JSON number precision becomes a problem when a file contains digits that its reader cannot represent exactly. The text can be valid JSON while a JavaScript application rounds a numeric value during parsing. If the value is an identifier, that change can point to the wrong record.
The important distinction is between the characters in the source and the numeric value the program stores after reading them.
Know the reader's numeric model
JavaScript's ordinary Number type has a maximum safe integer of 9007199254740991. MDN's MAX_SAFE_INTEGER reference explains the exact-integer boundary. Above the safe range, not every consecutive integer has a distinct exact representation.
As a sample native JavaScript example, parsing {"id":9007199254740993} with JSON.parse produces an ordinary numeric ID represented as 9007199254740992. The source digits and the represented value disagree. This example concerns that parser and number type; it does not describe every JSON implementation.
Once the original digits have been lost, making the parsed output look tidy does not recover them. The source must remain available to investigate the discrepancy.
Identifiers and quantities need different decisions
If id is an identifier rather than a quantity, a JSON string can preserve its characters: {"id":"9007199254740993"}. That is appropriate only when the receiving contract expects or permits a string. Do not change a live API field's type without checking its requirements.
For a true large integer quantity, the application needs a suitable numeric representation and parsing strategy. JavaScript BigInt can represent integers beyond the ordinary safe range, but ordinary JSON.parse does not automatically convert such literals into BigInt. Serialization and interoperability also need deliberate handling.
For decimal quantities, exactness brings a separate set of requirements. Avoid assuming that staying below the integer limit makes every decimal calculation exact. Use the representation and calculation method required by the application.
Inspect the source before transforming it
JSON Formatter can help review supported JSON, but formatting should not be treated as a precision-preservation guarantee for arbitrary large numbers. Read the tool's limitations and compare important identifiers with the original text.
CSV to JSON Converter can help preserve supported tabular values according to its options. Decide which columns are identifiers before conversion. A column of digits does not necessarily belong in numeric JSON values.
Prepare a small synthetic sample containing an ordinary ID, a leading-zero ID and a value beyond the relevant reader's safe range. Run it through the authorized conversion and receiving workflow. Compare the exact source characters with the final stored and exported values, rather than checking only whether the import reports success.
For a data handoff, document both the field type and the expected reader behavior. A short note that IDs are strings can prevent a downstream application from inferring numbers and silently changing them. The parser's successful completion is only one check; preservation of the intended identity is the one that matters here.