As organizations increasingly rely on data to drive business decisions, the field of data engineering is rapidly evolving. In 2024, several key trends are expected to shape the future... Read more »
Data quality monitoring. Data testing. Data observability. Say that five times fast. Are they different words for the same thing? Unique approaches to the same problem? Something else entirely?... Read more »
Data observability has been one of the hottest emerging data engineering technologies the last several years. This momentum shows no signs of stopping with data quality and reliability becoming... Read more »
When it comes to the technology race, moving quickly has always been the hallmark of future success. Unfortunately, moving too quickly also means we can risk overlooking the hazards... Read more »
These days, keeping up with the latest advancements in GenAI is harder than saying “multimodal model.” It seems like every week some shiny new solution launches with the lofty... Read more »
As recently as a year ago, about half of the data leaders we spoke with felt the business value of their team sold itself. Today, maximizing and measuring data... Read more »
Imagine you’ve been building houses with a hammer and nails for most of your career, and I gave you a nail gun. But instead of pressing it to the... Read more »
Like bean dip and ogres, layers are the building blocks of the modern data stack. Its powerful selection of tooling components combine to create a single synchronized and extensible... Read more »
I link to Benn Stancil in my posts more than any other data thought leader. I might not always agree with his answers, but I almost always agree with... Read more »
What is data freshness and why is it important? Data freshness, sometimes referred to as data timeliness, is the frequency in which data is updated for consumption. It is... Read more »
