Transform data¶
In this tutorial we will look closer into the transformation phase of a Sesam synchronization.
The transformation phase is where we prepare the data to be sent out to a target. We will now use the data you worked with in the previous tutorial to improve the data quality in the HubSpot company data as well as build a payload structure.
Objectives:
After you complete this tutorial you will have learned the following:
How to use Data Transformation Language to create system specific payloads
How to use global properties to increase payload data quality
Prerequisites
Before starting on this tutorial we suggest you complete the Connect tutorial as we will use that data in this tutorial.
Populate a payload with high quality data¶
In order to create the transform pipe, please follow the steps below.
Navigate to Pipes
Click on New pipe
Paste and save the configuration below
Click Start to ensure your pipe runs
Click the Output tab to see the result
{
"_id": "company-hubspot-transform",
"type": "pipe",
"source": {
"type": "dataset",
"dataset": "global-organization"
},
"transform": {
"type": "dtl",
"rules": {
"default": [
["add", "id", "_S.hubspot-company:id"],
["add", "payload",
["dict", "properties",
["apply", "create-properties", "_S."]
]
]
],
"create-properties": [
["add", "address", "_S.global-organization:address"],
["add", "city", "_S.global-organization:city"],
["add", "name", "_S.global-organization:name"],
["add", "about_us", "_S.global-organization:organization-number"],
["add", "zip", "_S.global-organization:zipcode"]
]
}
}
}
Notice that in this case we only use the properties we created in the connect phase. We could however have used any properties available to us in Sesam, as long as they are accepted by the HubSpot API.
HubSpot has specific requirements for the incoming data structure to their API, which is why we have added the payload and properties structures to the data.