Tag: Business Intelligence

Analytics, Business Intelligence, Data Visualization January 23, 2026January 29, 2026

Glossary – 100 “Data Visualization” Terms

Below is a glossary that includes 100 common “Data Visualization” terms and phrases in alphabetical order. Enjoy!

Term	Definition & Example
Accessibility	Designing for all users. Example: Colorblind-friendly palette.
Aggregation	Summarizing data. Example: Sum of sales.
Alignment	Proper positioning of elements. Example: Grid layout.
Annotation	Explanatory text on a visual. Example: Highlighting a spike.
Area Chart	Line chart with filled area. Example: Cumulative sales.
Axis	Reference line for measurement. Example: X and Y axes.
Bar Chart	Uses bars to compare categories. Example: Sales by product.
Baseline	Reference starting point. Example: Zero line.
Best Practice	Recommended visualization approach. Example: Avoid 3D charts.
Binning	Grouping continuous values. Example: Age ranges.
Box Plot	Displays data distribution and outliers. Example: Salary ranges.
Bubble Chart	Scatter plot with size dimension. Example: Profit by region and size.
Card	Displays a single value. Example: Total customers.
Categorical Scale	Discrete category scale. Example: Product names.
Chart	Visual representation of data values. Example: Bar chart of revenue by region.
Chart Junk	Unnecessary visual elements. Example: Excessive shadows.
Choropleth Map	Map colored by value. Example: Sales by state.
Cognitive Load	Mental effort required to interpret. Example: Overly complex charts.
Color Encoding	Using color to represent data. Example: Red for losses.
Color Palette	Selected set of colors. Example: Brand colors.
Column Chart	Vertical bar chart. Example: Revenue by year.
Comparative Analysis	Comparing values. Example: Year-over-year sales.
Conditional Formatting	Formatting based on values. Example: Red for negative.
Context	Supporting information for visuals. Example: Benchmarks.
Continuous Scale	Numeric scale without breaks. Example: Temperature.
Correlation	Relationship between variables. Example: Scatter plot trend.
Dashboard	Collection of visualizations on one screen. Example: Executive KPI dashboard.
Dashboard Layout	Arrangement of visuals. Example: Top-down flow.
Data Density	Amount of data per visual area. Example: Dense scatter plot.
Data Ink Ratio	Proportion of ink used for data. Example: Minimal chart clutter.
Data Refresh	Updating visualized data. Example: Daily refresh.
Data Story	Structured insight narrative. Example: Executive presentation.
Data Visualization	Graphical representation of data. Example: Sales trends shown in a line chart.
Data-to-Ink Ratio	Proportion of ink showing data. Example: Minimalist charts.
Density Plot	Smoothed distribution visualization. Example: Probability density.
Distribution	Spread of data values. Example: Histogram shape.
Diverging Chart	Shows deviation from a baseline. Example: Profit vs target.
Diverging Palette	Colors diverging from midpoint. Example: Profit/loss.
Donut Chart	Pie chart with a center hole. Example: Expense breakdown.
Drill Down	Navigating to more detail. Example: Year → month → day.
Drill Through	Navigating to a detailed report. Example: Customer detail page.
Dual Axis Chart	Two measures on different axes. Example: Sales and margin.
Emphasis	Drawing attention to key data. Example: Bold colors.
Explanatory Visualization	Used to communicate findings. Example: Board presentation.
Exploratory Visualization	Used to discover insights. Example: Ad-hoc analysis.
Faceting	Splitting data into subplots. Example: One chart per category.
Filtering	Limiting displayed data. Example: Filter by year.
