Is your latest Generative AI initiative not delivering the expected results? Do business reports take days of manual reconciliation? The issue probably isn’t with algorithms or people, but with the foundation: the quality of your data. We don’t build houses on cracked foundations—so why build our business on unreliable data? According to Gartner, as early […]
Back in 2023, we published a post exploring a concept that’s been gaining traction among data management professionals: the Data Product. Building on ideas from the literature (most notably Zhamak Dehghani’s seminal work on Data Mesh) we suggested a hands-on approach for positioning Data Products within modern data architectures. In today’s data landscape, we’ve moved
Understanding Data Products: benefits, evaluation frameworks, and how to monetize them Read More »
Augmented Data Quality means applying advanced functions to automate some Data Quality (DQ) processes with the help of “active metadata” and such technologies as Artificial Intelligence and Machine Learning. Today, data specialists face increasingly complex challenges: growing data volumes, increasingly heterogeneous data sources, and the need for an “AI-ready” information ecosystem. These needs have guided
What is Augmented Data Quality and how does it work? Read More »
In recent years, banks have benefited from a certain “tolerance” by regulators regarding the quality of risk data and risk reporting. But that period is over. The ECB is clear: regulations on this matter have existed for some time; now is the moment to truly apply them. Imagine a financial institution under stress: markets are
In the fascinating world of Data Management, curious stories often circulate that highlight the importance of data quality. Sometimes they even make us smile—until it happens to us or one of our clients, perhaps in the dreaded production environment! As we enjoy the summer, why not have some fun with quirky anecdotes that remind us
Augmented Data Management uses advanced technologies to optimize and improve data management processes in a company. Data Management (DM) is an essential enabling factor for analytics, Data Science, Regulatory Reporting and digital business transformation. This practice allows collecting and storing, transforming and using the data in compliance with policies and regulations. It helps to quickly
What is Augmented Data Management? Read More »
