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Data Integration Template:

Analyze your salesforce opportunity data with account and opportunity owner data.

Clean, structure and combine data from Salesforce objects to prepare opportunity analysis report

Salesforce opportunity performance analysis Flow The flow view of this template

Transformations:
Datedif, today, rename, if-else condition, change type, join, convert text to propercase

This template shows how to perform opportunity analysis combining data from salesforce objects like Account, Opportunity, User and Userrole data from a typical salesforce database.
The flow comes with detailed annotation of each dataset. Once you understand the recipe logic, you can customize this flow to jumpstart your own development or share it with others in your workspace.
The flow comprises of standard datasets like Opportunity, Account, User and Userrole objects that exist in salesforce. The initial recipes rename columns by prefix to help distinguish similar column name. This data is combined using left joins to enhance the opportunity data with account owner, user role and user data like city, state and manager id.
The final recipe creates columns that help understand the number of opportunities and amount created and closed in the current month and current quarter. It also provides actionable data on how many days it took to close an opportunity and how many days an opportunity is open till today.

This template is a pre-packaged, customisable and modular flow that leverage industry standard practices to report and analyze salesforce data.

The input datasets are dummy datasets that need to be replaced by your salesforce data. You can utilize this document to create your connection to salesforce.

The flow canvas also has detailed instructions of how to replace the dummy datasets(csv) with a SQL data from your salesforce datasource. You don’t have to create the SQL from scratch but simply copy the SQL corresponding to each dataset from the flow note and paste the SQL in “Create dataset with SQL” from the import page.

Once you have replaced the input datasets, follow the instructions to create output and run job.

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