QuickFixes
Last updated
Last updated
What are QuickFixes?
Getting Started
Types of QuickFixes
QuickFixes are one-click buttons designed to enable complex transformations, including AI Value Mapping, which uses advanced Large Language Models (LLMs) to automatically map source data to its nearest semantic match in the destination schema, eliminating tedious manual alignment and enhancing productivity. Additionally, AI Auto Clean empowers users to perform complex tasks, like formatting phone numbers, using natural language commands, and making data cleanup fast and intuitive. QuickFixes also include scenarios to clean up common data types like Lookups, Date, Text, and Numeric values. Combine multiple QuickFixes to clean and resolve data errors with ease.
Step 1: Once you have mapped the input (source) column(s) to the output (destination) column, click on any cell in the output column to open the Data Cleanup panel on the left.
The left side panel toggles between column mapping and data .
Step 2: From here you will see a list of potential QuickFixes that you can use to transform your data for the selected output column.
Step 3: If you want to use one or multiple QuickFixes, click on each of the QuickFixes in the order you want them applied.
Note: If you are uploading a file to clean up (i.e. not using Osmos Pipelines) and you need to make edits to specific cells in the output column after applying QuickFixes, click on any cell in the output column and provide a single-cell edit.
Step 4: To remove a specific QuickFix, click on the applied QuickFixes in the right panel.
Step 5: Once you are done, go to the bottom of the left panel and click Save, then move the next output column in the panel. If you want to restart and choose a different Data Cleanup method for this column, click Start Over.
There are several QuickFixes that populate based on a destination field value. These QuickFixes include AI Value Mapping and AI AutoClean, both use natural language commands to streamline data transformations. Additional Quick Fixes include lookups, address handling, number, and date defaults. For all QuickFixes, you have a variety of methods to handle QuickFix errors.
AI Value Mapping allows you to map end-user data into categories with your organization’s internal representation (commonly known as enumerations “enums”). Leveraging advanced Large Language Models (LLMs), this QuickFix automatically maps source data to its nearest semantic match in the destination schema. This saves your data operations teams hours of manual work while dynamically adapting to evolving source data without requiring updates to formulas or webhooks.
There are several QuickFixes related to addresses. These include Extract City, Extract State, and Extract Address Line 1.
There are several QuickFixes related to numbers. These include strip non-numeric characters, drop decimal, round, and round down.
There are many ways to default date layouts via QuickFixes.
If a QuickFix “QF” error occurs, you have five different settings to handle these errors.
Do nothing - The QF error will continue to present itself as an error until it is resolved
Ignore error - Do not treat the QF error as an error but instead ignore it
Skip row - If a QF error exists, the row will be skipped
Fill cell with a custom value - If a QF error exists, it will be populated with the custom value entered in the text box
Original value - If a QF error exists, the original value will be populated to the destination field.
