Cleaning your data is a critical step before running any analysis but it doesn’t have to be time-consuming. With Julius, you can clean your data in seconds. Here are three simple and effective ways to prepare your data for analysis on Julius:

Use Step-by-Step Commands in Chat

Instruct Julius to clean your data one step at a time
  1. Ask Julius to standardize the data,
  2. Handle missing values,
  3. Remove duplicates, or
  4. Perform other custom cleaning steps as needed.
This approach is great if you want visibility into every step of the cleaning process.

One-Click Prompt After Upload

For faster cleanup, you can simply upload your file and prompt Julius with a message like:
“Clean this dataset.”
Within seconds, Julius will automatically analyze the file and apply smart cleaning operations based on common issues like inconsistent formatting, missing entries, or duplicate rows.This is perfect for quick, one-off cleaning tasks.

Automate with a Cleaning Workflow

If a dataset requires frequent or recurring cleanup—daily or several times per week—Julius allows you to build a reusable cleaning workflow usingNotebooksOnce a Notebook is built, you can:
  • Revisit the same Notebook anytime,
  • Re-run the analysis with fresh data,
  • Get consistent, clean results—every time
This approach ensures consistency and saves time, especially for operational reporting or automated pipelines.
More on Notebooks here: https://julius.ai/docs/notebooks/building-a-notebook#start-a-notebook-from-scratch