Updated Sep 28, 2026
Most data exports contain JSON files. JSON is the format services use to hand you structured records. Every chat, every transaction, every workout, every search. In a single machine-readable file. The first time you open one in a text editor it can feel opaque: dense, full of brackets, no obvious structure. But you do not need to be a programmer to read JSON. Three approaches work for almost every export you will encounter, and once you know them, opening any JSON file becomes a thirty-second job.
JSON stands for JavaScript Object Notation. It is a text format for storing structured data. The same idea as a spreadsheet, but designed for machines to read and write reliably. A JSON file is plain text: you can open it in any text editor and read it, though the structure takes a moment to get used to.
Most export files are JSON arrays of objects. One object per event (a chat, a transaction, a viewing). Each object has labelled fields, and the file as a whole is just a list of those objects wrapped in square brackets.
The fastest way to read a JSON file with no setup. Every modern browser can render JSON as a collapsible tree. Drag the file into a new browser tab and the browser does the formatting for you.
This works for files up to a few hundred megabytes. For very large files (over 500 MB) the browser will start to choke. See the large-files section below.
If the browser view feels clunky, online viewers give you a more polished interface with better navigation, search, and filtering. They run entirely in the browser, so your file never leaves your computer.
The most-used free viewer is jsonviewer.stack.hu. There is also codebeautify.org/jsonviewer and similar tools. Pick whichever you find visually cleanest. They all do the same thing.
Spreadsheets are the right tool when you want to actually work with the data. Filter, sort, count, make charts. Excel and Google Sheets can both import JSON, but the path is slightly different in each.
Excel's Power Query is the most powerful route and handles nested JSON better than the basic import. Google Sheets works well for moderately nested files but flattens nested arrays into separate columns.
For files too large for browsers or when you want to navigate quickly, a code-aware text editor is the right tool. VS Code, Sublime Text, Notepad++, and BBEdit all render JSON with collapsible sections, syntax highlighting, and fast search.
This is also the right tool when you want to make small edits. But be careful: editing an export changes your archive. Make a backup before saving.
For a quick look at a JSON file from a terminal, the right tool is `jq`. A small, free command-line JSON processor. It is available on macOS via Homebrew (brew install jq), on most Linux distributions via the package manager, and on Windows via chocolatey or scoop.
Once installed, `jq "." filename.json` pretty-prints the file. `jq ".[0]"` shows the first record. `jq ".[].fieldname"` extracts a single field across all records. It is fast on multi-gigabyte files where browsers stall.
Exports with years of history can produce JSON files of several gigabytes. At that size, browsers and spreadsheets will not work. They load the whole file into memory. The right tool changes.
Across the dozens of services you might export from, a few patterns come up over and over. Knowing them makes reading any JSON file faster.
Even with the right tools, a few traps catch people consistently.
A standard text editor like Notepad or TextEdit shows JSON as one giant line of text with no line breaks or indentation. JSON is structured, but the structure is hidden until something adds the line breaks and indentation. That is exactly what browsers, online viewers, VS Code, and jq do. They reformat the file so you can navigate it.
Yes. Excel's Power Query (Data > Get Data > From File > From JSON) is the most reliable path and handles nested JSON well. Google Sheets needs an add-on or a JSON-to-CSV conversion step. Once imported, the data behaves like any other spreadsheet. You can filter, sort, and chart it.
For one-off viewing: drag the file into a browser. For more navigation: jsonviewer.stack.hu. For working with the data: Excel Power Query. For very large files or command-line users: jq. Most people only need the first two.
Do not open it in a browser or Excel: they will crash. Use jq from a terminal, or a streaming JSON parser. If you only need to look at a slice, jq can extract a single field across all records without loading the whole file into memory.
No. The three approaches in this guide: browser, online viewer, spreadsheet. Cover 95% of what most people want. A programming language only becomes necessary when you want to automate analysis, combine multiple exports, or build something custom.
Most reputable online viewers run entirely in your browser. The file never uploads to a server. Check that the URL stays "file://" or that the viewer explicitly states the data stays local. If in doubt, use the browser drag-and-drop approach, which is guaranteed to be local.
The most common cause is a truncated or corrupted download. Re-download the export. Other causes: a text editor that introduced invalid characters while saving, or saving with a non-UTF-8 character encoding. If the file is genuinely too large for your editor, switch to jq or VS Code.
Yes. Excel Power Query can flatten JSON to a CSV. Online converters like convertcsv.com/json-to-csv do it in the browser. Most spreadsheet tools also let you "Save As" CSV after importing the JSON. Note that nested fields get flattened or dropped in CSV. JSON preserves structure that CSV cannot.