Create Your DailyAggregation CRM Analytics Recipe

You join your raw package log file data with your License Management App (LMA) data to create the DailyAggregation CRM Analytics recipe. The recipe produces a dataset called DailyAggregation that you use to create App Analytics recipes.

In your org in Analytics Studio in CRM Analytics:

1. Click Data Manager.

2. Click Dataflows & Recipes.

3. On the Recipes tab, click Create Recipe.

4. Click Add Input Data.

5. Select RawPackageLogFile.

6. Select all the columns.

7. Create an aggregate with these specifications.

   Field	Aggregate By
   event_count	Sum
   login_key	Unique
   num_fields	Sum
   num_soql_queries	Sum
   operation_count	Sum
   rows_processed	Sum
   session_key	Unique

8. In the aggregate, in Group Rows, click +, and select timestamp_derived.

   1. Select Year, Month, and Day.
   2. Click Add.

9. In the aggregate, in Group Rows, create a group for each of these fields.

   • api_type
   • api_version
   • app_name
   • class_name
   • cloned_from_organization
   • custom_entity
   • custom_entity_type
   • entry_point
   • event
   • event_subscriber
   • http_method
   • http_status_code
   • log_record_type
   • managed_package_namespace
   • method_name
   • operation_type
   • organization_country_code

10. Create a transform named Create DMY Field with this formula.to_date(concat(timestamp_derived_DAY,"/",timestamp_derived_MONTH,"/",timestamp_derived_YEAR),"dd/MM/yyyy"))

11. Join your RawPackageLogFile dataset to your LMAData dataset using this information.

    • Select Input Data to Join: LMAData
    • Columns to Select: All fields
    • Join Type: Lookup
    • Join Keys: organization_id = Subscriber Org ID and package_id = PackageID15
    • API Name Prefix for Right Columns: LMAData

12. Join your country-codes dataset to your LMAData dataset using this information.

    • Select Input Data to Join: country-codes
    • Columns to Select: All fields
    • Join Type: Lookup
    • Join Keys: user_country_code = ISO3166-1-Alpha-2
    • API Name Prefix for Right Columns: UserCountry

13. Create a transform named Feature Name.

    1. Create as many CRM Analytics buckets as you need for your features, such as Inventory, Orders, and a catch-all bucket called Other.

    2. A CRM Analytics bucket represents a category that you use to group your data. For example, say your app contains multiple features, such as an inventory tracking feature and an order processing feature. Create a CRM Analytics bucket for each feature. Each bucket contains the custom objects, pages, Lightning components, and Apex classes that pertain to that feature. You can use these buckets to create Feature Adoption App Analytics recipes

       Add your custom entities to the appropriate bucket.

14. Select Output and use these settings.

    • Write To: Dataset
    • Dataset Display Label: DailyAggregation
    • App Location: PartnerIntelligence
    • Sharing Source: default
    • Security Predicate: Apply row-level security to the target dataset by adding a predicate filter condition
    • Name: Create Daily Aggregation Dataset

15. Click Apply.

16. Click Save.

17. Name your recipe DailyAggregation.

18. Click Save and Run.

When complete, your DailyAggregation recipe looks like this.

1. Monitor the DailyAggregation CRM Analytics Recipe

   CRM Analytics recipes can take a while to complete. Use these steps to monitor the status of your DailyAggregation recipe.

2. Run the DailyAggregation CRM Analytics Recipe

   To create a reusable dataset, schedule your DailyAggregation CRM Analytics recipe to run on a regular basis. We recommend daily at midnight.

See Also

Previous topic: Create Your App Analytics Dataset