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The Team Data Science Process (TDSP) is an agile, iterative data science methodology to deliver predictive analytics solutions and intelligent applications efficiently. TDSP helps improve team collaboration and learning by suggesting how team roles work best together. TDSP includes best practices and structures from Microsoft and other industry leaders to help toward successful implementation of data science initiatives. The goal is to help companies fully realize the benefits of their analytics program. This article provides an overview of TDSP and its main components. We provide a generic description of the process here that can be implemented with different kinds of tools. A more detailed description of the project tasks and roles involved in the lifecycle of the process is provided in additional linked topics. Guidance on how to implement the TDSP using a specific set of Microsoft tools and infrastructure that we use to implement the TDSP in our teams is also provi...

Today we released the dbt Integrated Developer Environment (IDE) into general availability in dbt Cloud. With the IDE, you can build, run, test, and version control dbt projects from your browser. There’s no wrestling with pip, homebrew, hidden files in your home directory, or coordinating upgrades across large teams. If you haven’t already, be sure to check out Tristan’s post on why we built the IDE and why we think it’s such a meaningful development in the analytics engineering space. Otherwise, read on to learn more about what you can do with the IDE and what’s next for dbt Cloud. Read full post >>>