Footnote	Additional explanation text. Example: Data source note.
Forecast	Predicted future values. Example: Next quarter sales.
Funnel Chart	Shows process stages. Example: Sales pipeline.
Gauge	Displays progress toward a target. Example: KPI completion.
Geospatial Visualization	Data mapped to geography. Example: Customer density map.
Granularity	Level of data detail. Example: Daily vs monthly.
Graph	Diagram showing relationships between variables. Example: Scatter plot of height vs weight.
Grouping	Combining similar values. Example: Products by category.
Heatmap	Uses color to show intensity. Example: Sales by day and hour.
Hierarchy	Parent-child relationships. Example: Country → State → City.
Highlighting	Emphasizing specific data. Example: Selected bar.
Histogram	Distribution of numerical data. Example: Customer age distribution.
Insight	Meaningful takeaway from data. Example: Sales decline identified.
Interactivity	User-driven exploration. Example: Click to filter.
KPI Visual	Highlights key performance metrics. Example: Total revenue card.
Label	Text identifying data points. Example: Value labels on bars.
Legend	Explains colors or symbols. Example: Product categories.
Legend Placement	Position of legend. Example: Right side.
Line Chart	Shows trends over time. Example: Daily website traffic.
Matrix	Table with grouped dimensions. Example: Sales by region and year.
Outlier	Value far from others. Example: Extremely high sales.
Pan	Move across a visual. Example: Map navigation.
Pie Chart	Displays parts of a whole. Example: Market share.
Proportion	Part-to-whole relationship. Example: Market share.
Ranking	Displaying relative position. Example: Top 10 customers.
Real-Time Visualization	Live data display. Example: Streaming metrics.
Reference Line	Benchmark line on chart. Example: Target line.
Report	Structured set of visuals and text. Example: Monthly performance report.
Responsive Design	Adjusts to screen size. Example: Mobile dashboards.
Scatter Plot	Shows relationship between two variables. Example: Ad spend vs revenue.
Sequential Palette	Gradual color progression. Example: Low to high values.
Shape Encoding	Using shapes to distinguish categories. Example: Circles vs triangles.
Size Encoding	Using size to represent values. Example: Bubble size.
Slicer	Interactive filter control. Example: Dropdown region selector.
Small Multiples	Series of similar charts. Example: Sales by region panels.
Sorting	Ordering data values. Example: Top-selling products.
Storytelling	Communicating insights visually. Example: Narrative dashboard. To learn more, check out this article on Data Storytelling.
Subtitle	Supporting chart description. Example: Fiscal year context.
Symbol Map	Map using symbols. Example: Store locations.
Table	Data displayed in rows and columns. Example: Transaction list.
Title	Descriptive chart heading. Example: “Monthly Sales Trend.”
Tooltip	Hover text showing details. Example: Exact value on hover.
Treemap	Hierarchical data using rectangles. Example: Revenue by category.
Trendline	Shows overall direction. Example: Sales trend.
Visual Clutter	Overcrowded visuals. Example: Too many labels.
Visual Consistency	Uniform styling across visuals. Example: Same fonts/colors.
Visual Encoding	Mapping data to visuals. Example: Color = category.
Visual Hierarchy	Ordering elements by importance. Example: Large KPI at top.
Waterfall Chart	Shows cumulative effect of changes. Example: Profit bridge analysis.
White Space	Empty space improving readability. Example: Padding between charts.
X-Axis	Horizontal axis. Example: Time dimension.
Y-Axis	Vertical axis. Example: Sales amount.
Zoom	Focus on specific area. Example: Map zoom.

