Write Simple Data 360 SQL Queries

Learning Objectives

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

• Describe the structure of a basic Data 360 SQL query.
  
• Select specific fields from data model objects (DMOs) and data lake objects (DLOs).
  
• Explain the role of the key qualifier (KQ_Id__c) in Data 360 records.
  
• Apply basic comments to your SQL code for improved readability.
  

As of October 14, 2025, Data Cloud has been rebranded to Data 360. During this transition, you might see references to Data Cloud in our application and documentation. While the name is new, the functionality and content remains unchanged.

Sign Up for a Custom Playground with Data 360

To complete this badge, you need a special, limited-time custom playground that contains Data 360 and our sample data.

1. Click Create Playground.
   
2. Your new org is automatically attached to your Trailhead account!
   
3. Make note of your org’s expiration date and complete this badge before then.
   

Connect Your Data

Connections in Data 360 are started by setting up data streams, which are data sources either connected or ingested into Data 360. The data from those data sources are stored in data lake objects (DLOs), which are storage containers for data stream data. If data needs manipulation, formula fields can be created to normalize your data or to create basic calculations.

Create a Data Stream

Data is ingested into Data 360 through data sources. Data sources can be other Salesforce orgs, Marketing Cloud Engagement business units, external platforms, and CSV files. For this badge, we’ve already connected a Sales Cloud and Service Cloud org to your Developer org. Now that these data source connections are already established, you can add data streams to Data 360. 

1. Once you’re logged in, search for and select Data Cloud from the App Launcher.
   

2. In Data Cloud, go to the Data Streams tab and click New.
   
3. Click Salesforce CRM under Connected Sources, and click Next.
   
4. Note the Salesforce Org is preselected. From View Bundles, choose the Sales data bundle and click Next.
   

5. View the associated fields and click Next. It can take a few minutes for the fields to appear.
   
6. Notice that the default Data Space is preselected and all the fields included in the bundle are listed. Leave the selections as is, and click Deploy.
   

Deployment can take a few minutes. If you run into any issues, wait a few minutes and then retry the deployment again. 

Six new data streams are now created. Next, add some additional data streams to connect Service Cloud case data to Data 360.

Add Data Streams

1. From the Data Streams window, click New.
   
2. Select Salesforce CRM and click Next.
   
3. Select View Objects (1) and search for Case (2).
   
4. Select both Case and Case History and click Next.
   

5. Under Objects starting with Case, keep the name the same (Case_Home) and select Engagement from the Object Category dropdown.
   
6. Then select Created Date from the dropdown for Event Time Field.
   
7. Click CaseHistory2. Keep the same name (CaseHistory2_Home), and select Other for the Object Category.
   
8. Click Next.
   
9. Check that the default data space is selected and click Deploy.
   

Create Your Query Workspace

Set up your environment for analysis.

1. In Data Cloud go to the Query Editor tab and click New.
   
2. For the Workspace Name, enter Customer Data Quality.
   
3. Leave the Data Space as Default.
   
4. Click Save.
   

By creating this workspace, your queries operate within the correct security and access protocols, and you can find the right objects for your analysis.

Write Your First Query

Every journey into data begins with asking a question. In Data 360 SQL, you ask your question by writing a query. A basic query has two required clauses: SELECT and FROM.

• The SELECT clause specifies which columns (fields) you want to retrieve.
  
• The FROM clause specifies the source of the data, which is always a data model object (DMO), data lake object (DLO), or calculated insight object (CIO).
  

Let’s see this in action. You can retrieve every field from the DMO by using the asterisk (*) wildcard in the SELECT clause to get a quick list of all individual records in Data 360.

SELECT *
FROM ssot__Individual__dlm

While SELECT * is fast for writing a query, it’s rarely a best practice because it can return a very large amount of data and slow down your query.

Select Specific Fields

A much more efficient approach is to list only the specific fields you need. This makes your query run faster and returns a result set that is focused on the data required for the analysis.

For an initial report, you only need the first name and ID.

SELECT ssot__FirstName__c,
       ssot__Id__c
FROM ssot__Individual__dlm

Understand the Key Qualifier Field

When working with Data 360 records, you'll frequently see a field called KQ_Id__c, or key qualifier ID. Understanding this field is critical for ensuring data accuracy when joining data later in this module.

The KQ_Id__c is an internal identifier that helps track the source and uniqueness of a record within the Data 360 system.

• Every record in a DMO has a unique combination of its primary ID (like ssot__Id__c) and the KQ_Id__c.
  
• This identifier is often used in Data 360 to ensure that when you are combining data from multiple objects, you are correctly linking the specific version of a record you intend to use.
  

It’s easiest to remember that the primary ID identifies the individual entity and the KQ_Id__c helps you identify the specific source record for that entity.

Add Comments as a Best Practice

As your queries become more complex, especially when collaborating on a team, readability is critical. You can add comments to your SQL statements to explain logic, note assumptions, or temporarily disable parts of your code. Comments are ignored when the query executes.

You can use two types of comments:

• Single-line comments: Use two hyphens (--) at the beginning of a line or to comment out the rest of a line.
  
• Multi-line comments: Enclose the text in /* and */ for comments that span multiple lines.
  

Create and execute the following query to practice what you learned in this unit.

Write and Run Your Query

In the Customer Data Quality workspace, execute your SQL statement.

• In the main editor window, paste this query to view individual records:
  

/*
This query retrieves all essential individual
records for Cara Ng's initial customer report.
The field list is explicit for performance optimization.
*/
SELECT ssot__FirstName__c,
       ssot__LastName__c,
       ssot__Id__c, -- Individual ID is critical for matching with other systems
	KQ_Id__c
FROM ssot__Individual__dlm
LIMIT 10

• Click Run Query in the top left of the editor.
  
• Review your results in the Query Result panel at the bottom of the screen.
  

Save Your Query

After confirming your results are correct, click the Save button in the top right corner of the workspace.

Now that you know the structure and best practices for simple queries, check that you set up your first workspace and query correctly by clicking the Check Challenge for 500 points.

Resources

• Data 360 Query Guide: Get Started with Data 360 SQL
• Data 360 Query Guide: Data 360 SQL Reference
• Data 360 Query Guide: SELECT