The Puzzle Pieces of a Modern Data Stack

Madison Schott
8 min readJun 22, 2022

Data warehouse, ingestion, transformation, orchestration, and monitoring

Photo by Ashkan Forouzani on Unsplash

Modern data stacks have grown in popularity since we realized how important data really is to a business. They came about as we moved from on-prem data storage to the cloud, allowing us to access our data quicker and easier than ever. These stacks have now enabled us to move data at record speed, from the creation of the data all the way to the insights that we draw from it.

Modern data stacks allow us to automate the process of ingesting, transforming, and scheduling data. They make it easier to create a seamless workflow that delivers insights in the blink of an eye. Not only this, but they also allow for a real-time picture of our data. We no longer have to wait days or weeks to receive last week’s numbers or reports. We can make decisions for our business based on what consumers need now.

There is no question that the modern data stack holds a lot of value, but how do we reach that point? What are the technical pieces that allow for automation and instant access to data we trust? In this article, I’ll be walking you through the pieces of the puzzle. More specifically, we will discuss the role of a data warehouse in the data stack, ingestion, transformation, orchestration, and monitoring. Lastly, you will understand how all of these pieces fit together to make visualization (the last part of the stack) possible. I will even introduce you to a tool that allows you to use all of these pieces cohesively within one platform.

Data warehouse

The data warehouse is your modern data stack’s hub. Nothing can reach your data without accessing the warehouse. It’s the one thing that connects all the other pieces to each other.

Your ingestion tool will load data into your data warehouse. Your transformation tool will aggregate, join, and manipulate tables within this warehouse. Your monitoring and orchestration tools will deploy your data models to various locations within your warehouse. And lastly, your visualization tool will connect to it directly in order to display the transformed data.

All data is flowing in and out of your data warehouse. You need to pick one that’s hosted on the cloud and accessible by anyone, anywhere. We…

Madison Schott

Analytics Engineer @ Winc, author of the Learn Analytics Engineering newsletter and The ABCS of Analytics Engineering ebook, health & wellness enthusiast