Analytics, Business Intelligence, Data Education & Training, Microsoft Certification, PL-300, Power BI January 17, 2026January 17, 2026

Exam Prep Hub for PL-300: Microsoft Power BI Data Analyst

Welcome to the one-stop hub with information for preparing for the PL-300: Microsoft Power BI Data Analyst certification exam. Upon successful completion of the exam, you earn the Microsoft Certified: Power BI Data Analyst Associate certification.

This hub provides information directly here (topic-by-topic), links to a number of external resources, tips for preparing for the exam, practice tests, and section questions to help you prepare. Bookmark this page and use it as a guide to ensure that you are fully covering all relevant topics for the PL-300 exam and making use of as many of the resources available as possible.

Skills tested at a glance (as specified in the official study guide)

Prepare the data (25–30%)
Model the data (25–30%)
Visualize and analyze the data (25–30%)
Manage and secure Power BI (15–20%)

Click on each hyperlinked topic below to go to the preparation content and practice questions for that topic. And there are also 2 practice exams provided below.

Prepare the data (25–30%)

Get or connect to data

Profile and clean the data

Transform and load the data

Model the data (25–30%)

Design and implement a data model

Create model calculations by using DAX

Optimize model performance

Visualize and analyze the data (25–30%)

Create reports

Enhance reports for usability and storytelling

Identify patterns and trends

Manage and secure Power BI (15–20%)

Create and manage workspaces and assets

Secure and govern Power BI items

Practice Exams

We have provided 2 practice exams (with answer keys) to help you prepare:

Important PL-300 Resources

Link to the free, comprehensive, self-paced course on Microsoft Learn – Design and manage analytics solutions using Power BI
It contains 5 Learning Paths, each with multiple Modules, and each module has multiple Units. It will take some time to do it, but we recommend that you complete this entire course, including the exercises/labs.
Link to the certification page: Microsoft Certified: Power BI Data Analyst Associate certification page
Link to the study guide: Study guide for Exam PL-300: Microsoft Power BI Data Analyst

YouTube videos you will find useful:

Reddit Power BI Thread
Datacamp’s Data Analyst in Power BI track (this is a paid service)

To Do’s:

Schedule time to learn, study, perform labs, and do practice exams and questions
Schedule the exam based on when you think you will be ready; scheduling the exam gives you a target and drives you to keep working on it; but keep in mind that it can be rescheduled based on the rules of the provider.
Use the various resources above and below to learn
Take the free Microsoft Learn practice test, any other available practice tests, and do the practice questions in each section and the two practice tests available on this hub.

Good luck to you passing the PL-300: Microsoft Power BI Data Analyst certification exam and earning the Microsoft Certified: Power BI Data Analyst Associate certification!

Data Security, BI Administration, Power BI, Microsoft Certification, PL-300 January 17, 2026

Configure Row-Level Security Group Membership (PL-300 Exam Prep)

This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Manage and secure Power BI (15–20%)
   --> Secure and govern Power BI items
      --> Configure Row-Level Security Group Membership

Note that there are 10 practice questions (with answers and explanations) at the end of each topic. Also, there are 2 practice tests with 60 questions each available on the hub below all the exam topics.

Overview

Configuring Row-Level Security (RLS) group membership is a key governance and scalability topic within the “Manage and secure Power BI (15–20%)” domain of the PL-300: Microsoft Power BI Data Analyst certification exam. This topic builds on basic RLS concepts and focuses on how users are assigned to RLS roles, with an emphasis on using Microsoft Entra ID (Azure AD) security groups instead of individual users.

For the exam, you should understand where RLS roles are defined, where group membership is configured, how group-based RLS behaves, and why it is considered a best practice.

What Is RLS Group Membership?

RLS group membership refers to assigning security groups (rather than individual users) to Row-Level Security roles in a Power BI semantic model. Any user who is a member of the group automatically inherits the data access defined by the role.

This approach:

Improves scalability
Simplifies administration
Aligns with enterprise security standards
Reduces ongoing maintenance

Exam Focus: The PL-300 exam strongly favors group-based RLS as the recommended approach.

Where RLS Group Membership Is Configured

Understanding where actions occur is frequently tested.

Power BI Desktop

Create RLS roles
Define DAX filter expressions
No users or groups are assigned here

Power BI Service

Assign users or security groups to RLS roles
Manage role membership after publishing

Key Distinction:

Roles and filters → Desktop

Users and groups → Service

Why Use Security Groups for RLS?

Benefits of Group-Based RLS

Centralized identity management
Groups are managed in Microsoft Entra ID, not Power BI.
Automatic access updates
Adding or removing users from a group instantly updates data access.
Reduced administrative effort
No need to modify RLS settings when staff changes.
Auditability and compliance
Easier to review who has access and why.

Exam Tip: If a question asks for the most scalable or best practice approach, choose security groups.

Types of Groups Used in RLS

Supported Group Types

Microsoft Entra ID security groups (recommended)
Mail-enabled security groups

Not Recommended / Not Supported

Distribution lists (not ideal for security)
Microsoft 365 groups (not designed for RLS scenarios)

PL-300 Expectation: Know that security groups are the preferred option for RLS role membership.

Assigning Groups to RLS Roles

Step-by-Step (Power BI Service)

Publish the semantic model from Power BI Desktop
In the Power BI Service, open the semantic model
Select Security
Choose an RLS role
Add one or more security groups
Save changes

Once assigned, all group members inherit the role’s data filters.

Group Membership and Dynamic RLS

Group membership is often combined with dynamic RLS for maximum flexibility.

