Seattle Data Guy

Let me start out by saying that not every data warehouse uses a columnar storage format.

Not every data pipeline or process needs to be real-time.

There are certain problems that seem to never really go away if you’re leading a data team.

I’ve been working in the data world for over a decade and consulting for nearly as long, and some things just don’t change.

Here is something that remains true in the era of AI.

Every morning, your team wakes up to over one hundred data quality alerts.

When you demo a new data tool, everything works perfectly.

Data teams continue to debate which is better: ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform).

We are several years into the AI Revolution, so to speak, and with that has come an increased demand for data.

The demand for data has grown substantially in this AI-driven world.

Whether you’re working at a large enterprise or a small business, there’s almost always a need to extract data from source systems, process it, and use it for operational or analytical purposes.