There are certain problems that seem to never really go away if you’re leading a data team. Don’t get me wrong. The tech world is currently saturated by AI hype. Not only because every tool you look at now just feels like a thin layer of ChatGPT, but every conversation you have with the business…
Read more
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…
Read more
Data teams continue to debate which is better: ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform). Meanwhile, they are overspending, pipelines are breaking, or no one is utilizing the data. So, does this debate even matter anymore? Ok perhaps that’s harsh but I do always find it a little funny when people still talk…
Read more
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…
Read more
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…
Read more
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. That process, moving data from point A to point B, transforming it along the way, and making it usable, is what we typically…
Read more
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…
Read more
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…
Read more
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…
Read more
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