Common Pattern

RLS role contains a dynamic filter using USERPRINCIPALNAME()
A mapping table links users to business entities (e.g., region, department)
A security group controls who is subject to that role

This pattern:

Minimizes the number of roles
Supports large organizations
Separates identity management from data logic

How Group-Based RLS Is Evaluated

When a user opens a report:

Power BI identifies the user’s Entra ID group memberships
The user is matched to assigned RLS roles
The union of all applicable role filters is applied
Only authorized rows are returned

Important Exam Concept:
Users in multiple roles see the combined (union) of allowed data—not the most restrictive set.

Testing Group-Based RLS

In Power BI Desktop

Use View as
Test role logic only (group membership is not evaluated here)

In Power BI Service

Use View as role
Or test by signing in as a user who belongs to the group

Exam Awareness: Group membership itself cannot be fully tested in Desktop—only in the Service.

Common Pitfalls (Exam-Relevant)

Assigning individual users instead of groups
Expecting RLS to apply before publishing
Forgetting that group membership changes happen outside Power BI
Confusing workspace roles with RLS roles
Assuming admins bypass RLS automatically

RLS Group Membership vs Workspace Roles

Feature	Workspace Roles	RLS Group Membership
Controls content access	✅	❌
Controls data visibility	❌	✅
Uses Entra ID groups	✅	✅
Defined in Desktop	❌	❌
Assigned in Service	✅	✅

PL-300 Focus: These are complementary—not interchangeable—security mechanisms.

Governance and Best Practices

Always prefer security groups over individuals
Use clear, business-aligned group names
Keep RLS logic simple and documented
Coordinate with identity administrators
Review group membership regularly

Common Exam Scenarios

You may be asked to identify:

The best way to manage RLS for hundreds of users
Why a user gained or lost data access without a model change
Where to update access when an employee changes roles
How group membership impacts RLS evaluation

Key Takeaways for the PL-300 Exam

RLS roles are defined in Power BI Desktop
Group membership is configured in the Power BI Service
Microsoft Entra ID security groups are the recommended approach
Group-based RLS improves scalability and governance
Users see the union of all assigned RLS roles
RLS applies to all reports and apps using the semantic model

Practice Questions

Go to the Practice Questions for this topic.

BI Administration, Data Governance, Data Security, Microsoft Certification, PL-300, Power BI January 17, 2026January 17, 2026

Implement Row-Level Security (RLS) Roles (PL-300 Exam Prep)

This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Manage and secure Power BI (15–20%)
   --> Secure and govern Power BI items
      --> Implement Row-Level Security (RLS) Roles

Note that there are 10 practice questions (with answers and explanations) at the end of each topic. Also, there are 2 practice tests with 60 questions each available on the hub below all the exam topics.

Overview

Implementing Row-Level Security (RLS) is a critical skill for Power BI Data Analysts and a key topic within the “Manage and secure Power BI (15–20%)” domain of the PL-300: Microsoft Power BI Data Analyst certification exam. RLS ensures that users only see the data they are authorized to view, even when accessing the same reports or semantic models.

For the exam, you must understand how RLS roles are created, how they are implemented using DAX, how users and groups are assigned, and how RLS behaves in the Power BI Service.

What Is Row-Level Security?

Row-Level Security restricts access to specific rows of data in a semantic model based on the identity of the user viewing the report.

RLS:

Is defined in Power BI Desktop
Uses DAX filter expressions
Is enforced in the Power BI Service
Applies to all reports that use the semantic model

Key Concept: RLS controls data visibility, not report visibility.

RLS Architecture in Power BI

The RLS workflow consists of four main steps:

Define roles in Power BI Desktop
Create DAX filter expressions for tables
Publish the semantic model to the Power BI Service
Assign users or groups to roles in the Service

Each role defines which rows are visible when the user is a member of that role.

Creating RLS Roles in Power BI Desktop

Step 1: Create Roles

In Power BI Desktop:

Go to Model view or Report view
Select Modeling → Manage roles
Create one or more roles (e.g., SalesWest, SalesEast)

Roles are placeholders until users or groups are assigned in the Power BI Service.

Step 2: Define Table Filters (DAX)

RLS is implemented using DAX filter expressions applied to tables.

Example: Static RLS

[Region] = "West"

This filter ensures that users assigned to the role only see rows where Region equals West.

