Nuances and Considerations for Implementing Data Mesh A data mesh architecture distributes data ownership across domain teams with federated governance and decentralized data products. Data mesh contrasts with other data…

The Analytics Leadership Consortium’s (ALC) Q3 theme on Funding and Budgets focused on three aspects: establishing and justifying value, sourcing funds, and allocating budget. While many valuable points came through…

Managing data science projects — or more specifically engineering teams building data products — is in my experience an art form, and a mysterious one at that. Anyone who has…

How many analytics organizations can quickly identify the top five capabilities they are actively building to prepare for their business needs 3-5 years from now? Perhaps not many. Many leaders…

Throughout my career, I’ve seen a number of different analytics teams; as you might expect, there are a handful of similarities and a handful of differences in how each team…

You’re interviewing for a job in data science: maybe it’s your first job or maybe it’s a Chief Analytics Officer role. One struggle people have is when to talk salary…

The Inequality in the Data Science Industry Data science as a discipline has received an increasing amount of attention in the public consciousness over the past decade from many, including…

Many analytics leaders will agree that talent is the most valuable asset in their organization— and the most challenging. But how much time do analytics leaders really spend designing the…

The need to upskill the data and analytics capabilities of both your analytics community and the broader business and operational communities is widely recognized. It is also difficult to determine…