Transforming data: key concepts
In this lesson, we explore the core of what makes Parabola so powerful: its data transformation capabilities.
Pro tip: Start by cleaning your data
The best way to start your Flow is by ensuring your data is as clean as possible at the beginning. Think about doing things like:
- Removing unnecessary columns
- Removing duplicates
- Clearly naming your columns
- Filtering out unnecessary columns
- Formatting dates
Building challenge
This lesson doesn’t have a challenge – continue onto the next lesson to continue the course.
Introduction to Data Transformation in Parabola
In this video, we’ll provide a high-level overview of the different data transformation steps in Parabola.
Parabola is designed to speak your language—if you were to write out a step-by-step guide for a manual process, the steps in Parabola would closely mirror that process. The best Parabola flows often include:
- Clear documentation on each step (e.g., "Filter out rows first, then rename columns, then remove duplicates")
- Logical sequencing of transformations that reflect how you would manually process data in a spreadsheet
Common Data Transformation Steps
Parabola provides a wide range of steps to manipulate your data, including:
- Editing columns (renaming, reordering, or removing)
- Filtering rows based on specific conditions
- Removing duplicates
- Searching for familiar spreadsheet functions (e.g., "VLOOKUP" maps to the Combine Tables step, "SUMIF" can be replicated with aggregation steps)
Whatever you can do in a spreadsheet, there’s a way to accomplish it in Parabola using a combination of transformation steps.
Best Practices for Building Flows
To ensure a smooth workflow, follow these best practices:
- Start with clean data – Remove unnecessary columns, rename fields clearly, and eliminate duplicates before applying transformations.
- Perform complex transformations mid-flow – This includes combining datasets, aggregating values, and applying logic-based operations.
- Format your data at the end – Adjust dates, numbers, and column names to prepare your final output.
Next Steps
In the next few videos, we’ll cover some of the most common and powerful data transformation steps in Parabola, including:
- Applying if/else logic
- Duplicating datasets
- Combining datasets across multiple keys
Up next, we’ll start with one of the most frequently used steps in Parabola: the Edit Columns step. 🚀