Exam Tip: RLS filters act like WHERE clauses and reduce visible rows—not columns.

Static vs Dynamic RLS

Static RLS

Filters are hardcoded values
Each role represents a specific segment
Easy to understand, but not scalable

Example:

[Department] = "Finance"

Dynamic RLS (Highly Exam-Relevant)

Dynamic RLS uses the logged-in user’s identity to filter data automatically.

Common functions:

USERPRINCIPALNAME()
USERNAME()

Example:

[Email] = USERPRINCIPALNAME()

Dynamic RLS:

Scales well
Reduces number of roles
Is commonly used in enterprise models

Best Practice: Use dynamic RLS with a user-to-dimension mapping table.

Assigning Users to RLS Roles (Power BI Service)

After publishing the semantic model:

Go to the Power BI Service
Navigate to the semantic model
Select Security
Assign users or Microsoft Entra ID (Azure AD) groups to roles

Best Practice: Always assign security groups, not individual users.

Testing RLS

In Power BI Desktop

Use Modeling → View as
Test roles before publishing
Validate DAX logic

In Power BI Service

Use View as role
Confirm correct filtering for assigned users

Exam Tip: “View as” does not bypass RLS—it simulates user access.

RLS Behavior in Common Scenarios

Reports and Dashboards

RLS applies automatically
Users cannot see restricted data
Visual totals reflect filtered data

Power BI Apps

RLS is enforced
No additional configuration required

Analyze in Excel / External Tools

RLS is enforced if the user has Build permission
Users cannot bypass RLS through external connections

Important RLS Limitations (Exam Awareness)

RLS does not hide tables or columns (use Object-Level Security for that)
RLS cannot be applied directly to measures
Workspace Admins are not exempt from RLS unless explicitly configured
RLS does not apply in Power BI Desktop for the model author unless using “View as”

Object-Level Security (OLS) vs RLS

Feature	RLS	OLS
Controls rows	✅	❌
Controls columns/tables	❌	✅
Configured in Desktop	✅	❌ (External tools)
Exam depth	High	Awareness only

PL-300 Focus: RLS concepts are tested far more deeply than OLS.

Governance and Best Practices

Use dynamic RLS wherever possible
Centralize security logic in the semantic model
Use groups, not individuals
Document role logic for maintainability
Test RLS thoroughly before sharing reports

Common Exam Scenarios

You may be asked to determine:

Why different users see different values in the same report
How to reduce the number of RLS roles
How to implement user-based filtering
Where RLS logic is created vs enforced

Key Takeaways for the PL-300 Exam

RLS restricts row-level data visibility
Roles and filters are created in Power BI Desktop
Users and groups are assigned in the Power BI Service
Dynamic RLS uses USERPRINCIPALNAME()
RLS applies to all reports and apps using the semantic model
RLS is enforced at the semantic model level

Practice Questions

Go to the Practice Questions for this topic.

Data Security, BI Administration, Power BI, Microsoft Certification, PL-300 January 17, 2026

Configure Access to Semantic Models (PL-300 Exam Prep)

This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Manage and secure Power BI (15–20%)
   --> Secure and govern Power BI items
      --> Configure Access to Semantic Models

Note that there are 10 practice questions (with answers and explanations) at the end of each topic. Also, there are 2 practice tests with 60 questions each available on the hub below all the exam topics.

Overview

Configuring access to semantic models (formerly known as datasets) is a core responsibility of a Power BI Data Analyst and a key topic within the “Manage and secure Power BI (15–20%)” domain of the PL-300 exam. This topic focuses on how access to data models is controlled, shared, governed, and secured so that users can interact with data appropriately—without compromising data integrity or confidentiality.

For the exam, you should understand how semantic models are shared, who can access them, what level of access they have, and how security is enforced at both the model and row level.

What Is a Semantic Model in Power BI?

A semantic model is the business-ready representation of data in Power BI. It includes:

Tables, relationships, and hierarchies
Measures, calculated columns, and KPIs
Data formatting and metadata
Security rules (such as Row-Level Security)

Semantic models are published to the Power BI Service and act as the foundation for reports, dashboards, and analysis.

