Date Formatting

Step 1. Set Input Dataset

Consider a dataset containing dates in various formats that need to be standardized to the format "YYYY-MM-DD". Here is a sample dataset before formatting:

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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

Convert the date in @Event_Date to the format YYYY-MM-DD.

Why This Prompt Is Good

• Clearly states the task (date conversion) and the target format (YYYY-MM-DD).
• Directs the AI to focus on the specific column (@Event_Date).
• Ensures uniformity in date formatting across the dataset.

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Step 3. Configure the Flow Designer

1. Add the input dataset to the flow designer.
2. Select the AI Column node from the tools panel and enter the prompt.
3. Start with a row-by-row execution to fine-tune your prompt.
4. Correct your prompt, regenerate any single row, or remove all previous results.
5. Once you satisfied with the prompt, apply the AI Column Node to all rows (it will be applied only for empty cells).
6. 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 standardize the dates: