Tom Fynes

If you're building a data warehouse, dimensional modeling is your best friend. It makes data easier to query, understand, and analyze. Let's break down this powerful technique!

What is Dimensional Modeling?​

Dimensional modeling is a design technique optimized for data retrieval and analytics. Unlike transactional databases (OLTP) which are optimized for writes, dimensional models (OLAP) are built for blazing-fast reads and intuitive queries.

Think of it as organizing your data warehouse like a well-structured library, where finding what you need is quick and intuitive.

Bad data leads to bad decisions. As data engineers, one of our most important jobs is ensuring data quality. Let's explore how to validate and maintain high-quality data!

Why Data Quality Matters​

Imagine your CEO making a million-dollar decision based on a dashboard... that's pulling from corrupted data. Scary, right? Data quality isn't just a nice-to-have - it's essential for:

• Accurate analytics and reporting
• Reliable machine learning models
• Regulatory compliance
• Customer trust

Apache Airflow has become the go-to tool for orchestrating data workflows. If you've ever needed to run tasks in a specific order, on a schedule, with dependencies - Airflow is your friend!

What is Apache Airflow?​

Airflow is a platform to programmatically author, schedule, and monitor workflows. Think of it as a smart scheduler that can:

• Run tasks in the right order
• Retry failed tasks automatically
• Send alerts when things go wrong
• Provide a beautiful UI to monitor everything

Choosing a database feels a bit like choosing a car - there's no single "best" option, only the best option for your specific needs. Let's navigate this together!

The Big Question: SQL or NoSQL?​

This is usually where everyone starts, but here's the thing - it's not an either/or decision anymore. Many projects use both!

Hey there! If you're stepping into the world of data engineering, you've probably heard the term "data pipeline" thrown around quite a bit. Let's break down what they are and why they're so important.

What is a Data Pipeline?​

Think of a data pipeline as a highway for your data. It's a series of steps that move data from point A (your source) to point B (your destination), with some transformations happening along the way. Just like a real pipeline moves water, a data pipeline moves data!