CTE (Common Table Expression) is a temporary result set defined within the execution scope of a single SELECT, INSERT, UPDATE, or DELETE statement.
Category Archives: SQL
Data Warehousing Explained: Star Schema vs. Snowflake Schema
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.
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Business Intelligence with Python and SQL: A Beginner’s Guide
In Business Intelligence (BI), SQL is used to extract and manipulate data from databases, while Python adds flexibility for data processing, visualization, and automation. Combining both enables you to build powerful, automated BI pipelines and dashboards.
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Hive SQL vs Regular SQL: A Practical Guide for Data Engineers and Analysts
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.
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How a WHERE Clause Can Break Your LEFT JOIN — and How to Fix It
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.
Understanding Partitioning in Databases: What p_date Means and Why It Matters
As data grows larger and more complex, optimizing for performance and scalability becomes essential. Partitioning is one of the most powerful strategies for managing big datasets efficiently. If you’ve come across a column like p_date in an SQL query, it often signals the use of table partitioning. But what does that mean, and how is it different from traditional databases?
Mastering SQL LEAD and LAG Functions: Advanced Data Analysis
SQL window functions like LEAD and LAG are indispensable tools for business intelligence and data analysis, enabling professionals to uncover trends, track changes, and derive actionable insights. In this guide, we’ll break down how these functions work and demonstrate their real-world applications in SQL-driven analytics.
Advanced SQL: Windows Function Cheat Sheet
SQL window functions are one of the most powerful tools for performing calculations across a defined range of rows while maintaining access to individual row-level details. Unlike aggregate functions that collapse rows into a single value, window functions allow you to perform calculations over a subset of rows (a window) while preserving the original row structure.
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The Ultimate Guide to SQL Functions for Data Analysts
If you work with data, SQL functions are your toolkit for unlocking powerful insights. Whether you’re crafting detailed reports or uncovering business-changing analytics, SQL is the backbone for data doers in every industry. This guide explores 27 SQL functions that every data analyst, data engineer, or analytics enthusiast should know. These functions are grouped into five categories for easier understanding and practical use.
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SQL to Hive — Commonly Used Hive Syntax and Features
I recently encountered a project that uses HIVE table, coming from microsoft sql , mysql background, I had a little struggle with different sql syntax and behavior, thought I’d write this article on some common SQL to Hive conversions in case you are ever in similar situation.
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