Get Started with Data Cloud Credit Consumption
Learning Objectives
After completing this unit, you’ll be able to:
- Explain how Data Cloud consumes credits.
- Identify strategies to reduce credit consumption.
This content only applies to customers with a Data Cloud license. Data Cloud customers whose orgs are contracted as Customer Data Platform orgs should refer to Customer Data Platform Billable Usage Calculations.
What Are Data Cloud Credits?
Data Cloud credits are digital currency that you use to pay for Data Cloud services. Data Cloud pricing is consumption-based, meaning you only spend as many credits as the services you use. You can directly impact your cost by controlling your usage. This makes Data Cloud pricing flexible for different use cases. A small company that’s just getting started with Data Cloud and has simple projects consumes far fewer credits compared to a company with large datasets and complex projects. With consumption-based pricing, it’s important to plan your usage so you don’t accidentally consume more credits than anticipated.
Depending on your use cases and add-on licenses, there are various types of credits for Data Cloud, such as specific marketing credits for segmentation and activation, and a specific amount of data storage.
Refer to Data Cloud Billable Usage Types to learn about types of credits in more detail.
What Consumes Data Cloud Credits?
You have a Data Cloud license, and you have your credits. Now what? It’s time to start using Data Cloud. Let’s see how it works.
When you use a service in Data Cloud, you generate a usage event. Usage events consume credits, and each usage event has a usage type. We can group each usage type under a consumption category. The consumption categories reflect the main goals within Data Cloud.
There are three consumption categories and associated usage types.
- Connect: Connect streaming and batch data to Data Cloud. Or connect data from Snowflake, Databricks, or BigQuery using data federation.
- Batch Data Pipeline
- Streaming Data Pipeline
- Data Share Rows Shared (Data Out)
- Batch Data Pipeline
- Harmonize: Transform, map, and unify your data in Data Cloud.
- Batch Profile Unification
- Segment Rows Processed
- Batch Calculated Insights
- Streaming Calculated Insights
- Batch Profile Unification
- Activate: Act on your data by creating insights, building AI functionality, querying for reports and dashboards, integrating data with apps, and creating automations.
- Accelerated Data Queries
- Data Queries
- Data Federation or Sharing Rows Accessed
- Inferences
- Real-Time Profile API
- Streaming Actions (including lookups)
- Batch Activation
- Accelerated Data Queries
As an example, when you ingest data through MuleSoft using a batch data pipeline, you generate a usage event with the batch data pipeline type, under the connect consumption category.
Calculate Your Cost
Each usage type has a unit and multiplier. The unit represents how much data is considered 1 unit of usage. This is 1 million for every usage type. For Data Cloud, the multiplier represents how many credits are consumed by 1 unit of usage. Multiply this number by your usage to get the total credits consumed. Refer to the rate card linked in the Resources section for current multipliers. To calculate how many credits are consumed in a usage event, you need to know the usage type, the multiplier for the usage type, and how much data was processed.
d represents the total amount of data processed. m represents the multiplier for the usage type.
Credits consumed = (d/1,000,000) * m
Let’s calculate credit consumption for creating a batch calculated insight (CI) on 2 million rows of data. Set d to 2,000,000. For this example, set m to 15.
(2,000,000/1,000,000) * 15 = 2 * 15 = 30 credits
Credits are consumed again when the CI refreshes. We set the CI to refresh every day. By the next day, our data grew to 2,200,000 rows.
(2,200,000/1,000,000) * 15 = 2.2 * 15 = 33 credits
The CI will cost more and more credits as the data grows.
Make Your Credits Count
It’s important to find ways to optimize your use of Data Cloud and accurately meet your needs with what you purchase. Here are strategies to cut back on extra usage.
- Opt for batch over streaming. Streaming processes data in real time, but at a cost. Streaming CIs cost 55 times more than batch CIs. If your use case isn’t time sensitive, save credits by using batch data.
- Deactivate projects that aren’t being used, such as outdated segments that are still running.
- Only bring in relevant data for your use case. For example, limit the profiles you bring in to those that were active within the last year.
- Process data less often. For example, if the use case for your CI isn’t time sensitive, set it to refresh every day instead of every hour.
Monitor your credit usage, discover trends, and identify patterns for better budgeting with Digital Wallet. Learn more in the Salesforce Digital Wallet: Quick Look module.
Taking a proactive approach to credit usage is the first step in designing cost-efficient projects in Data Cloud. Now you understand how Data Cloud consumes credits and how to optimize your Data Cloud credits.