📘 Introduction When you start learning modern data pipelines, you will quickly hear about both dlt and dbt. The names look similar, and both tools are used in data engineering workflows. But they solve different problems. In this beginner-friendly guide, we will explain the difference between dlt and dbt, where each...
📘 Introduction dbt Fusion is one of the biggest changes in the dbt ecosystem. If you already know dbt Core, you can think of Fusion as a new engine underneath the familiar dbt workflow. You still write models, define dependencies, configure YAML files, define tests, and build transformation logic in SQL....
📘 Introduction When you start learning dbt, you will quickly come across many new terms: models, materializations, seeds, snapshots, tests, macros, DAGs, packages, profiles, and targets. At first, these concepts can feel confusing, especially if you are new to analytics engineering or modern data pipelines. In this beginner-friendly guide, we’ll...
📘 Introduction Working with structured data is a core part of any data engineering or analytics workflow. DuckDB, often called the SQLite for analytics, makes it incredibly easy to query local data files—including JSON—without requiring a complex setup. In this tutorial, you’ll learn how to load JSON data...
📘 Introduction In this tutorial, you’ll learn how to load data from a Parquet file into a DuckDB database using Python. DuckDB’s native Parquet support makes it fast and efficient to work with columnar data, making it ideal for analytics, ETL pipelines, and Python data projects. You’ll see...
📘 Introduction In this tutorial, you will learn how to insert data from a CSV file into a DuckDB database using Python. DuckDB is a powerful in-process analytical database that makes working with structured data fast, simple, and efficient—perfect for data projects, notebooks, and local analytics. ✅ Prerequisites Before you begin,...
📘 Introduction DuckDB has quickly become a favorite tool among data engineers and analysts because of its speed, simplicity, and ability to run analytical SQL queries directly within Python. Whether you’re prototyping data pipelines, running local analytics, or managing lightweight data storage, knowing how to insert data into DuckDB is...
📘 Introduction Renaming columns is one of the most common transformations you’ll perform when cleaning or standardizing data in PySpark. Whether you’re aligning tables from different systems, preparing data for machine learning, or simply making column names more readable, updating many column names at once can quickly become tedious...
📘 Introduction One of DuckDB’s most useful features is the ability to query CSV files directly—no need to load them into a database first. This tutorial will guide you through running SQL queries on a CSV file using Python. ✅ Prerequisites Before you begin, make sure you have: 🐍☑️ Installed Python...