For large datasets in Alteryx, optimization usually comes down to reducing data movement and pushing work to the right place.

• Filter early, select only needed columns to reduce volume upfront

• Use In-DB tools to push processing to the database instead of pulling everything into Alteryx

• Replace heavy joins with indexed joins or pre-aggregations where possible

• Use summarize and sample tools to limit unnecessary processing

• Cache intermediate outputs with .yxdb files to avoid recomputation

• Avoid large data in Browse tools and unnecessary UI rendering

• Enable parallel processing where applicable

Most performance gains come from designing workflows that minimize data load and avoid redundant operations, not just tool-level tweaks.