Excel, CSV or Parquet
Your team picks a file, a sheet or a range of cells, and imports it. There is no connector to build.
Bring Your Own Data
Budgets, targets, price lists and mapping tables often live outside any database. Import them from Excel, CSV or Parquet, and they get the same approval, masks and history as everything else in the lakehouse.
In short
A report often needs a figure that nobody keeps in a database. Once the file is in the lakehouse, it sits next to the rest of your data, under the same rules.
Your team picks a file, a sheet or a range of cells, and imports it. There is no connector to build.
SchemaVortex reads the file and proposes a type for every column. Nothing is saved until someone checks them.
An imported table waits for a Data Warden's approval, then gets the same masks as any other table.
When the file changes, it is imported again into the same table. A versioned Vault table keeps what the earlier files said, as far back as your history reaches.
How it works
The import wizard reads the file, proposes a table, and hands it to the same pipeline your databases use.
| Column | Type |
|---|---|
Region | nvarchar(40) |
Month | date |
Target | decimal(18,2) |
Notes | left out |
The uploaded file itself is not kept once its rows are in the lakehouse. Who imported which file, and when, stays on record.
Producer SDK
For a system without a built-in connector, a small .NET library pushes its data straight into the lakehouse, from an API, a queue or an export of your own.
Send the whole table each time, add new rows, or update rows by their key.
The SDK runs in your own infrastructure and signs in with a key that belongs to a single source.
Data sent this way is approved, masked and kept in the Vault like every other source.
A short live demo: we import a file, approve it, and query it from Power BI.