The Unbundling of SaaS Analytics
The modern data stack is on the rise. Many companies use raw data from their SaaS analytics tools as input for their data warehouse, but this introduces problems downstream. Are there better ways? When Google Analytics launched nearly 20 years ago, it took the market by storm.
The Death of Data Modeling - Pt. 1
👋 Hi folks, thanks for reading my newsletter! My name is Chad Sanderson, and every week I talk about data, data products, data modeling, and the future of data engineering and data architecture. In today's article, I will be diving into data modeling - why I think it's critical to any data infrastructure, and why it needs a revamp for the 21st century.
A path towards platform that aligns data, value and people
The potential of today's cloud data ecosystem is compelling: Get data from anywhere in the business and build powerful reporting on top of it. It's now available to any company as a combination of SaaS and open source tools. And it indeed delivers. But with great new power comes a new challenge, especially as the company scales.
Top 10 metrics for a Data Team - Castor Blog
Measuring data ROI is one of the top challenge of data teams. There are many ways to do it, and no established best practices. In a previous article inspired by discussions with data leaders, we sought to identify the skeleton of a framework for measuring data team's performance.
How should analysts spend their time
When I was at Google and started building machine learning models, one of the first things I was shown was the image below. It highlighted that writing the actual machine learning code is only a fraction of the total work I'd be doing. This turned out to be true.