There’s a moment in every data engineer’s journey when the excitement of building pipelines meets a difficult, quiet question: Should this run in batch, or should it be real-time? It sounds technical — but it’s actually philosophical. Behind it lies a deeper question:What are we really optimizing for — freshness, simplicity, or reliability? Because you…
Welcome back to our deep dive into Elasticsearch! So far, we’ve mastered the art of finding the right documents. We’ve become experts in queries, filters, and the mighty bool query. But what happens after you’ve retrieved your results? How do you make sense of the bigger picture? This is where the true analytical power of Elasticsearch shines: Aggregations. If queries…
Introduction If you’ve been following this series, you already know: Now it’s time for the real workhorse: the bool query.Why? Because no real-world search problem is solved by just one condition. Users expect relevance and restrictions: The bool query is how you glue all of these conditions together. By the way, I should also mention…
In Part 1 of this series I walked through the foundations of Elasticsearch queries: the mental model, why mapping is your best friend, and how to choose between filters and matches. Now it’s time to roll up our sleeves and look at some of the practical query types that you’ll actually use when building real-world…
When I first got to know Elasticsearch, I told myself: “Well, this is just another database… right?”But I was wrong. Elasticsearch is actually different. It kind of feels like a mix between a search engine and a database.To be honest, I’m still not very comfortable with it myself 🙂But in this post—which is the first…
Let me be honest: when I sit down with a fresh dataset, I’m not looking for ceremony. I’m looking for clarity. That first hour matters more than most people admit. I want to get a feel for the terrain—what’s messy, what’s surprising, what’s worth digging into. If I can’t answer “what’s going on here?” in…
You’ve probably heard the term batch processing before.In this post, we’ll talk about what it means and how to use it in Apache Airflow. These days, with the mind-boggling amount of data growing by the second, one of the most important skills you can have is knowing how to process massive datasets efficiently. Tools like…
When you’re working with the vast world of machine learning models, especially large language models (LLMs) like LLaMA, a fundamental question always arises: How much Graphics Memory (VRAM) do I need for my work? Accurately understanding this requirement not only helps you choose the right hardware but also plays a crucial role in optimizing your…
One of the most common issues in many organizations and data teams is a messy and disorganized Data Warehouse. This problem usually develops over time due to rapid team growth, evolving analytics needs, onboarding new members without proper documentation, and an increase in temporary projects. The result? A chaotic data warehouse with inconsistent structures, duplicate…
A few weeks ago, in the chaos of war and crisis, I talked to you about the importance of backups. From pg_dump and mysqldump to mongoexport and rsync; about how we can prevent data loss during critical situations. Now that things have calmed down a bit, it’s time to revisit the topic. In the previous…
