hyperpbi

Retail Sales Operations

Combines the warm Productly visual language with portable semantic charts and a practical order work queue.

Files

• specification.json — strict HyperPBI dashboard schema 2.0.
• runtime.json — Runtime Configuration protocol 1.0.
• data.csv — deterministic synthetic source data.
• project.hyperpbi — complete offline Playground project with normalized rows and stable row keys.

Playground

Load this example from the Dashboard Examples gallery, or import project.hyperpbi from the Playground home page. The bundle is local-first and contains no credentials or remote data.

Power BI

1. Import the HyperPBI Core PBIVIZ package.
2. Import data.csv as one table.
3. Add every column to HyperPBI’s single Values field well. Keep the simple lowercase column names unchanged.
4. Paste runtime.json into Runtime Configuration.
5. Paste specification.json into Advanced JSON, validate, preview, and save.

All logical datasets use the portable powerbi source alias. The CSV has 19 fields, below the visual’s 50-field limit, and 89 rows, below the 30,000-row Power BI window.

Source fields

• recordtype
• recordid
• date
• month
• monthorder
• customer
• product
• category
• channel
• revenue
• expense
• tax
• orderstatus
• provider
• dueamount
• duedate
• balance
• dailyusers
• newproducts

Expected behavior

Monthly revenue, category share, recent orders, and upcoming payments all resolve from logical views over one sparse retail dataset.

Limitations

The balance card is illustrative and does not initiate payments or connect to a financial institution.

All names, organizations, accounts, assets, and events are synthetic and provided only for product demonstration.

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