Tablizer

Convert JSON to DAX Online

Paste a JSON table below, edit it if you need to, and get DAX back. The conversion runs in your browser, so nothing is uploaded, there is no size limit and there is no signup.

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The output will appear here once there is a table to convert.

What JSON is

JSON is a text format for nested data: objects with named keys, arrays, strings, numbers, booleans and null. It has no date type and no comments.

Every web API, most configuration files and anything that talks to JavaScript.

What DAX is

A DAX DATATABLE expression that defines a table inline in a Power BI model.

Power BI report authors.

What changes when you convert JSON to DAX

Four shapes all read correctly: an array of objects, an array of arrays with a header row, an object of column arrays, and an object keyed by row id. A single wrapper key holding the array, which is how most APIs reply, is unwrapped automatically. Nested objects are flattened one level into dotted keys; anything deeper is kept as JSON text in the cell, because a table cannot hold a tree.

All columns are declared as STRING. Change the type declarations by hand if you need numeric columns.

What carries over from JSON to DAX

JSON records 3 things about a table that DAX has no way to hold.

An empty cell and a missing one are the same thing in DAX, so a null and an empty string in the JSON both come out blank and can no longer be told apart.

JSON can hold a value that is itself a list or an object. DAX has only flat cells, so nested values are flattened into one cell rather than being spread across columns.

A line break inside a cell ends the row in DAX, so line breaks are replaced rather than carried through.

DAX marks header cells differently from data cells, so the keys are lifted out and written once as a marked header row rather than repeated on every row.

Both formats record types, so numbers, booleans and nulls survive as themselves rather than as text.

The identifier 007 comes out of the DAX as 007. Reading it as a number would have made it 7, and an id that changes value is worse than one that stays text.

The role "Analyst, data" survives with its comma, in one cell rather than split across two. That is the first thing to check in any converted table, and the usual place a DAX file goes wrong.

The quotes around Jonah "Jo" Pryce are escaped with a backslash in the DAX.

A worked example

Three rows of staff data, with an identifier that has a leading zero, a value containing a comma, a value containing quotes and one blank cell. Those are the four places formats disagree, so they are the four places to look.

JSON in
[
  { "id": "007", "name": "Halima Yusuf", "role": "Analyst, data", "started": "2024-03-15", "hours": "38.5" },
  { "id": "012", "name": "Jonah \"Jo\" Pryce", "role": "Engineer", "started": "2025-11-02", "hours": "" },
  { "id": "104", "name": "Wei Chen", "role": "Manager", "started": "2023-06-30", "hours": "40" }
]
DAX out
staff =
DATATABLE(
    "id", STRING,
    "name", STRING,
    "role", STRING,
    "started", STRING,
    "hours", STRING
    {
    {"007", "Halima Yusuf", "Analyst, data", "2024-03-15", "38.5"},
    {"012", "Jonah \"Jo\" Pryce", "Engineer", "2025-11-02", ""},
    {"104", "Wei Chen", "Manager", "2023-06-30", "40"}
    }
)

Questions

How do I convert JSON to DAX?

Paste your JSON into the box above or drop the file onto it. Check the table in the grid, then copy or download the DAX from the output panel. It takes one step and the data never leaves your browser.

Why did my zip code lose its leading zero?

Type inference turned the text 07030 into the number 7030. Tablizer leaves inference off by default for exactly this reason, and refuses to convert any value starting with a zero followed by a digit even when it is on.

What happens to nested values?

DAX has no nested cell, so a list or object inside a JSON value is flattened into a single cell rather than expanded into extra columns. Split it before converting if the parts need to be separate.

One of my cells has a line break in it - what happens?

A line break would end the row in DAX, so it is replaced instead of carried through. The rest of the cell stays where it belongs.

Is there a limit on file size?

No. The work happens on your own machine, so the limit is your machine's memory rather than an upload cap. A file with tens of thousands of rows converts in a second or two.

Is my data uploaded anywhere?

No. The parsing and generating are done by JavaScript running on this page. You can watch the network tab while you convert and see that nothing is sent.

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