Explore Data Classifications

Datorama is now Marketing Cloud Intelligence. 

Learning Objectives 

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

• Describe data classifications.
• Identify why data classifications are required.
• Explain how data classifications harmonize data.

Data Classifications

Data classification is the grouping of certain dimension values that share a common theme. For example, the following site names can be classified by a set of site type classifications:

Once classified, data can be analyzed at the level of the classification groupings, rather than at the level of each individual site. This is important because it allows an additional layer of analysis, with higher-level insights. Here’s an example: Imagine you’re running an advertising campaign and want to identify the type of site that is generating the highest clickthrough rate. This kind of analysis can easily be achieved by creating a classification based on site type (as shown earlier), and then sorting these classifications for the highest clickthrough rate.  

How Do Data Classifications Harmonize Data? 

When creating a data classification, it applies to all data from all sources—as long as that data complies with the classification rule. Let’s use the site name example from before. Imagine your workspace has data from two different sources, and both relate to the site name values used in the data classification example. The data classification that has been set up for the site type applies to both of these data sources because they both have data that complies with this rule. In visualizing this data, you would see data from these two sources perfectly aligned for every shared site type classification. This means that the data is effectively harmonized using the data classification.

Check out this video to learn more about creating data classifications.

Create a Data Classification

In this module, we assume you are a Marketing Cloud Intelligence admin with the proper permissions to create data classifications and patterns. If you’re not, that’s OK. Read along to learn how your administrator would take the steps in a production org. Don’t try to follow these steps in your Trailhead Playground. Marketing Cloud Intelligence isn’t available in the Trailhead Playground.

In order to create a data classification using the harmonization center, all you need to do is upload a classification file into the data classification tool. This file must have one column with the dimension values that need to be classified, referred to as the key column. And you need at least one column with the classification values, referred to as a classification column.

In addition to dropping an external classification file into a data classification, you can also create one from within the tool itself.

To access the data classification tool, in Marketing Cloud Intelligence navigate to Connect & Mix > Harmonization Center > Data Classification. Then select Add New. Next, name your classification rule (1), select the dimension to apply the classification (2), and then add your classification file (3).

Each file can have multiple classification columns, meaning that each dimension value (under the key column) can have multiple classifications. In the following example, each site name has a site type and an audience age group classification.

Being able to classify data is part of effective data management and analysis. Being able to do it with such ease, using the data classification tool, is a bonus. In the next unit, we introduce two more powerful tools that take your harmonization capabilities to the next level: patterns and harmonized dimensions.