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Guided DP-600 Domain 2
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DP-600 Study Guide

Domain 1: Maintain a Data Analytics Solution

  • Workspace Access Controls
  • Row-Level & Object-Level Security
  • Sensitivity Labels & Endorsement
  • Git Version Control in Fabric
  • Deployment Pipelines: Dev β†’ Test β†’ Prod
  • Impact Analysis & Dependencies
  • XMLA Endpoint & Reusable Assets

Domain 2: Prepare Data

  • Microsoft Fabric: The Big Picture Free
  • Lakehouses: Your Data Foundation Free
  • Warehouses in Fabric Free
  • Choosing the Right Data Store Free
  • Data Connections & OneLake Catalog
  • Shortcuts & OneLake Integration
  • Ingesting Data: Dataflows Gen2 & Pipelines
  • Star Schema Design Free
  • SQL Objects: Views, Functions & Stored Procedures
  • Transforming Data: Reshape & Enrich
  • Data Quality & Cleansing
  • Querying with SQL
  • Querying with KQL
  • Querying with DAX

Domain 3: Implement and Manage Semantic Models

  • Semantic Models: Storage Modes
  • Relationships & Advanced Modeling
  • DAX Essentials: Variables & Functions
  • Calculation Groups & Field Parameters
  • Large Models & Composite Models
  • Direct Lake Mode
  • DAX Performance Optimization
  • Incremental Refresh

DP-600 Study Guide

Domain 1: Maintain a Data Analytics Solution

  • Workspace Access Controls
  • Row-Level & Object-Level Security
  • Sensitivity Labels & Endorsement
  • Git Version Control in Fabric
  • Deployment Pipelines: Dev β†’ Test β†’ Prod
  • Impact Analysis & Dependencies
  • XMLA Endpoint & Reusable Assets

Domain 2: Prepare Data

  • Microsoft Fabric: The Big Picture Free
  • Lakehouses: Your Data Foundation Free
  • Warehouses in Fabric Free
  • Choosing the Right Data Store Free
  • Data Connections & OneLake Catalog
  • Shortcuts & OneLake Integration
  • Ingesting Data: Dataflows Gen2 & Pipelines
  • Star Schema Design Free
  • SQL Objects: Views, Functions & Stored Procedures
  • Transforming Data: Reshape & Enrich
  • Data Quality & Cleansing
  • Querying with SQL
  • Querying with KQL
  • Querying with DAX

Domain 3: Implement and Manage Semantic Models

  • Semantic Models: Storage Modes
  • Relationships & Advanced Modeling
  • DAX Essentials: Variables & Functions
  • Calculation Groups & Field Parameters
  • Large Models & Composite Models
  • Direct Lake Mode
  • DAX Performance Optimization
  • Incremental Refresh
Domain 2: Prepare Data Premium ⏱ ~12 min read

Data Connections & OneLake Catalog

Before you transform data, you need to find it. Learn how to discover data with OneLake catalog and Real-Time hub, and create connections to external sources.

How does data get into Fabric?

β˜• Simple explanation

Think of data connections like plumbing in a building.

Before water (data) reaches your tap (lakehouse or warehouse), someone has to lay the pipes (connections) from the water main (source systems). Some pipes are permanent β€” they bring data from your company’s databases every night. Others are temporary β€” you hook up a garden hose to test something.

In Fabric, you discover what data exists using the OneLake catalog (like a building directory that shows where every pipe goes), and you connect to external sources using data connections (the plumbing itself).

Data connections in Microsoft Fabric define how Fabric items connect to data sources β€” both internal (OneLake items) and external (Azure SQL, Dataverse, Amazon S3, Google Cloud Storage, etc.). Connections store authentication credentials and endpoint information, and can be shared across multiple Fabric items (pipelines, dataflows, notebooks).

The OneLake catalog is Fabric’s data discovery experience β€” a searchable directory of all Fabric items across the tenant. It shows lakehouses, warehouses, semantic models, and other items with metadata, endorsement status, and sensitivity labels. The Real-Time hub extends this to streaming data sources β€” showing available event streams that can be connected to Eventhouse or other real-time consumers.

OneLake catalog: Find data across your organisation

The OneLake catalog is your starting point for data discovery. Instead of asking colleagues β€œwhere is the sales data?”, you search the catalog.

