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1.3 Data Source Settings and Parameters

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Microsoft Power BI Data Analyst PL-300

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1 Introduction

About the PL-300 Exam The Power BI Ecosystem

2 Chapter 1: Get or Connect to Data

1.1 Data Source Types and Connections 1.2 Storage Modes: Import, DirectQuery, and Direct Lake 1.3 Data Source Settings and Parameters

3 Chapter 2: Profile and Clean the Data

2.1 Data Profiling in Power Query 2.2 Resolving Errors, Nulls, and Data Quality Issues 2.3 Data Types and Type Detection

4 Chapter 3: Transform and Load the Data

3.1 Column Transformations and Data Types 3.2 Grouping, Aggregating, Pivoting, and Unpivoting 3.3 Merge Queries, Append Queries, and Relationship Keys 3.4 Query Folding and Load Performance

5 Chapter 4: Design and Implement a Data Model

4.1 Star Schema Design 4.2 Relationships, Cardinality, and Cross-Filter Direction 4.3 Table and Column Properties 4.4 Calculated Columns and Calculated Tables

6 Chapter 5: Create Model Calculations with DAX

5.1 DAX Fundamentals and Measures 5.2 The CALCULATE Function 5.3 Time Intelligence Measures 5.4 Statistical Functions, Semi-Additive Measures, and Calculation Groups 5.5 Essential DAX Patterns and Functions Reference

7 Chapter 6: Optimize Model Performance

6.1 Performance Analyzer and DAX Query View 6.2 Model Size Reduction and Cardinality Management 6.3 DAX Optimization Patterns

8 Chapter 7: Create Reports

7.1 Visual Types and Selection 7.2 Visual Formatting and Conditional Formatting 7.3 Copilot in Power BI Reports 7.4 Report Page Configuration and Slicers

9 Chapter 8: Enhance Reports for Usability and Storytelling

8.1 Bookmarks, Navigation, and Drillthrough 8.2 Sorting, Selection Pane, Mobile Layout, and Accessibility 8.3 Export Settings and Automatic Page Refresh

10 Chapter 9: Identify Patterns and Trends

9.1 The Analyze Feature and AI Visuals 9.2 Using Copilot to Summarize the Semantic Model 9.3 Advanced Analytics Patterns

11 Chapter 10: Create and Manage Workspaces and Assets

10.1 Workspaces, Apps, and Content Distribution 10.2 Subscriptions, Alerts, and Semantic Model Refresh 10.3 Dashboards and Advanced Distribution

12 Chapter 11: Secure and Govern Power BI Items

11.1 Row-Level Security (RLS) 11.2 Sensitivity Labels, Item Access, and Governance 11.3 Deployment Pipelines and Content Lifecycle

1.3 Data Source Settings and Parameters

Key Takeaways Explain This Topic AI

Data source settings control credentials, privacy levels, and connection properties for each source.

Privacy levels (Private, Organizational, Public) determine how data from different sources can be combined.

Parameters allow dynamic connection strings, enabling environment switching and user-configurable queries.

Credentials can be updated in Desktop via Data Source Settings or in the Service via dataset settings.

Query parameters use the M language and can be referenced in connection strings, filter values, and transformations.

Last updated: June 2026

Quick Answer: Data source settings manage credentials and privacy levels for each connection. Privacy levels (Private, Organizational, Public) control data mixing between sources. Parameters let you create dynamic connection strings so you can switch servers, databases, or filter values without editing queries manually.

  • Data Source Settings
  • Data source settings are managed in Power BI Desktop under: File → Options and Settings → Data Source Settings
  • What You Can Configure
  • Setting Description
  • Credentials Username/password, OAuth tokens, API keys
  • Privacy Level Private, Organizational, or Public
  • Connection Type Encryption settings, certificate validation
  • Permissions Edit or delete source credentials
  • Managing Credentials

Each data source stores credentials independently. When credentials expire or change:

  • Open Data Source Settings in Power BI Desktop
  • Select the affected data source
  • Click Edit Permissions → Edit Credentials
  • Enter new credentials and test the connection

In the Power BI Service , credentials are managed per dataset:

  • Navigate to Settings → Datasets → select the dataset
  • Under Data source credentials , configure each source
  • Service credentials are separate from Desktop credentials

Exam Tip: When you publish a report, credentials do NOT transfer to the Service. You must configure credentials in the Service separately.

