From the course: Build with AI: LLM-Powered Data Analysis App with Python and Streamlit
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App design fundamentals
From the course: Build with AI: LLM-Powered Data Analysis App with Python and Streamlit
App design fundamentals
- [Instructor] It's important to think through the user experience and design decisions. Before we build anything, we need to understand who our users are and how they will interact with the app. Questions like, who will use our AI data assistant, what problems are they trying to solve, how technically comfortable are they, should drive every design decision that we make. If you're not familiar with Streamlit's capabilities, I highly recommend checking out their gallery at streamlit.io/gallery. You will see apps designed by other users from financial dashboards to scientific tools. This will give you inspiration for what's possible as we design our own interface. Starting with user research, I interviewed several non-technical professionals about their data challenge. Common themes emerged. They have data in spreadsheets. They need quick answers for meetings, and they don't know how to code in SQL. They feel intimidated by complex interfaces. The result of this research tells us our…
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