Ask the Experts: The Rise of DBT

Ask the Experts: The Rise of DBT

When it comes to next-generation data processing architectures, there’s still a lot of innovation going on. It’s great to see the advancements being made to enhance, simplify and democratise the use of data. One technology we’ve seen gaining great traction over...
Tooling up with a Feature Store

Tooling up with a Feature Store

A Feature Store is useful tool to help manage Features used by Machine Learning models. I discussed in my previous blog the challenges related to Feature management, how to curate them and the desirable capabilities of a Feature Store. In this blog I will build upon...
Sharing Features in Scaled AI

Sharing Features in Scaled AI

Let me tell you a secret – the art of machine learning is not about data (although lots of people say that it is). Data itself is the raw material input for machine learning, especially for supervised learning or deep learning. The secret of machine learning is...
Redshift Serverless: First Impressions

Redshift Serverless: First Impressions

There were a LOT of announcements at re:invent 2021 – nothing new in that. Standard practice in the New Year at Inawisdom is to go through a process of digesting them in a bit more depth than is possible during the hubbub of the event. As part of this I had a quick...
Reflections on MLOps

Reflections on MLOps

A rare event! Last night, I attended the London MLOps meetup in person, something that has not been possible for getting on for two years. Despite a massive run from IT folk on a limited supply of pizza (clearly making up for lost time!), it was great to get...
5 Common Myths About AI Adoption

5 Common Myths About AI Adoption

When AI first came on the scene, only those businesses with cutting-edge tech agendas and well-resourced global enterprises had the budgets, skillsets and breadth of data needed to truly take advantage of it. Fortunately, as technology and best practice has developed,...