Typical organisations have hundreds of data sources. This level of complexity (often handled by teams of only a handful of data analysts) can seem unmanageable at first. Each time a new question comes along, the analyst would need to work out which source datasets are relevant, write a query involving many joins, think about how to map different data sources together, and much more.
But this is not what modern data teams do. Instead, they create simplified datasets on top of the source data, expressly designed to help them answer typical business questions quickly. These tables are called data models. Data models can help modern data teams respond more quickly to requests, improve the quality of their data and help knowledge be shared from one person to another.
- Dan Lee (Head of Data @ Dataform): the benefits of building a centralised data model and data modeling principles and best practices.
- Saadat Qadri (Founder of Modern Data Sciences): how data modeling fits into a typical Modern project and the value it brings to their clients.