How to Clean and Transform Your Hubspot Data

In this tutorial, you will learn how to clean and transform your customer data in Hubspot with Mantium's platform. By the end of this guide, you will be able to connect your Hubspot account to Mantium, apply a few transforms such as Coalesce columns, and Combine columns to restructure your data in Hubspot.

Video

We understand that sometimes it's easier to learn by watching rather than reading. If you prefer a more visual explanation, feel free to check out our accompanying video tutorial below. If you prefer reading or are unable to watch the video, please continue with the text documentation.

Prerequisites

API Keys for OpenAI.
Access to a Hubspot account with proper permissions.

Connect Your Hubspot Account to Mantium

The first step is to connect your Hubspot account to Mantium. Follow the steps in this detailed guide, if you haven't set up your Hubspot Data Source connector

After completing the steps above, follow the steps below to create datasets from your imported data.

Click on the Create Custom Datasets button in the Data Source section.
Alternatively, you can create datasets by navigating to the Datasets section on the left pane.
Provide a Dataset name, and select where the data comes from (Hubspot Data Connector).
Click on Save to save your configuration, and wait for the job to complete.

Now you have your Hubspot data in Mantium, and you can perform transformations on the datasets.
Here is an example of the Hubspot dataset.

Apply Transforms

Coalesce Columns

In this example, we will coalesce the mobilephone column with the phone column, so that any instance of None in both columns is filled with the corresponding mobilephone number. This example is useful to fix any missing data.

Click on Transforms in the Datasets section.
Click on Add Transform and select Coalesce Columns from the dropdown menu.
In the Source Columns field, enter mobilephone and phone in the order they should be checked.
In the Destination Column field, enter the name of the new column that will hold the coalesced data.
Click on Save and Run Transforms to apply the transformation.

Your phone column should now be updated such that any instance of None is replaced with the corresponding phone number, if available.

Combine Columns

In this example, we will create a new column - Full Name that combines First Name, and Last Name using the string pattern.

Click on Transforms in the Datasets section.
Click on Add Transform and select Combine Columns from the dropdown menu.
In the Destination Column field, enter Full_Name to create a new column that will hold the combined data.
In the String Template field, enter First_Name: $column_First Name, Last_Name: $column_Last Name to define the pattern for combining the First Name and Last Name columns.
Click on Save to save your configuration, and then click on Run to apply the transformation.

Your dataset should now include a Full Name column that combines the First Name and Last Name for each record.