Spreadsheet analyzer
Analyze data of a CSV data by SQL queries.
Last updated
Analyze data of a CSV data by SQL queries.
Last updated
Customers can leverage SQL queries to analyze data within CSV files, offering a powerful way to extract, manipulate, and interpret information. By importing CSV data into an SQL-compatible environment, users can perform complex queries to filter, sort, and aggregate data, enabling detailed analysis and insights. This functionality is particularly beneficial for users who need to handle large datasets or require advanced analytical capabilities beyond basic spreadsheet tools.
The Spreadsheet analyzer component has the identifier of tbl-analyzer-X, where X represents the instance number of the Spreadsheet analyzer component.
Here is a simple use case of the Spreadsheet analyzer component, where the Spreadsheet analyzer component is being used to count the number of items in a CSV file.
Parameter Name | Description |
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Options | Description |
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Data
The target file.
Action
The action to be performed on the table.
There is just 1 possiblity.
Query data from table
SQL Generate Method
Method used to generate the SQL query.
There are 2 possibilities.
Use AI
Manually enter SQL
Input
The content or data that will be used to interact with the table.
Enable caching
This option determines whether the results of the component are cached. This means that on the next run of the Flow, Diaflow will utilize the previous computed component output, as long as the inputs have not changed.
Caching time
Only applicable if the "Enable Caching" option has been enabled. This parameter controls how long Diaflow will wait before automatically clearing the cache.