Privacy Levels

Privacy levels are a critical concept that controls how Power BI combines data from different sources.

The Three Privacy Levels

  • Level Description Combining Rules
  • Private Sensitive data (HR records, financials) Only combined with other Private sources from the same source
  • Organizational Internal business data Can be combined with other Organizational sources; isolated from Public
  • Public Publicly available data (web, open data) Can be combined with any source
  • Privacy Level Implications

When combining data from sources with different privacy levels:

  • Private + Public = Blocked (Power BI will not combine these)
  • Private + Organizational = Blocked
  • Organizational + Organizational = Allowed
  • Organizational + Public = Allowed (Organizational level is maintained)
  • Public + Public = Allowed

Warning: Setting the privacy level to "None" disables privacy checks entirely. This is useful for development but should never be used in production with sensitive data.

Configuring Privacy Levels

Privacy levels can be set:

  • Per data source — In Data Source Settings when first connecting
  • Globally — Under File → Options → Privacy
  • "Always combine data according to privacy settings" (recommended)
  • "Combine data according to each file's privacy level settings"
  • "Always ignore privacy level settings" (development only)
  • Parameters

Parameters in Power BI are variables that can be referenced in queries, connection strings, and transformations.

  • Creating Parameters
  • In Power Query Editor: Home tab → Manage Parameters → New Parameter

Configure:

Name : Descriptive identifier (e.g., ServerName, DatabaseName)

Type : Text, Decimal Number, Date/Time, True/False, etc.

  • Suggested Values : Any value, List of values, or Query
  • Default Value : The initial value
  • Current Value : The active value used in queries
  • Common Parameter Use Cases
  • 1. Dynamic Server/Database Connections

Create parameters for server and database names to switch between development, test, and production environments without editing queries: let

  • Source = Sql.Database(ServerName, DatabaseName)
  • in
  • Source
  • 2. Dynamic Filter Values
  • Use parameters to filter data at the source, reducing the amount of data loaded: let
  • Source = Sql.Database("myserver", "mydb"),
  • Filtered = Table.SelectRows(Source, each [Year] >= StartYear)
  • in
  • Filtered
  • 3. Dynamic File Paths
  • Reference a parameter for file locations: let
  • Source = Csv.Document(File.Contents(FilePath))
  • in
  • Source
  • Modifying Parameters

Parameters can be changed in two ways:

  • Power BI Desktop : Home → Transform Data → Edit Parameters
  • Power BI Service : Dataset Settings → Parameters section

Exam Tip: When using parameters for data source connections, changes in the Power BI Service will trigger a data refresh with the new parameter values.

  • Parameter Best Practices
  • Use descriptive names (ServerName, not Param1)
  • Set suggested values as a list when there are known options
  • Always provide a default value for published reports
  • Document parameter purposes in a README table within the model
  • Use parameters with deployment pipelines for environment management
  • Privacy Levels and the Formula Firewall

Privacy levels exist to stop Power Query from accidentally leaking sensitive data to an external source. Internally this protection is enforced by the Formula Firewall , which prevents a query that touches one source from passing data into a query that touches a differently-classified source within the same evaluation.

This is why a query that combines a Private HR table with a Public web API throws a "Formula.Firewall: Query references other queries, so it may not directly access a data source" or a privacy-level error at refresh time. The fix is rarely to disable privacy — instead, separate the offending logic into staging queries so each query references a single source, or align the privacy levels when the data truly may be combined.

Parameters in Deployment Pipelines

Parameters become especially powerful with deployment pipelines (Dev → Test → Production). Each pipeline stage can override a parameter's value through parameter rules , so the same .pbix points at the development server in Dev and the production server in Production without any manual M edits.

  • Parameter pattern Benefit
  • ServerName / DatabaseName Switch environments per pipeline stage
  • RangeStart / RangeEnd (Date/Time) Drive incremental refresh windows
  • RowLimit Load a small sample in Dev, full data in Prod

Exam Tip: Remember the two-part rule for moving a report to the Service: (1) credentials never publish with the file — set them in dataset settings; and (2) parameter values can be edited in the Service under Dataset settings → Parameters , which triggers a refresh with the new values.

On the Exam

The PL-300 frequently tests:

  • Understanding privacy level implications when combining data sources
  • Creating and modifying parameters for dynamic connections
  • Managing credentials in both Desktop and Service
  • Knowing that credentials don't transfer when publishing
  • Using parameters with deployment pipelines for environment switching