Data mesh is one of the newer ideas in the data world. And it’s generated a lot of confusion. Unlike data lakes or data warehouses, it’s not a technology you buy or install. Rather, it’s a way of organizing how your company thinks about and manages data.
Database Concepts
What Is an Edge Database?
If you’ve been hearing “edge database” thrown around and aren’t totally sure what it means, you’re not alone. The term often gets used loosely, so let’s break it down clearly.
Data Governance Explained
Data governance isn’t the most exciting term in the data world, but it might be one of the most important. Companies that ignore it tend to find out why it matters the hard way. Often this is through a compliance failure, a data breach, or a boardroom argument about whose numbers are right.
What is a Data Mart?
You might have heard “data mart” come up in conversations about analytics or business intelligence and wondered how it’s different from a database or a data warehouse. It’s a fair question, because the terms get muddled a lot. Here’s a clear breakdown.
Column-Level Security Explained
You may be aware of a concept called row-level security, which controls which rows a user can see in a table. Column-level security is a similar concept, controls which columns are visible. It solves a different problem. Same table, same rows, but some fields in those rows shouldn’t be visible to everyone.
Think about an employees table. A manager might reasonably see a list of all staff and their departments. But salary? National ID numbers? Personal contact details? These should be visible to the manager, but they probably shouldn’t be visible to most other employees, even if they’re querying the same table.
Understanding Row-Level Security (RLS)
Most developers learn about database permissions in broad strokes. You grant a user access to a table, and they can read it. Simple. But what happens when different users should only see some of the rows in that table? That’s where row-level security comes in.
Data Lineage Explained
Data lineage is one of those concepts that sounds more complicated than it is. Once you understand the basic idea, it’s actually pretty intuitive. And it solves a problem that anyone who works with data has run into.
What is a Data Lake?
Data lake is one of those terms that gets thrown around a lot in conversations about data strategy, often alongside data warehouses and data marts. But what actually is a data lake, and how does it fit into the picture? Let’s find out.
What Is ELT?
Data doesn’t always arrive clean, structured, or ready to use. And anyone who’s worked with data knows that gap between raw information and actionable insight is where a lot of the real work happens. ELT is a modern approach to bridging that gap.
Unlike its older cousin ETL, ELT flips the script by loading data into its destination first and transforming it there, taking advantage of the processing power that today’s cloud data warehouses have in abundance. The result is a faster, more flexible pipeline that’s become something of a default choice for many data teams building on platforms like Snowflake, BigQuery, or Redshift.
What is ETL?
If you’ve spent any time around data teams or analytics tools, you’ve probably heard the term ETL thrown around. It sounds technical, but the concept is actually pretty straightforward. This article looks at what the term actually means, how it works, and why it matters.