ERP Data Dictionary Worksheet
Every ERP analyst has a private notebook of what each column really means. This worksheet turns that into a shared data dictionary you can export to Excel and keep current.
| Table | Column | Data type | Length | Key | Null rate % (%) | Fill rate % | Business meaning | Data owner | |
|---|---|---|---|---|---|---|---|---|---|
100% | |||||||||
98.5% | |||||||||
100% | |||||||||
95.8% | |||||||||
100% |
Table and column names in the example are illustrative. Replace them with names from your own ERP schema. Null rates can be measured with a COUNT of nulls divided by COUNT of rows per column.
Turn your dictionary into answers
Optional: see how a documented schema helps a private AI assistant answer ERP questions accurately.
Optional. The tool and every export work without this. No spam.
How to use the worksheet
Add one row per column you actually use. Do not try to document an entire ERP schema in a weekend, since thousands of columns are unused. Start with the tables behind your top reports. Record the real business meaning, not just the technical name, because many ERP columns are reused for something their original name does not suggest.
Measuring null and fill rate
Null rate is the share of rows where a column holds no value. Fill rate is the complement, 100 minus null rate. A column with a 4% null rate on a promise date means 4% of lines cannot be judged late, which affects any on-time delivery report. Profile each documented column with a simple query and enter the result here so quality is visible beside meaning.
- Null rate = null rows divided by total rows
- Also check empty strings and placeholder values such as 0 or 1900-01-01
- Re-measure quarterly or after major loads
Ownership
A dictionary without owners goes stale. Name a data owner per row, usually the function that creates or relies on the value, and ask them to confirm the meaning. Disagreement about what a column means is useful information, and is the starting point of a data governance conversation.
Common mistakes
Teams copy the technical schema from the database and call it a dictionary. That lists type and length but misses meaning, allowed values, source and quality. Another mistake is ignoring user defined fields, which often hold the most business critical data in customized ERPs.
Frequently Asked Questions
How many columns should I document first?
Start with 50 to 150 columns behind your most used reports and integrations. It is more useful to have a small accurate dictionary than a large stale one. Grow it as questions come in.
Where do I get data types and lengths?
From the database catalog, for example INFORMATION_SCHEMA.COLUMNS in SQL Server or the data dictionary views in Oracle. Export them and paste into the worksheet, then add meaning and owners by hand.
What is a good fill rate?
It depends on the column. Keys should be 100%. Optional descriptive fields may be much lower. What matters is that the rate matches the business rule, and that unexpected gaps are investigated.
Can this replace a data catalog tool?
For a small team, a shared spreadsheet is a good start. Larger organizations eventually want a catalog tool with lineage and workflow, but the content you collect here transfers directly.
A good dictionary also makes AI over your ERP far more accurate. If you want a governed assistant that understands your columns, we can help you build that on-premises.
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