Have you used an AI-enabled notebook to write data cleaning or analysis code from plain English?

Hex, Databricks, Colab and Jupyter AI write pandas or SQL code from a description of what you want, and you check the results step by step.

How to automate it

How to automate “clean and reshape messy data”

Here are 2 ways to spend less time on this, best first. Each comes with steps you can follow today and, for AI fixes, a prompt to copy.

60 min

typically, a few times a week

55%

of the time can be automated

Easy

to set up

Fix 1 of 2

AIBest fix

Clean and explore data in a notebook with AI built in

Hex, Databricks notebooks, Jupyter AI, Colab with Gemini and ChatGPT or Claude data analysis write the cleaning and reshaping code from plain-English instructions. You check the output.

Typically saves about 40% of the time10 min to set up

1Open the data in an AI-enabled notebook (Hex, Databricks, Colab, Jupyter AI), or upload a file to an approved assistant.
2Describe the cleaning you need using the prompt below.
3Read the generated code; check row counts before and after each step.
4Save it as a reusable notebook or move it upstream into the pipeline.

Prompt to copy

I have a dataset with these columns: [LIST COLUMNS AND TYPES]. Write [PANDAS / POLARS / SQL] code to: [e.g. standardize dates to ISO, trim and lowercase emails, remove exact duplicates, split full name into first and last, flag rows with missing customer IDs]. Print row counts before and after each step, and list any assumptions. Do not drop rows silently.

Tools: Hex Magic · Databricks Assistant · Jupyter AI · Google Colab with Gemini · ChatGPT or Claude data analysis

Fix 2 of 2

Process fix

Fix the data at the source instead of cleaning it every time

If you clean the same mess every week, the fix belongs upstream: a required field, a dropdown instead of free text, or a cleaning step in the pipeline.

Typically saves about 35% of the time2 h to set up

1List the cleaning steps you repeat most.
2For each, find where the bad data enters (a form, a CRM field, an import).
3Ask the system owner for validation, dropdowns or required fields.
4Move any cleaning that must stay into a shared pipeline model so nobody does it by hand.

Tools: Your CRM, ERP or form tool settings · dbt or your pipeline tool

Quick wins

Have you tried…

Have you used an AI-enabled notebook to write data cleaning or analysis code from plain English?: Hex, Databricks, Colab and Jupyter AI write pandas or SQL code from a description of what you want, and you check the results step by step.

Who does this task

Roles in our library that list this as one of their common tasks. Each guide covers the rest of that role’s week.

Data / BI analyst Data scientist

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