Excel Spreadsheet Automation with the QUERY Formula



Pull data, automate spreadsheets, and more with the QUERY formula.

The CData Excel Add-In for PostgreSQL provides formulas that can edit, save, and delete PostgreSQL data. The following three steps show how you can automate the following task: Search PostgreSQL data for a user-specified value and then organize the results into an Excel spreadsheet.

The syntax of the CDATAQUERY formula is the following: =CDATAQUERY(Query, [Connection], [Parameters], [ResultLocation]);

This formula requires three inputs:

  • Query: The declaration of the PostgreSQL data records you want to retrieve or the modifications to be made, written in standard SQL.
  • Connection: Either the connection name, such as PostgreSQLConnection1, or a connection string. The connection string consists of the required properties for connecting to PostgreSQL data, separated by semicolons.

    To connect to PostgreSQL, set the Server, Port (the default port is 5432), and Database connection properties and set the User and Password you wish to use to authenticate to the server. If the Database property is not specified, the data provider connects to the user's default database.

  • ResultLocation: The cell that the output of results should start from.

Pass Spreadsheet Cells as Inputs to the Query

The procedure below results in a spreadsheet that organizes all the formula inputs in the first column.

  1. Define cells for the formula inputs. In addition to the connection inputs, add another input to define a criterion for a filter to be used to search PostgreSQL data, such as ShipCountry.
  2. In another cell, write the formula, referencing the cell values from the user input cells defined above. Single quotes are used to enclose values such as addresses that may contain spaces.
  3. =CDATAQUERY("SELECT * FROM Orders WHERE ShipCountry = '"&B6&"'","User="&B1&";Password="&B2&";Database="&B3&";Server="&B4&";Port="&B5&";Provider=PostgreSQL",B7)
  4. Change the filter to change the data.

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Use Excel to read, write, and update PostgreSQL data. Perfect for mass imports / exports / updates, data cleansing & de-duplication, Excel based data analysis, and more!