What the catalog shows

InformationDescription
Item name and typeLakehouse, warehouse, semantic model, dataflow, etc.
WorkspaceWhich workspace the item lives in
EndorsementWhether the item is Promoted or Certified (trust signals)
Sensitivity labelsClassification level (Confidential, Internal, Public, etc.)
DescriptionOwner-provided context about the item
LineageWhat upstream and downstream items are connected

Endorsement badges

Endorsement is how organisations signal data quality:

BadgeMeaningWho Can Apply
PromotedRecommended by the workspace owner β€” ready for useWorkspace Members and above
CertifiedVerified by a designated certifier β€” meets organisational standardsOnly users granted certification permissions by the Fabric admin
NoneNo endorsement β€” use with cautionβ€”
πŸ’‘ Exam tip: Promoted vs Certified

The exam tests whether you know who can apply each endorsement. Promoted can be applied by any user with write permission on the item (Contributors, Members, Admins). Certified requires special permissions configured by the Fabric admin in the admin portal β€” only designated users or groups can certify items. A certified item carries more trust than a promoted one.

Real-Time hub: Discover streaming sources

The Real-Time hub complements the OneLake catalog for streaming data:

  • Browse available streams β€” Event Hubs, Azure IoT Hub, Change Data Capture, custom streams
  • Preview data β€” see sample events before connecting
  • Connect to Eventhouse β€” create a direct link from a stream to an Eventhouse database
  • Set up alerts β€” trigger actions when specific patterns appear in the stream
πŸ’‘ Scenario: Dr. Sarah discovers patient monitoring data

Dr. Sarah at Pacific Health Network opens the Real-Time hub and discovers a stream of patient vital signs from ICU monitors, published by the hospital’s IoT team. She previews the data β€” heart rate, blood pressure, oxygen saturation, timestamped every 5 seconds.

She connects the stream to an Eventhouse database with one click. Within minutes, she can query the live vitals data with KQL and build a real-time clinical dashboard.

Without the Real-Time hub, she would have needed to coordinate with the IoT team, exchange connection strings, and configure ingestion manually.

Creating data connections

Data connections in Fabric are centralised, reusable, and shareable.

Connection types

Connection TypeUse CaseAuthentication
Cloud connectionsAzure SQL, Azure Data Lake, Dataverse, Snowflake, Google BigQueryOAuth, service principal, connection string
On-premises data gatewaySQL Server, Oracle, file shares behind a firewallGateway cluster + credentials
OneLake shortcutsReference data in ADLS Gen2, S3, GCS without copyingStorage account keys, SAS tokens, service principals

Creating a connection

  1. Go to Settings β†’ Manage connections and gateways (or create inline within a pipeline/dataflow)
  2. Select the connection type (e.g., Azure SQL Database)
  3. Provide the server and database details
  4. Configure authentication (OAuth 2.0, SQL auth, service principal)
  5. Test the connection and save
  6. The connection is now reusable across pipelines, dataflows, and notebooks in the workspace
πŸ’‘ Scenario: James connects to 15 client databases

James at Summit Consulting sets up data connections for each client’s source database. He creates named connections like client-a-sql-prod and client-b-dataverse so his team can reference them by name in pipelines and dataflows.

Because connections are workspace-level resources, he can control who has access to each client’s credentials. A consultant working on Client A never sees Client B’s connection details.

Question

What is the OneLake catalog?

Click or press Enter to reveal answer

Answer

A searchable directory of all Fabric items across the tenant β€” lakehouses, warehouses, semantic models, and more. It shows metadata, endorsement status (Promoted/Certified), sensitivity labels, and lineage. It helps users discover existing data without asking colleagues.

Click to flip back

Question

What is the difference between Promoted and Certified endorsement?

Click or press Enter to reveal answer

Answer

Promoted can be applied by any user with write permission on the item (Contributors, Members, Admins) β€” it signals 'recommended for use.' Certified requires special certification permissions configured by the Fabric admin β€” it signals 'verified against organisational standards.' Certified carries higher trust.

Click to flip back

Question

What is the Real-Time hub in Fabric?

Click or press Enter to reveal answer

Answer

A discovery experience for streaming data sources. It lets you browse available event streams (Event Hubs, IoT Hub, Change Data Capture), preview live data, and connect streams to Eventhouse databases or other real-time consumers with minimal configuration.

Click to flip back

Knowledge Check

James at Summit Consulting wants to mark a client's warehouse as trustworthy for the broader analytics team. He is a workspace Admin. Which endorsement level can he apply?

Knowledge Check

Raj at Atlas Capital needs to connect Fabric to an on-premises SQL Server database behind the company firewall. The database contains compliance data that cannot be moved to the cloud. Which connection method should he use?

🎬 Video coming soon


Next up: Shortcuts & OneLake Integration β€” reference external data without copying it, and integrate Eventhouse data with the rest of Fabric.

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Choosing the Right Data Store

Next β†’

Shortcuts & OneLake Integration

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