Access Control Concepts You Must Know

Workspace Roles

Access to semantic models is primarily governed by workspace roles in the Power BI Service:

Role	Capabilities Related to Semantic Models
Viewer	Can view reports and read data (if permitted)
Contributor	Can create and edit content, including reports
Member	Can publish, update, and share semantic models
Admin	Full control, including managing permissions and security

Exam Tip: Viewers cannot create new reports from a semantic model unless Build permission is explicitly granted.

Semantic Model Permissions

Semantic models support item-level permissions, separate from workspace roles.

Key permissions include:

Read – Allows users to view data used in reports
Build – Allows users to create new reports using the semantic model
Reshare – Allows users to share the semantic model with others

These permissions can be assigned to:

Individual users
Security groups
Microsoft Entra ID (Azure AD) groups

Best Practice: Grant access using security groups instead of individual users for scalability and easier management.

Build Permission (Highly Exam-Relevant)

Build permission is one of the most tested concepts in this topic.

With Build permission, users can:

Create new reports using the semantic model
Use the model in Excel (Analyze in Excel)
Use the model via external tools (when allowed)

Without Build permission:

Users can view reports
Users cannot create new reports from the model

Build permission can be granted:

Automatically through workspace role (Member/Admin)
Manually on the semantic model
Via sharing settings

Sharing Semantic Models

Semantic models can be shared in several ways:

Through workspace access
By directly sharing the semantic model
By publishing reports that use the model
Via Power BI Apps

When sharing, you can choose whether recipients:

Can build new content
Can reshare the model
Are restricted by existing security rules

Exam Scenario: A user can view a report but cannot create their own—this often indicates missing Build permission.

Row-Level Security (RLS)

Row-Level Security restricts which rows of data a user can see within a semantic model.

Key RLS concepts:

Roles are defined in Power BI Desktop
DAX filters control row visibility
Users or groups are assigned to roles in the Power BI Service
RLS applies to all reports using the model

Types of RLS:

Static RLS – Fixed filters (e.g., Region = “West”)
Dynamic RLS – Filters based on the logged-in user (e.g., USERPRINCIPALNAME())

Important: RLS is enforced at the semantic model level, not the report level.

Object-Level Security (OLS) (Awareness Level)

While not deeply tested, you should be aware that Object-Level Security can:

Hide tables, columns, or measures from specific users
Be configured using external tools (e.g., Tabular Editor)

OLS complements RLS but is more advanced and typically managed by model developers.

Certified Dataset / Endorsed Semantic Models

To support governance, Power BI allows semantic models to be endorsed:

Promoted – Indicates the model is reliable and ready for reuse
Certified – Officially validated and approved by data owners or admins

Endorsements help users:

Identify trusted data sources
Avoid using unofficial or duplicate models

Exam Tip: Certification requires specific tenant permissions and approval workflows.

Power BI Apps and Semantic Models

When distributing content via a Power BI App:

Access to the semantic model is controlled through the app
Users can be allowed to connect to the underlying semantic model
RLS still applies

Apps provide a controlled, read-only distribution method while maintaining centralized security.

Common Exam Scenarios

You may be asked to determine:

Why a user cannot build a report from an existing model
How to allow self-service reporting without giving full workspace access
How to restrict data visibility for different users
Which permission or role best fits a business requirement

Key Takeaways for the PL-300 Exam

Semantic models are secured through workspace roles and item-level permissions
Build permission is essential for report creation and analysis
Row-Level Security controls data visibility per user
Use groups, not individuals, for scalable access control
Endorsed and certified models support governance and trust
Security is applied at the semantic model level, not per report

Just a FYI … this topic emphasizes balancing self-service analytics with strong data governance, a recurring theme throughout the PL-300 exam.

Practice Questions

Go to the Practice Questions for this topic.

Data Security, BI Administration, Power BI, Microsoft Certification, PL-300 January 17, 2026

Configure Item-Level Access in Power BI (PL-300 Exam Prep)

This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Manage and secure Power BI (15–20%)
   --> Secure and govern Power BI items
      --> Configure Item-Level Access

Note that there are 10 practice questions (with answers and explanations) at the end of each topic. Also, there are 2 practice tests with 60 questions each available on the hub below all the exam topics.

Overview

Item-level access in Power BI controls who can access specific Power BI items—such as reports, dashboards, semantic models (datasets), and apps—and what actions they can perform on those items.

