Last Updated on November 6, 2022 by Rakesh Gupta

Big Idea or Enduring Question:

• How to save recipe results to more than one dataset? 

Objectives:

After reading this blog, you’ll be able to:

• Understand CRM Analytics recipe and dataset
• Create a recipe by joining tables 
• Save recipe outcomes to two datasets

Business Use Case

Donna Serdula is a System administrator at Gurukul On Cloud (GoC). She just started learning CRM analytics from Trailhead and got the following requirements from her manager:

1. Create a dataset combining Opportunity and Account using Account Id (using lookup join)
2. Save the recipe result to two datasets
   1. OpportunityWithAccount_1
   2. OpportunityWithAccount_2

Automation Champion Approach (I-do):

A dataset is a set of source data specially formatted and optimized for interactive exploration. Dataset is used to create lenses and dashboards.

A recipe is an alternate way to create a dataset. Recipes must be created from an existing dataset or connected data (data sync) and are built in a visual interface called Data Prep.

With recipes, you can able to do the following:

• Combine data from multiple datasets or synced data
• Transform (Buket, formula field, change field attributes, etc.) or filter fields
• Add or remove fields
• Write the recipe result to datasets, connections, or CSV files

Connect disconnected nodes or branches to join or append data from any node to any other node in a recipe. You can also create a branch at an intermediate node and join or append it to another path in the recipe.

Guided Practice (We-do):

There are 7 steps to solve Donna’s business requirement using CRM Analytics Recipe. We must:

1. On the Data Manager app page, navigate to Data Manager | Recipes | New Recipe.
2. Click Add Input Data option, and select the check box next to the connected object Opportunity.
   1. In the Selected Columns area on the right, you can choose columns to include selected input data or all columns to automatically update every available column when the recipe syncs.
3. Click Next.
4. The next step is to add the join node to bring data from the account object. 
   1. Click Add Node and select Join.
   2. Select the connected object Account to join and choose which columns to include.
   3. Click Next.
   4. Select the join type, i.e., Lookup 
   5. Select Account Id as the Join Key. 
   6. Use the Preview tab to preview columns and their data. 
   7. Once ready, click Apply to add the node to the recipe.
5. It’s time to save the recipe result to the first dataset.
   1. Click Add Node button from a single node and select Output.
   2. Enter the dataset name – OpportunityWithAccount_1 and other details.
6. Let’s save the recipe result to another dataset.
   1. To create a branch and join or append it to another path, hover over a node to select the Branch button.
   2. Select Output.
   3. Enter the dataset name – OpportunityWithAccount_2 and other details.
7. Almost there! Once everything looks good, click the Save and Run button.
8. Click Save again. 
   

Schedule a Recipe to Run Automatically

You can run your recipes automatically at the scheduled time or after an event. For example, Use time-based scheduling to ensure that new data is available to your dataset. Use event-based scheduling to run a recipe after the sync runs to ensure that datasets include the latest data.

You can schedule a recipe to run hourly, weekly, monthly, or on specific days of the week or dates.

1. In the data manager, click the Recipes tab.
2. Click the drop-down to the right of the recipe name you want to run, and select Schedule.
3. Select the Scheduled Mode and the time to run the recipe.

Proof of Concept

The Jobs subtab under data manager shows the status of data sync and recipe CRM Analytics jobs. You can view error messages about a job, the run-time details about every transformation processed, and monitor the number of jobs remaining from your org’s 24-hour limit.

Once the job status is changed to Successful, navigate to Data Assets tab to access newly created datasets.

Formative Assessment:

I want to hear from you!

What is one thing you learned from this post? How do you envision applying this new knowledge in the real world? Feel free to share in the comments below.