I'm currently using SQL and Python to fetch results from Oracle and Impala databases, which I then send over to Google Sheets. This is connected to Looker Studio for creating dashboards. While this setup works, I find it a bit clunky, especially when I want external users to be able to filter data on their own, like by Client ID. I'm on the lookout for alternatives that would allow me to publish tables and charts more directly while still enabling users to run parameterized queries securely. Should I consider options like Streamlit or FastAPI with JavaScript? I'd love to hear what others have found effective!
3 Answers
I built a backend API that serves data to the front end, pulling it from SQL or files. To allow users to filter and run complex SQL queries, I utilize DuckDB with WebAssembly and some JavaScript. This way, users can run queries right in their browsers without needing to sandbox queries on the server side. It's worked out really well for me!
It really depends on who your audience is. For example, in my Big Data projects, I often export tables to Parquet files. Researchers then load these into Python for their own analyses.
If your goal is to let users visualize datasets based on specified parameters, you might want to check out Metabase. It offers data sandboxing, which simplifies the process since you won't have to build the whole application from scratch. If you want to go the custom route, libraries like Flask or FastAPI can help, but make sure to include an authentication layer to manage access to sensitive data.
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