Unleash the full potential of your data.
Data is the lifeblood of modern business, driving everything from customer insights to operational efficiency. Yet, despite all the shiny tools, tech, and talent, most companies are stumbling. They’ve built impressive systems, but when it comes to making data work, they’re failing. Badly. Let’s be clear: this
Working with Strings in Python - Python has a lot of useful features built into its data types, as we’ve seen with our record dictionaries, but strings (text values) can do a lot for us as well.
Removing Fields from a Record - There are two main ways to remove a field from a Record… Or three, if we count simply clearing out the value.
Writing to Records - There are a few different ways that we can modify an existing record, to add a new field and value, change the value on an existing field, or remove a field entirely.
Reading from Records - There are two main ways to access the individual values (or “fields”) of a Record: Indexing and the get() Method.
The Default Transform & Working with Records - Matterbeam allows you to write your own Transformation steps in Python: Functional units of code that will be run on individual records.
Did you know you can send data to Matterbeam over HTTP using our HTTP Collector? Matterbeam provides an always available HTTP endpoint where you can PUT data for immediate use. Simply provide the name of your dataset in the url and a record in the request body. You can get
This is a comprehensive guide on how to get set up using Matterbeam's Salesforce Collector to gather your CRM data. With Matterbeam, you can select specific Salesforce objects for collection, ensuring your data is instantly available for transformation and emission to various destinations. To discover how Matterbeam can
Does your organization struggle with data sprawl? Do you have valuable information scattered across a myriad of different silos, tools, and personal computers? Are you dealing with duplicates or inconsistently named datasets that complicate the data management process? Or perhaps, your dilemma is having numerous different datasets with the same