This topic is part of the Manage and secure Power BI (15–20%) exam domain and falls specifically under Secure and govern Power BI items, making it a critical governance concept for PL-300 candidates.

Unlike workspace roles (which define broad permissions across an entire workspace), item-level access allows more granular control over individual Power BI assets.

What Is Item-Level Access?

Item-level access refers to permissions assigned directly to individual Power BI items, independent of workspace roles. These permissions determine whether users can:

View an item
Share an item
Build new content using an item
Reshare or export data
Modify or manage the item

Item-level access is commonly configured for:

Reports
Dashboards
Semantic models (datasets)
Apps (indirectly through audience access)

Why Item-Level Access Matters (Exam Perspective)

From a PL-300 standpoint, item-level access is important because it helps:

Enforce principle of least privilege
Enable self-service BI safely
Separate content creation from content consumption
Support enterprise governance without duplicating workspaces

Expect exam questions that test when to use item-level permissions instead of workspace roles, and how item-level access interacts with security features like RLS.

Configuring Item-Level Access by Item Type

1. Report-Level Access

Reports can be shared directly with users or groups.

Key capabilities:

View report
Share report (optional)
Build new content (if underlying model allows it)

How it’s configured:

Use the Share button on a report
Assign access to users, security groups, or distribution lists

Important exam note:
Sharing a report does not automatically grant access to the underlying semantic model unless explicitly allowed.

2. Dashboard-Level Access

Dashboards are typically shared for executive or summary-level consumption.

Key characteristics:

View-only by default
No data modeling or editing
Tiles link back to underlying reports (which require separate access)

Exam tip:
Users must also have access to the source reports behind dashboard tiles to avoid broken visuals.

3. Semantic Model (Dataset) Item-Level Access

Semantic models support some of the most important item-level permissions.

Key permissions:

Read – view reports using the model
Build – create new reports or analyze in Excel
Reshare – share the dataset with others

Common use case:

Grant Build permission to analysts so they can create their own reports without modifying the dataset.

Exam highlight:
The Build permission is essential for self-service BI scenarios and is frequently tested.

4. App Access (Audience-Based)

Apps use audiences to control item-level visibility.

What audiences allow you to do:

Show different content to different user groups
Hide specific reports or dashboards
Control navigation and access without duplicating content

Best practice:

Use Azure AD security groups for app audiences.

Item-Level Access vs Workspace Roles

Feature	Workspace Roles	Item-Level Access
Scope	Entire workspace	Individual items
Granularity	Coarse	Fine-grained
Best for	Content creators/admins	Consumers & self-service
Exam focus	Governance	Security precision

Key exam takeaway:
Workspace roles control what users can do, while item-level access controls what items they can access.

Item-Level Access and Row-Level Security (RLS)

These two are often confused on the exam.

Item-level access controls access to content
RLS controls data visibility within content

They are complementary, not interchangeable.

Example scenario:

Item-level access → Can the user open the report?
RLS → What rows of data does the user see after opening it?

Best Practices for Configuring Item-Level Access

Use Azure AD security groups instead of individuals
Grant Build permission carefully
Avoid oversharing datasets
Combine item-level access with RLS for data security
Prefer apps and audiences for large-scale distribution

Common Exam Traps to Watch For

Assuming report sharing grants dataset access automatically
Confusing workspace roles with item permissions
Forgetting that dashboard tiles require report access
Overlooking Build permission in self-service scenarios

Summary for PL-300 Exam Readiness

To succeed on PL-300 questions about item-level access, you should be able to:

✔ Identify when item-level access is required
✔ Configure permissions for reports, dashboards, and datasets
✔ Understand Build vs Read permissions
✔ Explain how item-level access differs from workspace roles
✔ Combine item-level access with RLS appropriately

Practice Questions

Go to the Practice Questions for this topic.

BI Administration, Business Intelligence, Data Governance, Data Strategy, Microsoft Certification, PL-300, Power BI January 17, 2026

Configure a Semantic Model Scheduled Refresh (PL-300 Exam Prep)

This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Manage and secure Power BI (15–20%)
   --> Create and manage workspaces and assets
      --> Configure a Semantic Model Scheduled Refresh

Note that there are 10 practice questions (with answers and explanations) at the end of each topic. Also, there are 2 practice tests with 60 questions each available on the hub below all the exam topics.

