WhereScape is thrilled to have won the Excellence in International Trade award at the Westpac Business Excellence Awards.
The BEAs celebrate innovation and business excellence all around New Zealand. This year the competition was stiff, with finalists from a variety of business sectors including pharmaceuticals and video production.
We are honoured to have been recognised for our international efforts and hoping to continue to strive for excellence in everything we do.
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...
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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...
Data modeling workflows need to be predictable. Whether teams are importing models through the command line, running workflow scripts, applying Model Conversion Rules or editing multiple entity columns at once, they need confidence that every step can be monitored,...
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...
For many enterprise data teams, SAP PowerDesigner has been part of the data architecture toolkit for years. It has supported conceptual data models, logical data models, physical data models, warehouse modeling, reverse engineering, impact analysis and database design...
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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...