4.1. Introduction to Data Modeling

After learning the dashboard planning framework and understanding data connectors and data sources, we can now model (or transform) our data before visualization.

In this chapter we will cover Data Modeling: how to shape, process, and clean data before we visualize and share it to others.

Specifically, in this chapter we will discuss:

• Data Sources
• Aggregation
• Working with Numbers
• Scope of Custom Fields

Data Modeling within Data Sources

We learned in the previous lessons that the first place we can perform data modeling is at the source, such as setting a goal in Google Analytics or labeling campaigns in an Ad platform. And the second place we can perform data modeling on is at the Data Connector level.

Modeling data at the source (the tool) and within the data connector (such as how it can be done in partner connectors like Dataddo, Supermetrics, or Funnel.io) are out of the scope of this course. Mainly because those are specific to the tool being used, and not the core functionalities of Looker Studio.

In this chapter we will cover the third place where we can transform data to make it ready for visualization in Looker Studio, which is at the Data Source level.

Every Chart is a Table

It’s fundamental to understand this concept: At its core, every chart or visualization is a table, with rows, and columns.

When we perform data modeling, we do it while presenting data as a table. We will cover why in the next lessons.

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