9 Building and deploying data apps

 

This chapter covers

  • Building an interactive web application with Streamlit
  • Deploying Streamlit applications with Streamlit Community Cloud
  • Rendering interactive charts with Plot.ly
  • Creating a dashboard for Business Intelligence (BI) with Apache Superset
  • Creating charts from a custom SQL query with Apache Superset

In the last section of the previous chapter, we learned how to build a pipeline that ingested data into a local DuckDB database, as well as one running on MotherDuck. While many data analysts will be happy to interact with the data in DuckDB with SQL queries, other users will prefer to have an interface that doesn’t require them to write code. To provide value for those users we want to create applications that retrieve the information from DuckDB—either via SQL queries or any of the other means we learned so far, like the relational Python API—and present it in an accessible fashion and in such a way that it conveys its meaning.

9.1 Building a custom data app with Streamlit

9.1.1 What is Streamlit?

9.1.2 Building our app

9.1.3 Using Streamlit components

9.1.4 Visualizing data using plot.ly

9.1.5 Deploying our app on the Community Cloud

9.2 Building a BI dashboard with Apache Superset

9.2.1 What is Apache Superset?

9.2.2 Superset’s workflow

9.2.3 Creating our first dashboard

9.2.4 Creating a dataset from a SQL query

9.2.5 Exporting and importing dashboards

9.3 Summary