Is Palantir onto something, or are they just blowing hot air? You may have heard the term Ontology, and why leading businesses rely on them to build trustworthy data models. Recent advances in LLMs have made it possible for startups and enterprises alike to build flexible, reliable semantic layers faster

In the fast-paced world of modern organizations, data is both a goldmine and a puzzle. Every team wants answers, and they want them yesterday. Yet as demands for analytics grow, so does the complexity of managing data. Systems fragment, definitions diverge, and chaos ensues, we’ll call that entropy in

The term “Business Intelligence” was first used in 1865 by a writer named Richard Millar Devens to describe how a 19th‑century banker used data to gain a competitive advantage. Etymology is funny. When someone asks us if AstroBee is a BI tool, I think Richard Millar Devens would say

It always starts the same way. A dashboard looks off. Maybe the churn rate spiked unexpectedly. Or the LTV curve flattened when it shouldn’t have. An analyst is tasked with figuring out what happened. They retrace the query. They check the join. They pull the raw tables. Nothing is

When people talk about applying LLMs to the modern data stack, they usually focus on the analytics layer. That makes sense. The analytics layer is the part most people are familiar with, where tools like Power BI, Tableau, and Looker live. These tools sit on top of data that’s

Here’s a joke I thought of: Q: What does the father of data warehousing have in common with a $300B analytics powerhouse named after a Lord of the Rings spying device? A: Both of them defy the star schema paradigm and encourage you to model your data top-down, in

Most data teams need to balance two opposing priorities in the tools they provide business stakeholders: accuracy of insights and breadth of data availability. Typically, you can not maximize one without sacrificing the other. The holy grail of the “text2sql” and “chat with your data” space is to break the

Connecting to disparate source systems is a solved problem. Tools like FiveTran, AirByte, and merge.dev sink thousands of hours of engineering work into supporting connectors to every software system on the planet, and most teams who supporting 1,000s of connectors can use one of these tools under the

Everyone and their grandmother nowadays knows about ETL (extract-transform-load). Whoever ran that category creation push did a great job, because it’s become the household name for “any process that puts data into the data warehouse”. There’s even a concept of Reverse ETL, which has nothing to do with

The idea of “democratizing data” in enterprise settings has existed for a while. It’s taken different forms over the years such as self-service BI tools, better access to data teams, and more recently, text-to-SQL AI assistants. Still, the core concept has remained consistent: “Your business needs data to operate,