From ETL mishaps to data triumphs - chronicles of a data whisperer.
I share expert insights on Azure Data Factory, SQL Server, ETL, and Python — everything I’ve learned (and broken) along the way. Whether you're building your first data pipeline or scaling enterprise systems, you’ll find actionable tips, reusable patterns, and real-world solutions here.
What is data engineering? What is it important to businesses? Today we examine and explain these topics.
Data engineering is a complex field and you will need to have a wide array of tools in your toolkit to be able to excel. You have an important role in ensuring timely and accurate data insights for analysts, data scientists, and other stakeholders.
Learn the technical and soft skills needed in data engineering.
Building robust Azure Data Factory (ADF) pipelines is crucial for efficient and reliable data workflows. This guide explores essential practices such as implementing reusability, retry mechanisms, error alerting, and avoiding unnecessary loops. By leveraging tools like Logic Apps for notifications and incorporating version control and CI/CD, you can create scalable, maintainable, and cost-effective pipelines that minimize downtime and deliver consistent results.
Master the basics of Azure Data Factory (ADF) with this step-by-step guide to integrating API responses with SQL. Learn how to use web activities for fetching JSON data, write responses to Azure Blob Storage, normalize data with data flows, and load it into a staging SQL table using the copy activity.