Datenmodellierung in Sigma

In this chapter, you'll learn about the core use cases for data models in Sigma. Using a data model, you can create custom data sources that are available to other Sigma documents in your organization. This will enable you to scale, govern, and maintain your team's insights, analytics, and apps.

In this chapter, you’ll learn how to scale insights outside a single table using metrics and relationships. You'll build an example of each of these core data model features, and then see them in action in a workbook, so you can understand the impact first-hand. After learning about these features, you'll be able to provide calculations across an analytics team, and control join logic centrally from a data model while still offering flexibility to users.

In this chapter, you'll learn about two advanced data model features (parameters and column security) before carrying on to implement everything you've learned in one final example. Parameters will give you the ability to configure flexible filters on your models, and security will help you keep sensitive data safe. Then, by combining all the features and best practices you've learned up to this point, you'll get a chance to cement your mastery of scalable analytics.