Lakehouse · Analytics connector

The Fabric data catalog your whole team can trust.

The Dawiso Fabric connector turns your tenant into a searchable data catalog: every workspace, lakehouse, warehouse, semantic model and Power BI report, with native lineage.

Read the docs

Live connector Stable connector

Fabric

Dawiso

Metadata-only · your data never leaves the source

Type: SaaS analytics platform
Auth: Service principal (Entra ID)
Sync: Scheduled, incremental
Direction: Read-only · metadata

First things first

What is a data connector?

Metadata-only Read-only access Incremental sync Cross-system lineage

A data connector is the bridge between a tool in your stack and the catalog that gives you a unified view of it. Once a connector is configured, it reaches into the source system on a schedule, reads out the metadata - schemas, tables, dashboards, jobs, ownership, lineage - and represents it inside the catalog. Your actual rows and values stay where they are.

Connectors are the reason a data catalog can answer questions like "which Power BI dashboard depends on this Snowflake table?" or "who owns the orders topic in Kafka?" - automatically, without anyone keeping a spreadsheet up to date.

Three properties separate a good connector from a brittle one: it should be read-only and safe, it should be incremental so a full re-scan isn't required for every refresh, and it should resolve lineage across system boundaries, not just inside one tool.

About the platform

What is Microsoft Fabric?

Microsoft Fabric is the SaaS analytics platform built on OneLake. It unifies Data Factory, Data Engineering, Data Science, Data Warehouse, Real-Time Intelligence and Power BI in one tenant, so a single dataset can be served to ETL, ML and BI without copies. Microsoft positions it as the all-in-one analytics solution for organisations already on Azure and Microsoft 365.

The OneLake Catalog covers what's inside Fabric. What it doesn't cover is the Oracle source that feeds the lakehouse, the Snowflake share alongside Fabric, the Tableau dashboard on the other side of the org, and the data product the business owns end to end. That's where the Dawiso Fabric data catalog joins the picture: read-only, metadata-only, and cross-platform.

Architecture

How Dawiso connects to Fabric

A small read-only role on the Fabric side. The Dawiso scanner pulls metadata on a schedule. Everything ends up in your catalog, business-readable.

Source

Microsoft Fabric tenant

Workspaces & capacities
Lakehouses & warehouses
Semantic models & reports
Notebooks & pipelines

REST · JDBC

Dawiso scanner

Read-only metadata

Schema & object discovery
Dependency resolution
SQL flow parsing (optional)
Sampling on opt-in

Internal

Catalog

Dawiso platform

Searchable metadata
Lineage & ownership
Business glossary
Policy & classifications

Connection details

Protocol: Power BI Admin API + Fabric API
Authentication: Azure service principal · Entra ID security group · client secret
Lineage: Native lineage from Fabric admin APIs (datasets to reports, lakehouses to semantic models); object-level advanced lineage built from view and procedure definitions on enterprise plans

Setup

Connect Fabric in 4 steps

01

Register an Entra app

In Azure Portal, register a new application (e.g. Dawiso Integration). Copy the Application (client) ID and Directory (tenant) ID from the Overview page.
02

Generate a client secret

Under Certificates & secrets, create a new client secret with an expiration that matches your rotation policy. Copy the value immediately - Azure shows it only once.
03

Configure Fabric tenant

Create an Entra security group with the service principal. In Fabric Admin Portal, enable: service principals can call Fabric public APIs, read-only admin APIs, enhance responses with detailed metadata and DAX.
04

Grant workspace access

Add the security group to each workspace as Contributor (Viewer ingests basics; Contributor exposes view and procedure definitions for advanced lineage).

Capabilities

What you get with the Fabric connector

Workspace & lakehouse catalog

Every Fabric workspace, lakehouse, warehouse, semantic model and report is searchable, with column descriptions, owners and the notebooks behind them.
Native + object-level lineage

Lakehouse, warehouse, semantic model and Power BI links come from Fabric admin APIs. View and procedure definitions add object-level advanced lineage on enterprise plans.
DAX & M parsing

Enhanced admin API responses with DAX and mashup expressions feed the catalog with semantic-model measures, calculated columns and Power Query steps.
Tags & sensitivity in context

Tags and sensitivity labels set in Microsoft Fabric are read into Dawiso, so governance context stays visible alongside Databricks, Snowflake and BigQuery. Read-only, metadata-only.
PII classification

Classify a column once. Dawiso flags every Fabric column carrying email, IBAN or government IDs across all workspaces in scope.
Ownership & certification

Mark lakehouses, semantic models and reports as certified, deprecated or under review. The owner is visible directly in the catalog.

Business value

Why teams turn on the Fabric connector

-65%
Fewer 'which report?' pings

Business users find the certified semantic model in Dawiso instead of asking BI which of seven dashboards shows the real revenue number.
10x
Faster impact analysis

Before retiring a Fabric lakehouse table, see exactly which semantic models, Power BI reports and downstream warehouses depend on it.
Audit-ready
GDPR & DORA evidence

Sensitive columns are classified once and the policy follows them through lakehouses, semantic models and reports, with a full audit trail.

Ready to catalog your Fabric?

Set up the connector in an afternoon. See your first lineage graph the same day.

Read the docs

Frequently asked questions

Still curious? Talk to our team ->

Does Microsoft Fabric have a data catalog?

Fabric has the OneLake catalog for items inside Fabric, with Microsoft Purview for governance. Dawiso adds the cross-platform layer: it reads Fabric and OneLake metadata read-only and connects lakehouses, warehouses and reports to the rest of your stack with object-level lineage.

What is the difference between data catalog and data fabric?

A data fabric is an architecture for connecting data across systems; a data catalog is the inventory that makes it discoverable and governed. Dawiso is the catalog layer over Microsoft Fabric, with business glossary, lineage and ownership.

What is a data catalog used for?

A data catalog makes every Fabric item discoverable, documented and trustworthy. Dawiso turns Fabric metadata into one searchable catalog the whole business can use, with lineage across tools.

What permissions does Dawiso need in Fabric?

An Azure service principal in an Entra security group. In Fabric tenant settings: service principals can call Fabric public APIs, read-only admin APIs, enhance responses with detailed metadata, and enhance responses with DAX. Plus Contributor on each workspace for full ingestion.

What's the difference between Viewer and Contributor access?

Viewer access ingests schemas, tables and views, plus procedures and functions without SQL bodies. Contributor adds view and procedure definitions, which unlocks advanced object-level lineage. Dawiso recommends Contributor on every workspace that needs full coverage.

Does Dawiso copy our Fabric data?

No. Dawiso reads metadata from the Power BI Admin API and the Fabric API only. Row-level data stays inside OneLake. Open Preview links direct users to sample data inside Fabric, so access stays on the platform.

Power BI or Fabric connector - which one do I pick?

If you're on Fabric, pick this connector: it gives broader native lineage and more object types (lakehouse, warehouse, notebook, pipeline). The standalone Power BI connector remains for tenants still on classic Power BI Premium without Fabric workloads.