Learn About Data Structure

Datorama is now Marketing Cloud Intelligence. 

Learning Objectives

After completing this unit, you’ll be able to:

• Explain what a data model is and how it’s used.
• Distinguish between dimensions and measurements in a data set.
• Recognize what an entity is and the relationship between an entity key and entity attributes.

A data model is a predefined structure that’s used to organize data in a database and define the relationships between its elements. In this module, we explain the relationship between different data types and the Marketing Cloud Intelligence data model, describe what data streams are, and go through the benefits of using the Marketing Cloud Intelligence data model. But before we look at the specific Marketing Cloud Intelligence data model, it’s important to understand a few basic principles about data in general.  

Distinguish Between Dimensions and Measurements

Most data sets are made up of a collection of fields that can either be categorized as measurements or dimensions. 

Measurements are simply numbers whose purpose is to count or quantify given dimension values. For example, impressions, clicks, and conversions are data measurements. 

Dimensions are usually a textual description or characteristic of a given field. Examples include campaign name, site name, and creative type. Note that sometimes, dimensions can contain numbers. Since these aren’t for the purpose of quantification, but rather as a form of textual description, they’re still considered to be dimensions. For example, campaign ID may consist of a string of numbers, but only as a form of identification and not for the purpose of summation. 

Dimensions can be further subcategorized into two main groups: entity dimensions and general dimensions.

An entity is an item that you wish to capture and store information about in your database because it is of primary interest to you. Entities are unique and distinguishable from one another, usually by a unique ID or key number. Each entity is also associated with additional characteristics that further describe it. These are called attributes.

If we apply the above definitions to the digital marketing world, a campaign is an entity that is of primary interest to us and the Marketing Cloud Intelligence database, therefore, it has the campaign entity in it. The campaign key dimension is what uniquely identifies a specific campaign and distinguishes it from all other campaigns. All other related campaign dimensions such as the campaign name, campaign category, campaign start date, and so forth, are all in fact attributes of the campaign entity. You can therefore think of it as a container of related dimensions as shown below.

In the Marketing Cloud Intelligence data model, the relationship between an entity key and its attributes is such that an attribute can only ever hold one value per entity key. So, for example, a certain campaign key can only have one campaign name and campaign type at any given moment in time. Similarly, the same campaign can’t have more than one start date, nor can it belong to more than one category at once. 

General dimensions, as the name suggests, are not unique and distinguishable from one another, that is, they’re not entities themselves, nor are they attributes of a given entity. Rather they are an additional breakdown of the data with information such as date, device, and geolocation.

Knowledge Check

Read the task on the card, then click on the card to reveal the correct answer.

For an overview of everything discussed in this unit, check out this video. 

Now that you understand how data sets are structured, you’re ready to dive deeper into the Marketing Cloud Intelligence data model.