3.7. Data Sources in Looker Studio

Data sources play an important role in the backend of our reports since they contain the dimensions, metrics, parameters, and custom fields that we provide to our charts and visualizations.

Understanding Data Sources

Data sources are the backbone of Looker Studio, connecting data sets to charts and visualizations. They receive data from a Data Connector and contain fields (dimensions, metrics, and custom fields). You can perform data modeling, create custom fields, and perform aggregations within data sources.

It's crucial to understand data sources, as they often play a role in any struggles you might encounter when working with data modeling, fields, and connector settings.

Data Source Properties

Data sources have five properties:

1. Title
2. Owner
3. Data credentials
4. Data freshness
5. Scope (either embedded or reusable)

Let's explore data credentials and how they control who can view data from connected data sources.

Data Credentials: Owner vs. Viewer

Data credentials determine who can access the data in a secure dataset connected to a Looker Studio dashboard. When the data source is set to use the owner's credentials, the data flows into Looker Studio, and anyone viewing the report can see the data. To control access, you must manage who can view the report itself.

However, there's another way to manage data access: viewer credentials. With viewer credentials, each individual viewer's credentials are used to authorize access to the data.

If a viewer has access to the underlying dataset, they can see the data in the report. Otherwise, they can view the report, but the charts will be broken. This approach can be helpful in situations where you want to give access to data only to those who already have access to the underlying dataset.

Understanding how data sources and credentials work in Looker Studio is vital for managing data access and ensuring the right people have access to the right data.

In this chapter:

→ 3.2. Bringing in Your Data

→ 3.3. Data Connectors

→ 3.4. Live vs Warehoused Connectors

→ 3.5. Google Connectors

→ 3.6. Partner Connectors

→ 3.7. Data Sources

→ 3.8. Data Source Scope: Embedded vs Reusable

→ 3.9. Caching & Data Freshness

→ 3.10. Managing your Data Sources

→ 3.11. Assignment

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