How Data Modeling improves data and report quality and reduces requirements for analyst experience

Usually, all the discussions about the Modern Data Stack devote a lot of time to instrumental issues: choosing an ETL tool, a data visualization tool, etc. But not much is usually said about the importance of data modeling and documenting modeled datasets.

We will talk about the evolution of our approach to client analytics projects: what is data modeling, and why data modeling became the most important phase of our projects. We'll talk about what changes when we begin a project with creating a data model:

• the dataset is fully documented "by design" and keeping the documentation updated and consistent is the integral part of the process;
• new analysts can join the project and begin effectively contributing in half a day;
• data lineage “out of the box” without additional tools;
• you can add (well, almost) any number of analysts to the project, and the speed of project development grows linearly.