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ChatGPT and other LLM use cases for QlikSense
I’m interested in use cases to improve QlikSense apps using ChatGPT or any other LLM (Large Language Model).
In fact, I'm particularly attracted to the idea of using an in-house solution. Like a Open Source model with RAG and/or fine-tuning
Here you have a brief list of use cases:
- LLM assistant (for user data queries)
- Report Generation
- Sentiment Analysis
- Text Analytics: tagging and extracting meaningful insights from unstructured text data
- Predictive Analysis and Forecasting. I wouldn’t use a LLM for that when that is possible … I’d prefer to use a custom predictive model, or the Auto ML connector. However, it's still a relevant use case for enhancing a QlikSense app with AI.
- Augment your data model. https://www.youtube.com/watch?v=XCaaRenozb8 Because not all the users are used to the load scripts, I like the idea of using an extension to add the augmented data as inline data and reload.
Could you give me more uses cases? I’m also interested in what connectors, extensions or any QlikSense related technology would you use for these use cases. Also, any advice or examples would be greatly appreciated
Thanks in advance

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What about using an LLM to help with coding in Qlik - expressions & data load, for devs. The generic ones like Claude tend to produce invalid syntax and aren't that useful, it's like they don't really understand Qlik at all and have it muddled with other languages.
