using risk assessments as a tool to facilitate communication between business and IT.

Revving up your data quality

Mark de Brauw (Cofounder at Mesoica) on: how data quality is traditionally addressed as a technical issues rather than a business issue. Mark explains how more than a data governance is required in order to implement successful data quality management processes. He explains the advantage of using dedicated data quality tooling that support business users.