CSV column mapping

Map CSV columns once and reuse the mapping on every new file

If source and target CSV files use different column names, orders, or code systems, save the mapping from source fields to output fields and reuse it. If you already have the desired result CSV, BOMU can compare the two files and build the mapping rules automatically.

File data is processed in your browser. BOMU saves reusable transformation rules, not the contents of your source file.

Recurring workflow problem

Common CSV column-mapping problems

Use this when the same data has to fit different CSV structures for another system, client, vendor, or internal team.

1

Rename source fields such as cust_id and full_name to CustomerID and CustomerName

2

Reorder columns into the exact field sequence required by the destination CSV

3

Map source codes such as A01 and H01 to destination values such as ACTIVE and HOLD

Manual Before → BOMU After

Example: source CSV → destination CSV mapping

Manual Before Source
cust_id full_name phone_raw status_code
C001 Park Min 010 1234 5678 A01
C002 Kim Hana 010-2222-3333 H01
BOMU After Transformed result
CustomerID CustomerName Phone Status
C001 Park Min 01012345678 ACTIVE
C002 Kim Hana 01022223333 HOLD
Rule

Rules to configure in BOMU

  1. 1 Rename cust_id to CustomerID and full_name to CustomerName
  2. 2 Reorder fields to match the destination CSV structure
  3. 3 Remove spaces and special characters from phone_raw
  4. 4 Map A01 to ACTIVE and H01 to HOLD
  5. 5 Exclude source fields that are not needed in the destination file

A good fit for these recurring tasks

Client or vendor files that use different CSV column structures
CSV exports from ERP, CRM, accounting, or operations systems that need another layout
File exchanges where field names and code systems differ
Daily or weekly operations that repeat the same CSV mapping

Frequently asked questions

Can I use BOMU only to reorder CSV columns?

Yes. Keep the fields you need and place them in the exact output order required by the destination CSV.

Can I rename columns and map values in the same transformation?

Yes. Output header names, field ordering, status or code mapping, and format cleanup can be part of the same saved rule.

Can the output CSV have a different number of columns than the source?

Yes. You can exclude source columns and add fixed-value columns, so the output structure does not have to match the source one-to-one.