When managing large datasets with complex full names, it is essential to accurately split these into individual components for better organization and analysis. Using the AI Column Node in Tabula.io, you can efficiently extract first or second names from a full name column, regardless of the complexity of the naming conventions.
Creating separate columns for first and last names for more detailed employee records.
Generating personalized emails by extracting the appropriate names from full names.
Customer Relationship Management (CRM)
Segmenting customer data for personalized marketing campaigns with accurate name components.
Streamlining data entry processes by automatically parsing names into individual columns.
Event Management
Preparing name tags and badges by correctly splitting full names into individual components.
Managing guest lists more efficiently with detailed name columns.
Step-by-step instruction
Step 1. Set Input Dataset
Consider a dataset containing full names that need to be split into first and last names, including cases where the last name consists of multiple words or names are listed in various orders. Here is a sample dataset before parsing:
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Step 2. Define the AI Prompt
The most crucial aspect of leveraging AI effectively is crafting a precise and relevant prompt. A well-defined prompt ensures the AI understands the task clearly, leading to accurate and useful outputs. This involves being specific about the desired outcome, providing necessary context, and avoiding ambiguity.
Prompt Example
Extract the first name from the @Full_Name column. The first name can consist of more than 1 word, like Anna Maria.
Why This Prompt Is Good
Clearly states the task (extraction) and the target column (@Full_Name).
Provides flexibility to handle various name formats and complexities.
Give an example
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Step 3. Configure the Flow Designer
Add the input dataset to the flow designer.
Select the AI Column node from the tools panel and enter the prompt.
Start with a row-by-row execution to fine-tune your prompt.
Correct your prompt, regenerate any single row, or remove all previous results.
Once you satisfied with the prompt, apply the AI Column Node to all rows (it will be applied only for empty cells).
For very large datasets that are bigger than 10,000 rows, run the flow for runtime processing over the whole dataset. Be aware that it can be costly for a large amount of data.
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Step 4. Get Final Result
Here is the dataset after using the AI Column Node to extract the first names:
