JSON (JavaScript Object Notation) has become the universal language for exchanging data between applications. Whether you’re pulling data from APIs, storing logs, or dealing with semi-structured data in a data lake — JSON is everywhere.

If you’ve worked with SQL for data analysis, you’ve probably used the SELECT DISTINCT keyword to remove duplicate rows. But at some point, you might come across another term — SELECT UNIQUE.

As data volumes continue to grow exponentially, traditional SQL engines often struggle to handle massive datasets efficiently. That’s where Apache Spark SQL comes in — a powerful module that combines the scalability of distributed computing with the simplicity of SQL syntax.

When building data warehouses, you’ll often face a classic challenge: how to track changes in dimension data over time. For example, what if a customer moves to a new city? Should you overwrite their old address or keep the historical record?

When working with databases, business analysts often come across two common objects: stored procedures and views. Both play a key role in querying and managing data, but they serve different purposes. Understanding their differences helps analysts write better queries, collaborate effectively with engineers, and choose the right tool for their reporting needs.

CTE (Common Table Expression) is a temporary result set defined within the execution scope of a single SELECT, INSERT, UPDATE, or DELETE statement.

When you’re building a data warehouse, the way you model your data can make the difference between fast, intuitive analytics and a never-ending maze of joins. Two of the most common data modeling approaches are Star Schema and Snowflake Schema. Both serve the same purpose—structuring your data to support reporting and analysis—but they differ in design, performance, and usability.

In the world of data processing, SQL is the lingua franca—but not all SQLs are created equal. If you’ve worked with big data tools like Apache Hive, you’ve probably noticed that Hive SQL isn’t exactly the same as traditional SQL used in relational databases like MySQL, PostgreSQL, or SQL Server.

TL;DR:
If you’re using a LEFT JOIN but filtering on the right table in the WHERE clause, you might unintentionally turn it into an INNER JOIN. Here’s why that happens, how to fix it, and how different databases handle it.