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Query Chain using XML as Data Source
Overview
This guide shows how to use an XML file as a data source in a Query Chain. Data Trust parses the XML structure using a configured root element path and maps the elements to tabular columns for downstream transformation and output.
Prerequisites
- You are logged in to Data Trust with a Pro-User or Admin Pro-User role.
- An XML file connection profile has been configured.
Steps
Path: Data Trust › Query Studio › Query Chain using XML as Data Source
Navigate to the Query Studio module and select Query cahin navigation to open the Query Builder workspace. This is the starting point for creating, editing, and managing queries in Data Trust.
Drag the Query Chain_Xml Widget widget from the palette and drop it onto the Query Chain canvas. Once placed, click the widget to open its configuration popup and complete the required settings.
This step shows Query chain_read data from table pop up in the Query Chain using XML as Data Source workflow. Follow the on-screen prompts to complete this configuration step before proceeding to the next stage.
This step shows Querychain_read data from table_Toggle to local in the Query Chain using XML as Data Source workflow. Follow the on-screen prompts to complete this configuration step before proceeding to the next stage.
The Querychain_Read data from table_Choose required file configures a CSV file as the data source for the query. Select the file connection profile, browse to the file location, and map the delimiter and header settings before saving.
The Querychain_Read data from table_Choose required file_Actions buttons population configures a CSV file as the data source for the query. Select the file connection profile, browse to the file location, and map the delimiter and header settings before saving.
This step shows querychain_read data from table _added root element and data model in the Query Chain using XML as Data Source workflow. Follow the on-screen prompts to complete this configuration step before proceeding to the next stage.
The Preview Data button fetches a sample of records from the selected table or query result. Verify the column names and sample values before proceeding to confirm the data source is correctly configured.
Click Save to persist the query or configuration to the Query Explorer. A confirmation message appears once the save completes, and the query is available for reuse in Query Chains and scenarios.
The Filter transformation restricts the records passing through the Query Chain to only those matching the specified conditions. Define the filter expression using field dropdowns, operator selectors, and value inputs, then save the widget.
The Filter transformation restricts the records passing through the Query Chain to only those matching the specified conditions. Define the filter expression using field dropdowns, operator selectors, and value inputs, then save the widget.
Click Save to persist the query or configuration to the Query Explorer. A confirmation message appears once the save completes, and the query is available for reuse in Query Chains and scenarios.
Drag the Querychain_Ged Rd Output widget from the palette and drop it onto the Query Chain canvas. Once placed, click the widget to open its configuration popup and complete the required settings.
The RD Output widget captures the final result set from the Query Chain for use in downstream processes. Configure the output name and format, then save the widget to make the results accessible to other scenarios and reports.
Click Execute Now to run the query immediately and fetch the result set. The results appear in the Results tab, and the execution status is displayed in the progress indicator.
The RD Output widget captures the final result set from the Query Chain for use in downstream processes. Configure the output name and format, then save the widget to make the results accessible to other scenarios and reports.
The Count at RD output widget_Results displays the output data returned by the query or Query Chain execution. Review row counts, column values, and data quality before saving or using the output in downstream processes.