#454: Data Pipelines with Dagster

The cloud is convenient until it isn't. You upload your photos, sync your contacts, click through the cookie banners. Then prices go up again or you read about a family that lost their entire Google account over a medical photo sent to a doctor. At some point, the question shifts ...  Show more

The OWASP Top 10 just got a fresh update, and there are some big changes: supply chain attacks, exceptional condition handling, and more. Tanya Janca is back on Talk Python to walk us through every single one of them. And we're not just talking theory, we're going to turn Claude ...  Show more

<div class="wp-block-jetpack-markdown"><h2>Summary</h2>

Python has beome the de facto language for working with data. That has brought with it a number of challenges having to do with the speed and scalability of working with large volumes of information.There have been many ...

Modern networked applications generate a lot of data, and every business wants to make the most of that data. Most of the time, that means moving production data through some transformation process to get it ready for the analytics process. But what if you could have in-app an ...

<h2>Summary</h2>

A core differentiator of Dagster in the ecosystem of data orchestration is their focus on software defined assets as a means of building declarative workflows. With their launch of Dagster+ as the redesigned commercial companion to the open source project t ...

<h2>Summary</h2>

Maintaining a single source of truth for your data is the biggest challenge in data engineering. Different roles and tasks in the business need their own ways to access and analyze the data in the organization. In order to enable this use case, while mainta ...