Data Cleaning Plan — AI workflow for Malaysian SMEs
Data Cleaning Plan turns messy dataset into cleaning steps. AI writes the first draft. You check it before it goes out.
Ready-to-use prompts for Data Cleaning Plan
Create prompt
Create prompt
Create a first-pass deliverable
Setup · same in all four
You are helping a small or medium Malaysian business in [industry]. Write in plain English. Use short sentences. If customers will read it in Bahasa Malaysia, add a natural BM version. Do not invent numbers, prices, laws or customer details. If something needs a human to check, say so.
Replace [industry] with yours — “F&B”, “construction”, “retail”.
The task
The task is data cleaning plan. Input: messy dataset. Output I expect: cleaning steps. Make it work for SMEs with spreadsheet data but limited analyst capacity. Short sections only. Wrap up with one next action and a version ready to paste into the workflow.
Replace “messy dataset” with your real data.
Analyse prompt
Analyse prompt
Analyse the input and identify the highest-impact insights
Setup · same in all four
You are helping a small or medium Malaysian business in [industry]. Write in plain English. Use short sentences. If customers will read it in Bahasa Malaysia, add a natural BM version. Do not invent numbers, prices, laws or customer details. If something needs a human to check, say so.
Replace [industry] with yours — “F&B”, “construction”, “retail”.
The task
Study the messy dataset I provide and analyse the data cleaning plan picture. Surface the top five insights, with numbers where the data supports them. Spell out the business impact. Deliver cleaning steps. End on the three highest-impact actions for analysis prep time.
Replace “messy dataset” with your real data.
Optimise prompt
Optimise prompt
Improve an existing version for better business results
Setup · same in all four
You are helping a small or medium Malaysian business in [industry]. Write in plain English. Use short sentences. If customers will read it in Bahasa Malaysia, add a natural BM version. Do not invent numbers, prices, laws or customer details. If something needs a human to check, say so.
Replace [industry] with yours — “F&B”, “construction”, “retail”.
The task
The task: make my data cleaning plan better. You get messy dataset and the version running today. Spot what is weak, what is unnecessary, and what is unclear. Rebuild it into a stronger cleaning steps. For every change, state the issue, the fix, and the expected impact on analysis prep time.
Replace “messy dataset” with your real data.
Automate prompt
Automate prompt
Turn the task into a repeatable AI-assisted workflow
Setup · same in all four
You are helping a small or medium Malaysian business in [industry]. Write in plain English. Use short sentences. If customers will read it in Bahasa Malaysia, add a natural BM version. Do not invent numbers, prices, laws or customer details. If something needs a human to check, say so.
Replace [industry] with yours — “F&B”, “construction”, “retail”.
The task
Design an AI-assisted automation around data cleaning plan. Starting point: messy dataset. End result: cleaning steps. Connected systems: Spreadsheets, BI, CRM, accounting, POS. I need the trigger, field list, AI instruction, decision rules, human approval points, failure handling, stored records and a analysis prep time tracking method. Keep maintenance light.
Replace “messy dataset” and the listed systems with what you actually run.
New here? How the four prompts work together
They are one sequence, not four options. Run them in order on the same piece of work, feeding each answer into the next.
Create
Paste your real data. You get a first draft. Most people never need to go further than this.
Analyse
Paste that draft back in. It tells you what is weak, missing or wrong before a customer sees it.
Optimise
Paste the draft again with what Analyse found. You get a stronger version.
Automate
Only once the output has been good five times running. This is the one people reach for too early.
Nothing forces you through all four. A good Create draft that you edit yourself is a finished job. The longer version.
Specification
- You give it
- Messy dataset
- You get back
- Cleaning steps
- Moves
- Analysis prep time
- Run it
- Weekly/Monthly
- Priority
- P4
- Works with
- Spreadsheets, BI, CRM, accounting, POS
- Tool guides
- Excel & Google Sheets, Accounting software, POS systems
Is this for you?
- Pick it for
- SMEs with spreadsheet data but limited analyst capacity. No setup needed. If you can copy and paste, you can run it.
- What you get
- Drafted in minutes, not built from scratch. It aims at productivity. Watch one number: analysis prep time.
- Reach for it when
- Most SMEs run it weekly, reviewed monthly. If you are doing it by hand more often, automate it first.
How to run it
- 01Collect the input: messy dataset.
- 02Copy the Create prompt and paste it into ChatGPT, Claude or Gemini.
- 03Replace “messy dataset” in the prompt with your real data, then run it.
- 04Read the output against what you already know and correct anything the model guessed at.
- 05Track analysis prep time. Only wire up the Automate prompt after five useful runs in a row.
The tools you will need
The prompts run in any chat assistant — ChatGPT, Claude or Gemini. These are what you need around them to get the input in and the output somewhere useful.
- Spreadsheets
- BI
- accounting
- AutoCountMalaysian, widely used for SST and e-Invoice.
- QuickBooks
- Xero
Check the rules yourself
This workflow touches rules set by someone else. Check the current requirements yourself before you act on the output.
- JPDP
- Pasting customer or staff records into an AI tool is a transfer of personal data. Consent, notice, retention and cross-border rules still apply when the tool is not yours.
Links go to each authority’s own site. See all Malaysian authorities.
Data & privacy
If you paste customer or staff details into an AI tool, your business stays responsible for them under the PDPA. Replace names and numbers with initials or references first.
Using customer data with AI tools in Malaysia covers what to check with any provider before you paste.
For this website, it works differently.
Nothing you type here is sent to us or to an AI model. The prompts are static content, and the copy button works directly inside your browser.
Related workflows
- Cash Flow Forecast Sheet StructureTurns your inflows and outflows into a forecast sheet structure with formulas.
- Customer Database Cleaning and Dedupe PassTurns your customer list export into a cleaning and dedupe procedure.
- Data Entry Form Design to Reduce ErrorsTurns your entry process and error types into a form design with validation rules.
- Debtor Ageing Report SetupTurns your invoice records into an ageing report setup with buckets.
All data analysis & reporting workflows: Data Analysis & Reporting
Maintained by Naven Pillai