Before we begin, it’s important to set things straight: by ‘data governance’, we mean the set of policies, processes, responsibilities and technical controls that determine how an organization understands, manages and trusts its data. For a data team, you will find...
Our take: medallion architecture is a shared vocabulary, not a specification. It helps a data team, a governance team, and an executive board hold the same picture in their heads; which is genuinely valuable. But the things that decide whether an AI agent gives...
We believe AI readiness in financial services must begin with governed data. Banks and insurers may experiment with new models quickly but the data beneath them must remain accurate, traceable and understandable for years. When an AI system produces an answer about...
Our take: AI readiness for K-12 data teams needs to start with trusted data. It doesn’t start with selecting an LLM, it doesn’t start with deploying a chatbot and it certainly doesn’t start by giving an AI agent unrestricted access to every table in a student...
What we’ve observed typically goes like this: higher education data challenges are not usually caused by a lack of data. In fact, most colleges and universities have plenty of data: student records, enrollment data, financial aid information, learning management...
Enterprise data modeling is no longer just a design exercise. For years, data models helped architects define entities, relationships, keys, attributes and structures before implementation. That work still matters. Conceptual, logical and physical models remain...
When we flew northbound to attend the Data Innovation Summit, DIS 2026, in Stockholm, we expected AI to dominate the conversation. And it did. But the most intriguing conversations were not about AI in isolation. Rather, they were about what needs to sit underneath...
The WhereScape team recently attended the 2026 HEDW Conference in Austin, Texas, held April 26 - 29th, 2026. HEDW describes itself as a community focused on knowledge management in colleges and universities, including data warehouses, institutional reporting...
Let’s preface this blog with what many know deep down but not everyone has consciously accepted: a modern data environment is no longer just a place to store, transform and report on data. Instead, it is now expected to support business intelligence, real-time...