We offer multiple ways for you to interact with your data from Fortnox. Which one you choose depends on the tools you use and the depth of your skills.
Data models overview
Your Fortnox data is made available via Bigquery, Google’s data warehouse.
While connecting, you’ll see different folders (called “dataset”). These are explained below.
| Dataset | Description | Suggested tool |
|---|---|---|
| /fortnox_api | Direct reflection of the Fortnox API, field by field. Mainly used to write custom SQL queries. |
Goole Bigquery |
| /fortnox_flat | Staged and flattened (denormalized) table. | Goole Sheets Microsoft Excel |
| /fortnox_bi | Facts and dimension (normalized) tables to build a star schema. | Power BI |
| /fortnox_reports | Useful data models (sql queries) to save you time. | Any |
What about Google Looker Studio?
We’ve developed dedicated Fortnox data sources for Google Looker Studio.
/fortnox_api
Do you prefer to interact with data using SQL? Then this is the dataset for you. For futher details, we refer to our dedicated Fortnox API SQL documentation.
/fortnox_flat
Wanna get started quick and easy, with a more tabular BI tool (e.g. Google Sheets or Microsoft Excel), but still have all relevant data at your fingertips? Use our prepared data models.
- incominggoods
- invoice_rows (fakturarader)
- invoices (fakturor)
- purchaseorders (inköpsordrar)
- supplier_invoices (leverantörsfakturor)
- vouchers (bokföring)
Important: All prepared data models are subject for continuously improvement. If static result structure is critical for your use case, copy the query to your own environment or let us created a separate dataset for you.
/fortnox_bi
This dataset is mainly created with Microsoft Power BI in mind. It holds fact and dimension tables which are building blocks in a star schema, used in Power BI.
A star schema has a fact table in the center, containing the measure you seek to measure - e.g. sales orders, booking vouchers etc.
The fact table can then have relationships/connections to multiple dimensions tables, containing more in depth information about different attributes often used for categorising and filtering - e.g. employees, products etc.
At time of this writing, these are the available tables. But they are subject to continuous improvement.
Dimensions
- dim_accounts
- dim_articles
- dim_company
- dim_cost_centers
- dim_customers
- dim_financial_years
- dim_labels
- dim_pricelists
- dim_prices
- dim_projects
- dim_stockpoints
- dim_suppliers
- dim_voucher_series
Fact
- fact_budgets
- fact_contract_rows
- fact_incominggoods
- fact_invoice_rows
- fact_invoices
- fact_offers
- fact_order_rows
- fact_orders
- fact_purchaseorders
- fact_stockbalance
- fact_supplier_invoice_rows
- fact_supplier_invoices
- fact_vouchers
You can see the relationships between the tables in Power BI, after downloading Enhanza’s template following this guide.
