Move a grown spreadsheet into a database

Prompt that plans moving a grown spreadsheet into a database, with clean-up and reconciliation. Paste it into an AI tool of your choice, which then plans the database migration.

Topic: Spreadsheets & data
Type: Prompt
Level: Intermediate
Time: about 12 min

Results depend on the tool, the model and what you enter.

Result preview

Example: written by our editors, not real AI output.

Tables: customers (id, name, town), orders (id, customer_id, date, status), line_items (id, order_id, item, quantity, price) Clean-up: - column "Date": 3 mixed formats → one format - 47 customers duplicated with different spellings - "Price" contains text like "approx. 50" → clarify Migration: test import, compare totals, cut-over on Monday, old spreadsheet read-only afterwards Open: Who may delete orders?

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SpreadsheetWhat is in the spreadsheet?

ProblemsWhat does not work today?

TargetWhere should it go?

Your prompt

Plan moving the following spreadsheet into a database.
Spreadsheet: [Spreadsheet]
Problems today: [Problems]
Target: [Target]
Approach: 1. Using the column names and a few sample rows, describe which things the spreadsheet contains, such as customers, orders and line items. 2. Propose tables with keys and relationships from that. 3. For each column, give the data type, whether it is required and the allowed values. 4. List the clean-up work: mixed formats, duplicates, merged cells, free text in number columns. 5. Plan the switch: test import, comparing totals, a cut-over date, the spreadsheet read-only afterwards. 6. List open questions for the people who maintain the spreadsheet.
Output: table design, column list, clean-up list and migration plan. Do not invent columns that were not mentioned.

Take particular care to clarify the things and their relationships first and lose no row during the move.

Before you answer, check: Are all instructions met? If key information is missing or a placeholder in square brackets is still in the text, ask instead of guessing. Mark assumptions as assumptions.

Plan moving the following spreadsheet into a database.
Spreadsheet: [Spreadsheet]
Problems today: [Problems]
Target: [Target]
Approach: 1. Using the column names and a few sample rows, describe which things the spreadsheet contains, such as customers, orders and line items. 2. Propose tables with keys and relationships from that. 3. For each column, give the data type, whether it is required and the allowed values. 4. List the clean-up work: mixed formats, duplicates, merged cells, free text in number columns. 5. Plan the switch: test import, comparing totals, a cut-over date, the spreadsheet read-only afterwards. 6. List open questions for the people who maintain the spreadsheet.
Output: table design, column list, clean-up list and migration plan. Do not invent columns that were not mentioned.

Take particular care to clarify the things and their relationships first and lose no row during the move.

Before you answer, check: Are all instructions met? If key information is missing or a placeholder in square brackets is still in the text, ask instead of guessing. Mark assumptions as assumptions.

This is an instruction for an AI, not the result itself.

Where this prompt works

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How to use it

Fill in the fields or tap a suggestion. Leave out names, addresses and other personal data.
Copy the finished prompt into an AI tool of your choice.
After the test import, compare the row count and the totals of important columns with the old spreadsheet. If anything differs, the import is not finished.

Why does this work?

Spreadsheets grow until one row describes several things at once. Clarifying the things and their relationships first gives you a database that prevents duplicates and can be maintained without formula chaos.

Tips

Enter only column names and a few anonymised sample rows, no real customer data.

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Move a grown spreadsheet into a database

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