BACKGROUND
For my outgoing data integration, I've configured export actions to not include the default list columns so that the csv doesn't contain columns which may be incompatible with BigQuery e.g. `G1 Market# - Display Name`. Instead in the export module, i've replaced these with a dedicated column which has a custom name and does contains an ITEM('List') formula.
The export action is configured not to include any Labels for the dimensions.
PROBLEM
I'm struggling to figure out how to perform schema validation to verify the source and destination schemas are compatible. When I get the export metadata, I can't identify the state of the 'Labels' options. If labels is empty, 'G1 Market#' won't be included in the output csv. If labels is populated, G1 Market#' will be included. Example response:
{
"meta" : {
"schema" : "https://google.anaplan.com/2/0/models/{model}/objects/exportMetadata"
},
"status" : {
"code" : 200,
"message" : "Success"
},
"exportMetadata" : {
"columnCount" : 5,
"dataTypes" : [ "ENTITY", "TIME_ENTITY", "ENTITY", "NUMBER", "NUMBER"],
"delimiter" : "\"",
"encoding" : "UTF-8",
"exportFormat" : "text/csv",
"headerNames" : [ "G1 Market#", "Period", "market", "data1", "data2"],
"listNames" : [ "", "", … "", "" ],
"rowCount" : 1,
"separator" : ","
}
}
The actual csv produced by the action contains the following columns:
Period,market,data1,data2
Is there a way to interpret the export metadata response to determine the actual csv output schema (including data types)? If not can the response be updated to include said data?
In the short term, is there an alternate approach to column aliasing?
How often is this impacting your users?
Every change to outgoing data integrations.
Who is this impacting? model builders, integration experts
What would your ideal solution be? How would it add value to your current experience?
Add necessary info to the export metadata response.
Please include any images to help illustrate your experience.
