Workflows
Documentation
Workflow
Key elements of the Workflow include
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Workflow Start Specifies the initial point of the workflow, such as File Paths, where the system reads or imports data from specific file locations, e.g., ecfd7b3-d440-446b-9d3d-d4313e879799/ABC BANK Data.xlsx.
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Query Datasource Defines the Datasource ID and the associated SQL query. For example, the query retrieves data from multiple tables like loan details and customer dimensions. The system uses SQL commands to fetch data based on specified criteria, such as SELECT t1.loan_id, t2.customer_name and other related fields.
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Is Custom Activity Indicates whether a specific task within the workflow is customized. In this case, the activities are marked as true, which means custom logic or actions are applied.
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Input Columns Lists the columns used as input in the workflow, such as first_name and last_name for customer data.
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Concatenate Columns Defines the output column, such as Customer, by combining multiple columns (e.g., first and last name). This output column may be used in later steps of the workflow.
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Schedules Provides information about when the workflow should run, along with options for setting a time zone and specifying whether the workflow should not run on holidays.
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Webhooks Defines the URL and the external services that will be called during the workflow. For example, a webhook is configured to communicate with PVR Consultancy.
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Emailhooks Specifies email recipients who will be notified at certain stages of the workflow. In this case, the email address symmondsagency.acmebanking@infoveave.app will receive updates.
This workflow configuration ensures that all necessary steps are executed in sequence, from data extraction and transformation to final reporting or notification, enabling businesses to automate and streamline their processes effectively.
Documents
In the Documents section, users can upload relevant files that assist in creating a more accurate description of the workflows using AI. These documents provide context and enrich the AI’s understanding, helping it generate better descriptions. This is particularly useful for data that requires detailed, nuanced explanations.