As a Data Engineer, I collect, extract and transform raw data in order to provide clean, reliable and usable data.
Introduction In dbt, the dbt_project.yml file is the backbone of your project configuration. It controls how dbt behaves, where it looks for different resource types, and how your models are materialized and organized. In this tutorial, we'll walk through a sample dbt_project.yml file and...
Introduction When working with PySpark DataFrames, understanding the statistical properties of your data is crucial for data exploration and preprocessing. PySpark provides the describe() and summary() functions to generate useful summary statistics. In this tutorial, we’ll explore how to use both functions to get insights into our dataset. 📥 Import...
Introduction dlt (data load tool) is a powerful Python package that simplifies data ingestion and helps you build efficient data pipelines. In the Extract, Load, Transform (ELT) process, dlt is particularly suited for the Extract (E) and Load (L) stages. In this tutorial, we'll guide you through the...
Introduction In dbt, one of the most essential commands is dbt build. In this tutorial, we’ll dive into the dbt build command, exploring its syntax, functionality, and practical usage. Since this topic is relevant for the dbt Analytics Engineering Certification Exam, this guide will be a valuable resource on...
Introduction Microsoft Fabric provides a powerful platform for managing and analyzing data efficiently. One essential capability within a Fabric warehouse is the ability to create tables, which form the foundation for structuring and storing data. Understanding how to define and create tables is crucial for managing datasets, running analytical queries,...
Introduction Microsoft Fabric provides a robust environment for managing and transforming data within a data warehouse. One of its powerful features is the ability to create stored procedures, which allow for encapsulating SQL logic that can be reused across multiple operations. Stored procedures simplify complex queries, automate repetitive tasks, and...
Introduction Microsoft Fabric provides a robust environment for managing and transforming data within a data warehouse. One of its powerful features is the ability to create functions in a warehouse, enabling reusable logic that simplifies complex queries and enhances efficiency. For the DP-600 certification exam, understanding how to create and...
Introduction An essential feature of Microsoft Fabric is the ability to create views in a data warehouse, enabling data transformation without physical duplication. Views simplify and aggregate data, improving accessibility and efficiency for analysis. For the DP-600 certification exam, knowing how to create and manage views is crucial. This task...
Introduction Microsoft Fabric offers multiple storage and processing solutions for different analytical needs, including lakehouses, warehouses, and eventhouses. For the DP-600 certification exam, understanding when to use each option is crucial for designing efficient data architectures. In this tutorial, you'll learn how to differentiate between lakehouses, warehouses, and...