Inspiration
In our training program for our job, we were encouraged to explore the world of data analysis and found this hackathon as the perfect opportunity to grow our skillsets with new and unfamiliar technology to build a solution.
What it does
The chatbot provides a user interface that allows users to find data anomalies with ease.
How we built it
We utilized Microsoft fabric to clean the data using a notebook and Data lake to import the sample sales data we pulled from Kaggle. Afterwards we utilized python API calls to leverage Azure OpenAI for anomaly detection.
Challenges we ran into
Integration was definitely the more difficult task when participating in this hackathon due to the lack of resources at our disposal with Azure resources and our local environments.
Accomplishments that we're proud of
The simplicity of the user interface and the various ways in which the chatbot is able to descriptively present its findings in a conversational manner. The output is far more readable with structure comparable to an iPhone messaging system.
What we learned
Making API calls and building a chatbot forum.
What's next for Cloud
Ideally, we would like to allow any database to be able to function with our architecture instead of importing a static database.
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