Rust Data Pipelines: From Files to Clean Databases and Web Dashboards

A practical two-hour session on building reliable data pipelines in Rust, starting from messy input files and ending with clean data that can be stored, queried, and visualized in a web application.

The session combines Rust, Polars, command-line data workflows, and SQLx to show how a developer can take CSV or Parquet files, validate and transform the data, handle errors clearly, persist clean records into a database, and prepare the results for charts, dashboards, or reporting screens.

Rust is used as the implementation context, but the main lesson stays focused on software engineering fundamentals: data contracts, repeatable workflows, visible progress, reliable error handling, database migrations, compile-time query checks, and operational clarity.

Audience: entry-level and intermediate developers who want a practical engineering session on turning raw files into clean, queryable, visualizable data.

Outcomes:

• Build a Rust command-line workflow that accepts input files and produces structured outputs
• Clean and validate CSV or Parquet data before storing it
• Use Polars for filtering, selecting, joining, grouping, and lazy execution
• Store clean records in a database with SQLx
• Use migrations and compile-time checks to make database access safer
• Prepare stored data for visualization in a web application

Format: two hours with a short framing walkthrough, a concrete end-to-end example, discussion of tradeoffs, and a closing checklist for practice.