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.
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.
Are you also struggling getting a grip on the amount of data in your organisation? Is your data properly catalogued, making it easy to find the right data through the massive amount of metadata?
Organise your data into datasets to make data governance practical.
Central for de-central data teams: start acting as a (temporary)…
Comparing data mesh vs traditional data management shows that one is not necessarilly beneficial above the other
Have you thought of how design can make or break the value you get from your data
Your web3 data value: successful and reliable. Data sharing is enabled by the decentralized web3, creating new ways to identify the value of data.
Utilizing data as the new oil requires a standard model to become successful. Don’t fall into pitfalls such as too large focus on data science or data platform tooling. Go from prototype to full data monetization.
With the rise of Artificial Intelligence (AI) and Machine Learning, the need for large and rich (test) data sets is even more rising. These data sets will improve performance and results of machine learning models. This blog contains quality assurance for synthetic data
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.
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.
Ori Yudilevich (Chief Technology Officer at Materials Zone) on: the…
Ryan Price (Executive Data & Artificial Intelligence at Avanade) on:…
Caroline Fluit (Global VP Digital Product Engineering at IKEA) on:…
Sander Kerstens (Director Data Analytics at Vanderlande) on: data mesh,…
Jan Leenaars(Product Owner at Rijkswaterstaat) on: data-driven asset management, how…
Remi Verhoeven (Senior Manager at KPMG) on: the character traits, technical skills and soft skills required in order to become a successful data profession. Listen to hear about the ways data professionals can improve their skills to increase their chances in the recruitment process.
Dennis Groot on: data autonomy, what it is, why it matters and why it is important now. Dennis talks about how to implement data autonomy in complex architectures and how it relates to current trends like self-sovereign identity and the metaverse.