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Get data from Lakehouse

Version 1.1 by Dimitri Rupp on 2026/06/11 09:16
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For security reasons, the document is displayed in restricted mode as it is not the current version. There may be differences and errors due to this.
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🔑 Get data from Lakehouse

Information

Data in Fabric can be accessed by connecting to shared workspace items such as Lakehouses, using permissions set by the admin team. Users can query data via supported endpoints with read access granted for specific items or tables. This article guides you through accessing Lakehouse tables using the SQL endpoint.

🗺️ Workflow overview

flowchart TD
    subgraph ACCESS["🔐 Phase 1 · Access"]
        S1[1 · Check your access]
        S2[2 · Locate the Lakehouse]
        S3[3 · Get connection string]
    end
    subgraph CONNECT["🔌 Phase 2 · Connect"]
        S4[4 · Choose your tool]
        S5[5 · Connect to endpoint]
        S6[6 · Choose mode
Import vs Direct Query]
    end
    subgraph USE["📊 Phase 3 · Use"]
        S7[7 · Explore the tables]
        S8[8 · Write queries with T-SQL]
        S9[9 · Explore data & build reports]
    end

    S1 --> S2 --> S3 --> S4
    S4 --> S5 --> S6 --> S7
    S7 --> S8 --> S9

    style S1 fill:#e8f1fa,stroke:#4472c4,stroke-width:2px
    style S9 fill:#d4edda,stroke:#28a745,stroke-width:2px
    style ACCESS fill:#fafafa,stroke:#888
    style CONNECT fill:#fafafa,stroke:#888
    style USE fill:#fafafa,stroke:#888

Step 1 — Check your access

Access to a Lakehouse in Fabric is granted either through workspace roles or direct sharing. If you are assigned a role like Member or Viewer, you will see the workspace and can navigate to the Lakehouse directly. If the Lakehouse is shared with you individually, you will not see the workspace — use the link provided to access it. This link gives you access only to the shared item, and your permissions depend on what was granted.

Step 2 — Locate the Lakehouse

Navigate to the Lakehouse from the workspace or via the shared link. Confirm that the Lakehouse loads successfully and that you can view its contents.

Warning

You might be able to see all the schemas in the Lakehouse, but depending on your security role set by the Fabric team, tables and views might be unavailable. Contact the admins to change your access.

Step 3 — Get connection string

To locate the SQL endpoint, go to Home → Settings → SQL endpoint and copy the string.

Alternatively, you can copy the SQL endpoint connection string directly from within the Lakehouse interface by clicking the „Copy SQL connection string" option located at the bottom-left corner of the screen.

Step 4 — Choose your tool

Decide how you want to query the data — Power BI, SQL Server Management Studio (SSMS), Azure Data Studio, or any tool that supports the TDS protocol.

Step 5 — Connect to the endpoint

Use the SQL endpoint connection string to connect from your chosen tool. Authenticate using your organizational credentials when prompted.

Information

Tip: Database name is the name of the Lakehouse. Use SQL Server as the connector in Power BI (Desktop and Dataflows).

Step 6 — Choose the mode

If you are connecting to the Lakehouse from Power BI Desktop, after you choose the tables you have the option to select between Import or Direct Query:

  • Import — lets you download the selected tables to the model
  • Direct Query — creates a live connection

Step 7 — Explore the tables

Once connected, browse the database objects (tables, views) exposed via the SQL analytics endpoint. Only items you have permission for will be visible and accessible.

Step 8 — Write queries

Use T-SQL to write queries against the tables. You can perform joins, filters, aggregations, and other analytical operations.

Information

Note: In Power BI (Desktop and Dataflows), you can write queries in the Advanced options of the SQL Server connector (Step 5).

Step 9 — Explore data

Use the results for reporting, analysis, or export them to downstream tools like Power BI or Excel.

Information

Migration note: This page was migrated on 24.05.2026 from SharePoint WikiPowerBI into the Lumi-XWiki staging.

Original author: Bukkerji Sreejith (created and last modified 2025-10-10)
Original source: Get data from Lakehouse (SharePoint)
Migration: Dimitri Rupp via ClaudeAI

Migration remarks:

  • Original language (English) preserved
  • SharePoint 3-column step-card layout with decorative Hubble stock icons (purely decorative circles) converted to clean nine H2 sections — keeps full content, improves readability and accessibility
  • Mermaid flow overview added at the top to visualise the 9-step sequence at a glance
  • Note and Tip blocks rendered as XWiki info/warning boxes for emphasis

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Status: Migriert — Team-Review ausstehend · Owner: (festlegen) · Letzter Review: 2026-06-11