From the course: Build with AI: Data Pipelines with Cursor, Neon, and Streamlit
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Build a Streamlit dashboard
From the course: Build with AI: Data Pipelines with Cursor, Neon, and Streamlit
Build a Streamlit dashboard
- [Instructor] We have built a powerful data pipeline that allows us to extract data on academic papers and store that data. But now the crucial question is how do we analyze this data? How do we extract insights from this data? And the ideal answer to this question is visualization. Visualization is key to allow people to work with data. So for now, we have our pipeline, and we can write SQL queries, we can export files, we can look at our table in Neon, but none of that is as powerful as having a dashboard where we can visualize our data. And this is where Streamlit comes into place. Streamlit is an open source solution to quickly and easily build beautiful dashboards in Python. And we're going to leverage Streamlit to visualize our data and build an interactive dashboard. Now, the first step would be to install the Streamlit Python library in our code base. But you might remember that we've already done this, when we…
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OpenAlex quick start: Analyze data for Python data pipelines6m 59s
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Data extraction layer: Get data from OpenAlex22m 40s
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Neon database setup: Cloud PostgreSQL for data pipeline projects9m 50s
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Design table schema and create a table in the database9m 50s
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Process and load your data12m 23s
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Data quality testing11m 21s
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Consolidate pipeline logic8m 38s
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Build a Streamlit dashboard7m 58s
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Deploy the Streamlit dashboard7m 28s
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