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Fixed-Width ↔ CSV
Convert between fixed-width text files and CSV. Editable column definitions with name, start, and length.
Fixed-Width ↔ CSV
Convert between fixed-width text files and CSV bidirectionally. Define column names, start positions, and lengths — then paste or upload data in either direction. The tool auto-detects column boundaries when you upload a file, and the column editor lets you add, remove, or reorder fields to match your record specification. Handles large files with proper padding and alignment in the fixed-width output. Ideal for IBM i report files, mainframe exports, and legacy banking formats. Runs entirely in your browser — your data never leaves your machine.
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What Are Fixed-Width Files?
Fixed-width (also called fixed-length or positional) files store data in columns defined by character position rather than delimiters. Each field occupies a specific range of characters in every row — for example, characters 1–10 might be an account number, 11–30 a name, and 31–40 a date. There are no commas, tabs, or quotes to worry about, but you need the record layout (field names, start positions, and lengths) to interpret the data. Text fields are padded with spaces; numeric fields may be zero-padded or right-justified.
Where Fixed-Width Files Are Still Used
Fixed-width formats remain common in banking (NACHA/ACH files, Positive Pay, BAI2), government reporting (census data, regulatory filings), mainframe and IBM i data extracts, insurance (ACORD), healthcare (older claim formats), and legacy ERP exports. Many of these formats predate CSV and were designed for systems where every byte mattered. IBM i spool files, print files, and database extracts often arrive as fixed-width text. The format is also used for high-volume data feeds where the predictable record length enables efficient sequential processing.
Automating Fixed-Width Data Processing
This tool handles one-off conversions between fixed-width and CSV. Once converted, you can use the Data Diff & Compare tool to compare two versions of the same dataset side by side, or run the output through the Data Profiler for instant column-level quality metrics before loading into a target system. For recurring data feeds — daily bank files, nightly ERP exports, or weekly regulatory submissions — I build automated pipelines that parse fixed-width records using configurable layouts, validate field types and ranges, convert to target formats, and deliver data to downstream systems on schedule. Learn about IBM i services, explore ETL development and integration services, or get in touch to discuss your data processing needs.
All tools run entirely in your browser. Your data never leaves your machine. Need help? Ask James.