Notice: This user guide is based on the legacy connector.
We recommend using our new connectors instead, as they are easier to use and actively maintained. This legacy documentation may not be up to date.
We recommend using our new connectors instead, as they are easier to use and actively maintained. This legacy documentation may not be up to date.
Extracting values from records
If you want to extract the value of a specific field from the received objects, you can use the lookup operator ”[ ]”. Here’s how you do it:- Go to “Add Column” tab and click on “Custom Column”. A dialog box will appear, where you can enter a name and a formula for your new column.
- Enter a name for your new column, we’ll name it “category”.
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In the formula box, you can access the fields you want using the following expression
You can replace “category” with the field you want to access. If the field is not found, an error will be returned.
- Click OK. A new column will be added to your table, containing the values of the “category” field from the records in the “data” column.
Nested records
Expanding data column
Here is what you need to do if you want to expand the fields of the records in your “data” column into separate columns:- Click on the Expand icon in the column header of your “data” column. It looks like two arrows pointing in opposite directions.
- A dialog box will appear, showing you the field names of the records in your column. You can select which fields you want to expand or select all of them.
- Click OK. The “data” column will be replaced by new columns, each containing the values of one field from the records.
Expanding a record column may have some disadvantages:
- It can increase the size of your data model if you expand a column that contains many columns or rows, which will be the case for Speckle data in most cases. Received Records will have all the properties of the source object (a lot of field names) and this can affect the memory consumption and performance of your report if you expand all.
- It can miss some column names if you have different object types in your data. This is because Power BI will hard-code the column names that you select to expand, and if there is a new or different column name in the source, it will not be included in the expanded results.