After working in data for over a decade, one thing that remains the same is the need to create data pipelines. Whether you call them ETLs/ELTs or something else, companies need to move and process data for analytics. The question becomes how companies are actually building their data pipelines. What ETL tools are they actually… Read more| Seattle Data Guy
Over the past three years our teams have noticed a pattern. Many companies looking to migrate to the cloud go from SQL Server to Snowflake. There are many reasons this makes sense. One of the reasons and common benefits was that teams found it far easier to manage that SQL Server and in almost every… Read more| Seattle Data Guy
If you work in data, then you’ve likely used BigQuery and you’ve likely used it without really thinking about how it operates under the hood. On the surface BigQuery is Google Cloud’s fully-managed, serverless data warehouse. It’s the Redshift of GCP except we like it a little more. The question becomes, how does it work?… Read more| Seattle Data Guy
Planning out your data infrastructure in 2025 can feel wildly different than it did even five years ago. The ecosystem is louder, flashier, and more fragmented. Everyone is talking about AI, chatbots, LLMs, vector databases, and whether your data stack is “AI-ready.” Vendors promise magic, just plug in their tool and watch your insights appear.… Read more| Seattle Data Guy
Since I started working in tech, one goal that kept coming up was workflow automation. Whether automating a report or setting up retraining pipelines for machine learning models, the idea was always the same: do less manual work and get more consistent results. But automation isn’t just for analytics. RevOps teams want to streamline processes… Read more| Seattle Data Guy