Day 3 of dashboard week and we were required to create a dataset using chat gpt and then create visualisations in Power BI.
Thought Process:
1. Conceptualizing a company based on the requirements
In this case, I thought of a dessert company.
2. Consulting ChatGPT for Data Fields
The first step is to ask ChatGPT to assist you in defining the data fields required for your dessert company dataset. In this case I gave chat gpt the requirements that we were given and selected those that I thought that were important.
3. Generating Python Script with Trends
Once I identified the necessary data fields, I instructed ChatGPT to create a Python script that incorporates trends.
4. Saving the Python Script
Copy the generated Python script and paste it into a text editor like Notepad. Give the script an appropriate name, such as "dessert_trends.py."
5. Running the Script
Before running the script, ensure that you have the necessary Python libraries installed. In this case, you may need libraries like Pandas. Open the command prompt, navigate to the script's directory, and execute the script.
6. Debugging and Error Handling
During the script's execution, it's common to encounter errors or unexpected behavior. I asked ChatGPT to troubleshoot the errors and rewrite a new python script.
7. Go to ChatGPT again and create more data at a different level of detail and repeat the process (if you need)
Unfortunately Chat GPT is not as advanced to create trends. Therefore, I would suggest to do the following:
Start by creating a basic table with the main columns(e.g. one row should represent 1 order for a particular category, in a particular date). Then you can ask ChatGPT to add more columns, specifying the values and which trends it should follow (e.g. add column named A, where X should represent 40% of sales, Y 10%,.....)
OR
Create different datasets and create relationships in the model with a common field