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Microsoft Fabric is Microsoft’s unified analytics platform, combining data engineering, warehousing and business intelligence on top of OneLake. Nekt reads from Fabric through the SQL analytics endpoint that every Lakehouse and Warehouse exposes, so any table or view you can query in Fabric can be brought into your Catalog — along with custom SQL queries of your own.

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Before you start

Microsoft Fabric accepts Microsoft Entra ID authentication only — there is no SQL username and password. The recommended setup for scheduled syncs is a service principal, which is an application identity in your own Microsoft Entra tenant. Nekt does not register an application on your behalf, so the three steps below all happen inside your organization.
1

Register an application in Microsoft Entra

In the Azure portal, go to Microsoft Entra ID → App registrations → New registration. Give it a name such as “Nekt connector” and register it.From the app’s Overview page, copy the Directory (tenant) ID and the Application (client) ID. Then go to Certificates & secrets → New client secret, create one, and copy its Value immediately — it is only shown once.
Client secrets expire. Note the expiry date you chose: when the secret expires, the source stops extracting until you create a new one and update it in Nekt.
2

Allow service principals to use the Fabric API

A Fabric administrator must enable the tenant setting “Service principals can use Fabric APIs” in the Fabric admin portal, under Tenant settings → Developer settings.If your organization restricts that setting to a security group, the application registered in step 1 must be added to that group.
This step is not optional, and skipping it produces confusing symptoms. Microsoft Fabric issues the service principal a security token through its API, not through the SQL connection. Without that token, queries can fail with “permission denied” or “file not found” errors even though the workspace access is configured correctly.
3

Give the application access to the workspace

In Fabric, open the workspace holding your Lakehouse or Warehouse, select Manage access → Add people or groups, and add the application registered in step 1.The Viewer role is enough for Nekt to read data. You can also share a single Warehouse with the application through item permissions instead of granting workspace-wide access.
4

Copy the SQL connection string

Open your Lakehouse or Warehouse in Fabric, go to Settings → SQL analytics endpoint (or SQL endpoint for a Warehouse) and copy the SQL connection string. It looks like abcd1234efgh.datawarehouse.fabric.microsoft.com.Note the name of the Lakehouse or Warehouse as well — that is the Database value Nekt asks for.
If your tenant restricts inbound public access to Fabric, you may also need to allow Nekt’s public IP. See this guide for where to find it.

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1. Add account access

  1. In the Sources tab, click the “Add source” button at the top right of your screen, then select Microsoft Fabric from the list of connectors.
  2. Click Next and fill in the connection settings:
    • SQL connection string: the value copied in step 4 above.
    • Database: the name of the Lakehouse or Warehouse to read from.
    • Authentication method: leave it as Service principal.
    • Tenant ID, Client ID and Client Secret: the values from your app registration.
  3. Click Next.
If your organization cannot approve a service principal, set Authentication method to Microsoft Entra user and password and provide the user principal name and password of a Microsoft Entra account that has access to the workspace.Multi-factor authentication must be disabled for that account, and the sync will break whenever the password changes — so this is a fallback, not the recommended setup.
If the Lakehouse or Warehouse contains a large number of tables, you can narrow discovery down with two optional settings.Filter schemas takes a comma-separated list of schema names:
Naming a schema explicitly also brings back schemas Nekt hides by default, such as Fabric’s own queryinsights.Filter tables takes a comma-separated list with the following patterns:
  • schema.table — match a specific table in a specific schema
  • table — match a table with this name in any schema
  • Wildcard patterns using * (any sequence) and ? (a single character)
Examples:
If neither setting is filled in, every table and view in the endpoint is available.
Fabric is a warehouse, so the data you want is often a join or an aggregate rather than a raw table. Query Streams lets you define SQL that runs inside Fabric and arrives in Nekt as its own table — which also moves far less data than extracting the underlying tables and rebuilding the result afterwards.Each entry needs a Stream Name (lowercase letters, digits and underscores, starting with a letter) and the SQL Query itself.Enable Query streams only if you want the source to sync nothing but these queries, skipping table and view discovery entirely.

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2. Select streams

Choose which data streams you want to sync — you can select all streams or pick specific ones that matter most to you. We recommend selecting only the tables that are useful to you. You can add new tables at any time after the source is created.
Tip: The stream can be found more easily by typing its name.
Select the streams and click Next.

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3. Configure data streams

Customize how you want your data to appear in your catalog. Select a name for each table (which will contain the fetched data) and the type of sync.
  • Table name: we suggest a name, but feel free to customize it. You have the option to add a prefix and make this process faster!
  • Sync Type: you can choose between INCREMENTAL and FULL_TABLE.
    • Incremental: every time the extraction happens, we’ll get only the new data - which is good if, for example, you want to keep every record ever fetched.
    • Full table: every time the extraction happens, we’ll get the current state of the data - which is good if, for example, you don’t want to have deleted data in your catalog.
Most Fabric tables arrive without a primary key, and this is expected rather than a problem. A Lakehouse SQL analytics endpoint carries no key metadata at all, and a Warehouse only reports keys that were added explicitly — Fabric never enforces them, so even a declared key can contain duplicates.That means you will usually pick the key columns and the incremental column yourself on this screen. If a table has no reliable column to track changes by, choose FULL_TABLE.
Once you are done configuring, click Next.

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4. Configure data source

Describe your data source for easy identification within your organization, not exceeding 140 characters. To define your Trigger, consider how often you want data to be extracted from this source. Bear in mind that each sync consumes Fabric capacity units, so a schedule matched to how often the data actually changes keeps your Fabric costs down. Optionally, you can determine when to execute a full sync. This will complement the incremental data extractions, ensuring that your data is completely synchronized with your source every once in a while. Once you are ready, click Next to finalize the setup.

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5. Check your new source

You can view your new source on the Sources page. If needed, manually trigger the source extraction by clicking on the arrow button. Once executed, your data will appear in your Catalog.
For you to be able to see it on your Catalog, you need at least one successful source run.

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Good to know

  • Timestamps have no time zone. A Fabric Warehouse cannot store datetimeoffset, and a Lakehouse endpoint maps Delta TIMESTAMP values to datetime2. Timestamps arrive exactly as they are stored in Fabric, with no offset applied.
  • Fabric supports a narrower set of data types than SQL Server does. Columns of types Fabric cannot persist — such as money, datetime, nvarchar or json — only appear through views or query streams, and are read as their closest equivalent.
  • Binary columns (varbinary) are delivered base64-encoded, and uniqueidentifier columns as text.
  • Both Lakehouses and Warehouses work. A Lakehouse SQL analytics endpoint is read-only by nature, which is all Nekt needs.

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Skills for agents

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Microsoft Fabric connector documentation as plain markdown, for use in AI agent contexts.