Every morning, your team wakes up to over one hundred data quality alerts. I know, I recall this issue at Facebook. Some of them would be fixable issues others should have just been warnings. It’s so easy to build data pipelines and add data quality checks these days that I am sure for some people…
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When you demo a new data tool, everything works perfectly. Account executives are great at making it sound like their product is the perfect product. They make sure their data pipelines run smoothly. The demo dashboards that load in seconds. And of course, the graphs and charts they put together look pretty impressive. So, you…
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We are several years into the AI Revolution, so to speak, and with that has come an increased demand for data. The increased demand for data comes an increased demand for data infrastructure. Some companies already have reliable data stacks; others are looking to migrate to Snowflake, Databricks, or some other solution(I am sure some…
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The demand for data has grown substantially in this AI-driven world. Meaning, there are more and more data pipelines being created. The funny thing is, when I first started in the data world, no one around me used the term data pipeline. I am sure plenty of data teams used the term data pipeline. But…
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One of the questions most data engineers need to answer is whether this data pipeline should be real-time or batch. Sometimes posed as streaming vs batch. The tools you might use to do that have changed over the past few years, but that was always the question. The business, of course, would always ask for…
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Is your data team constantly feeling the pressure to deliver? Do members of your team say they feel like they’re doing work meant for two people? If the answer to either or both of these questions is a resounding yes, you may feel tempted to think, “We just need more hands on deck.” However, hiring…
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Maybe you’re luckier than me. Maybe you’ve never opened a .sql file or an Airflow DAG only to be greeted by a 5,000+ line query…a true monster of a script that leaves you wondering where to begin. I’ve seen plenty of these, and every time, I ask myself: Why in the world do these exist? And, more…
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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…
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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?…
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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.…
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