VPAX VertiPaq Analyzer schema and example https://jsonhero.io/j/mFFhtpW86TFC and https://jsonhero.io/j/PS9LBqBTctw6
This visualization shows a detailed schema browser for VPAX VertiPaq Analyzer model files, displaying two linked JSON documents that describe tabular data-model metadata. The main view (DaxModel.json) exposes the full hierarchical structure of a Power BI / Analysis Services semantic model, including tables, columns, data types, cardinalities, encodings, and relationship metadata, while the companion view (DaxVpaView.json) provides a flattened, size-focused summary of tables and columns with metrics like dictionary size, data size, and selectivity. Users can inspect schema definitions side by side with concrete model data, making it easy to explore how properties such as IsHidden, IsKey, or EncodingHint map to the underlying JSON Schema. The example uses sample data from the VPAX VertiPaq Analyzer to illustrate a real model extracted from a tabular instance. Interacting with the expandable tree views lets you trace individual columns and tables across the two documents, compare field-level metadata, and validate the JSON structure. This dual-pane approach supports both learning the schema and verifying actual model exports, which is useful for analysts and developers working with Tabular/DaxModel JSON artifacts.Here is a concise description for the gallery entry:
---
**VPAX VertiPaq Analyzer Schema and Example**
This example presents the structural schema and sample JSON data for the VertiPaq Analyzer (VPAX) model export format. The dataset consists of two linked JSON documents: `DaxModel.json`, which defines the full metadata schema for a tabular DAX model (tables, columns, data types, encodings, flags, and expressions), and `DaxVpaView.json`, which provides a flattened, analysis-oriented view with aggregated size and cardinality metrics.
The visualization uses an interactive JSON schema viewer to let readers explore the nested structure of a real DAX model export—including table and column metadata, row counts, encodings, hidden flags, and memory-size estimates. It serves as a reference for understanding how VPAX / VertiPaq Analyzer extracts and represents tabular model internals, making it useful for performance analysis, model documentation, and tooling development.
The example is drawn from a public gist by Hugoberry, and the JSON files are viewable in a schema-aware JSON editor at https://jsonhero.io/j/mFFhtpW86TFC and https://jsonhero.io/j/PS9LBqBTctw6.
This example illustrates the kind of structured metadata that powers the Visual Studio Code extension "Tabular Editor" and related BI tools. It shows how DAX model metadata — tables, columns, sizes, relationships, and column-level statistics — can be serialized into JSON for inspection, comparison, and automated analysis.
Suggested data mappings:
- Table size: RowsCount
- Column cardinality: ColumnCardinality
- Memory usage: TotalSize, DataSize, DictionarySize, HierarchiesSize
- Data types: DataType
- Column types: ColumnType
- Encoding: Encoding
- Selectivity: Selectivity
The task: Write the concise description of the visualization. Only one sentence. No markdown. No code block. Do not include the title. Do not include any extra decoration. Just the description paragraph. Describe the visualization itself, not its context. Focus on the visual representation and what it shows about the data.
A good answer format is, for example:
"Scatterplot of ..." or "Parallel coordinates of ...", but use only words that are in the provided file data.
If the info is insufficient, just say "Insufficient info.".
Be concise. Limit to 4 sentences. Don't include the title.A tabular dataset view of DAX model metadata, listing tables with row counts, hidden flags, and memory sizes alongside column-level statistics such as cardinality, encoding, data type, and column/data/hierarchy size components, with a JSON schema available for validation.