What is Data Standardization?
Data standardization, told as a story about the student council unifying every class's own attendance format into one shared, school-wide standard.
Every class marks attendance a different way.At first, each class just wrote attendance however was convenient.
Adding up each class's attendance, the numbers don't match.Different formats mean the combined numbers can't be trusted.
Data standardization is a shared glossary, format, and code table the whole school uses.Same words, same format, same codes — then the whole school's numbers can be trusted and combined.
After standardizing, three classes' separately kept attendance can be added into one total.Standardizing doesn't change who attended — only the agreement on how to write it.
Even a standard has to keep being refined.Every new situation means refining the standard again.
Data standardization = getting many classes (systems) to use the same terms, format, and codes, so the numbers can be trusted and combined.
Data standardization aligns how multiple systems represent the same meaning — standard terminology, standard domain (format/range), standard codes, and naming conventions. Without it, linking or integrating data across organizations breaks down, because the same value gets interpreted differently, and statistics and data links fall apart. Standards are collected in a data dictionary that members can look up, and must keep being revised as new situations arise.
When grown-ups say it
- Data Standardization
- Getting the whole school to use the same words, format, and codes. Standardizing lets the combined numbers be trusted.
- Standard Terminology
- Calling the same meaning by the same name. Different names per class cause confusion.
- Standard Domain
- Fixing the format and range a value can take. Like agreeing dates are always YYYY-MM-DD.
- Code Standard
- Writing the same value with the same code. Unifies it to a numeric code, like 1 = present.
- Naming Convention
- A shared way of naming things. Code and variable names follow this rule too.
- Data Dictionary
- The list collecting the whole school's standard in one place. Kept where every member of the school can look it up.
- Data Quality
- How accurate and trustworthy data is — following the standard raises it. It echoes software's own standard for "good." → the standard for good software
- Open Data
- Publishing agency data for anyone to use — standardized data is easier to reuse. How open data gets linked is told through a warehouse in another field. → the warehouse that opens its door and links its tags