ManualTrigger Automate

ManualTrigger Automate enables users to effortlessly save data from a Microsoft SQL table as a CSV file with just one click. This streamlined workflow integrates Sticky Note for guidance, allowing for easy data export and storage, enhancing productivity and simplifying file management.

7/8/2025
5 nodes
Simple
manualsimplesticky notemicrosoftsqlspreadsheetfilefilesstorage
Categories:
Manual TriggeredSimple WorkflowData Processing & Analysis
Integrations:
Sticky NoteMicrosoftSqlSpreadsheetFile

Target Audience

This workflow is ideal for:
- Data Analysts: Who need to extract data from Microsoft SQL databases and save it in CSV format for analysis.
- Business Intelligence Professionals: Looking to automate data retrieval processes to enhance reporting efficiency.
- Developers: Who want a simple way to trigger workflows manually and integrate different applications.
- Small Business Owners: Needing to manage data without extensive technical knowledge, allowing them to focus on core business activities.

Problem Solved

This workflow addresses the challenge of manually extracting data from a Microsoft SQL database and converting it into a CSV file. It streamlines the process, reducing the time and effort required to perform these tasks, thereby increasing productivity and minimizing errors in data handling.

Workflow Steps

  • Manual Trigger: The workflow starts when the user clicks on "Execute Workflow".
    2. Set Table Name: It sets the table name to SalesLT.ProductCategory, which specifies the data to be extracted.
    3. Load Data from Microsoft SQL: The workflow executes a SQL query to retrieve all data from the specified table, ensuring that the latest data is fetched.
    4. Save as CSV: Finally, the retrieved data is saved as a CSV file, with the filename dynamically generated based on the table name. This allows for easy access and sharing of the data.

    • Customization Guide

    Users can customize this workflow by:
    - Changing the Table Name: Modify the value in the TableName node to extract data from a different SQL table.
    - Adjusting SQL Query: Alter the SQL query in the LoadMSSQLData node to filter or aggregate data as needed.
    - File Format and Name: Change the file format in the SaveCSV node or customize the filename to better suit their needs.
    - Adding Additional Nodes: Integrate more nodes for emailing the file, uploading to cloud storage, or further processing the data.