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 »
Over the past decade, data teams have been simultaneously underwater and riding a wave. We’ve been building modern data stacks, migrating to Snowflake like our lives depended on it,... Read more »
If you don’t like change, data engineering is not for you. Little in this space has escaped reinvention. The most prominent, recent examples are Snowflake and Databricks disrupting the... Read more »
Why do data quality metrics matter? If you’re in data, you’re either currently working on a data quality project or you just wrapped one up. It’s the law of... Read more »
Data engineering is the leading branch of big data. If you want to pursue a data engineering career and wish to present your skills, then you are on the... Read more »
As part of my job, I’m fortunate enough to speak with data leaders far and wide about how they are tackling some of our industry’s biggest challenges, from implementing... Read more »
What exactly is data engineering? The process of planning and constructing infrastructures for the gathering, storage, and analysis of data is referred to as “data engineering.” This is a... Read more »
Across both public and private sectors, more organizations are adopting a “data-driven” mindset-or, at least, data-driven messaging. But in reality, most aren’t prepared for the reality of what it... Read more »