Overview

A semantic model scheduled refresh ensures that Power BI reports and dashboards display up-to-date data without requiring manual intervention. For the PL-300 exam, this topic focuses on understanding when scheduled refresh is supported, what prerequisites are required, and how to configure refresh settings correctly in the Power BI service.

This skill sits at the intersection of data connectivity, security, and workspace management.

What Is a Semantic Model Scheduled Refresh?

A scheduled refresh automatically reimports data into a Power BI semantic model (dataset) at defined times using the Power BI service. It applies only to Import mode and composite models with imported tables.

Scheduled refresh does not apply to:

DirectQuery-only models
Live connections to Power BI or Analysis Services

Prerequisites for Scheduled Refresh

Before configuring scheduled refresh, the following conditions must be met:

1. Dataset Must Be Published

Scheduled refresh can only be configured after publishing the semantic model to the Power BI service.

2. Valid Data Source Credentials

You must provide and maintain valid credentials for all data sources used in the dataset.

Supported authentication methods vary by source and may include:

OAuth
Basic authentication
Windows authentication
Organizational account

3. Gateway (If Required)

A gateway is required when the semantic model connects to:

On-premises data sources
Data sources in a private network
On-premises dataflows

Cloud-based sources (such as Azure SQL Database or SharePoint Online) do not require a gateway.

4. Import Mode Tables

At least one table in the semantic model must use Import mode. DirectQuery-only models do not support scheduled refresh.

Configuring Scheduled Refresh

Scheduled refresh is configured in the Power BI service, not in Power BI Desktop.

Key Configuration Steps

Navigate to the workspace
Select the semantic model
Open Settings
Configure:
- Data source credentials
- Gateway connection (if applicable)
- Refresh schedule

Refresh Frequency and Limits

Shared Capacity

Up to 8 refreshes per day
Minimum interval of 30 minutes

Premium Capacity

Up to 48 refreshes per day
Shorter refresh intervals supported

These limits are enforced per dataset.

Refresh Options and Settings

Scheduled Refresh

Allows you to define:

Days of the week
Time slots
Time zone
Enable/disable refresh

Refresh Failure Notifications

You can configure email notifications to alert dataset owners if a refresh fails.

Incremental Refresh

Incremental refresh:

Requires Power BI Desktop configuration
Reduces refresh time by refreshing only new or changed data
Still depends on scheduled refresh to execute

Common Causes of Refresh Failure

Expired credentials
Gateway offline or misconfigured
Data source schema changes
Timeout due to large datasets
Unsupported data source authentication

Scenarios Where Scheduled Refresh Is Not Needed

DirectQuery datasets (data is queried live)
Live connections to Analysis Services
Manual refresh and republish workflows (not recommended for production)

Exam-Focused Decision Rules

For the PL-300 exam, remember:

Import mode = scheduled refresh
DirectQuery = no scheduled refresh
On-premises source = gateway required
Refresh settings live in the Power BI service
Premium capacity allows more frequent refreshes

Common Exam Traps

Confusing scheduled refresh with DirectQuery
Assuming all datasets require a gateway
Forgetting credential configuration
Thinking refresh schedules are set in Desktop

Key Takeaways

Scheduled refresh keeps semantic models current
Configuration happens in the Power BI service
Gateways depend on data source location
Capacity affects refresh frequency
Incremental refresh improves performance but still relies on scheduling

Practice Questions

Go to the Practice Questions for this topic.

BI Administration, Data Integration, Microsoft Certification, PL-300, Power BI January 17, 2026

Identify When a Gateway Is Required (PL-300 Exam Prep)

This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Manage and secure Power BI (15–20%)
   --> Create and manage workspaces and assets
      --> Identify When a Gateway Is Required

Note that there are 10 practice questions (with answers and explanations) at the end of each topic. Also, there are 2 practice tests with 60 questions each available on the hub below all the exam topics.

Overview

In Power BI, a data gateway acts as a secure bridge between on-premises data sources and the Power BI service in the cloud. Understanding when a gateway is required—and when it is not—is a core skill assessed in the Manage and secure Power BI section of the PL-300 exam.

This topic focuses less on installing gateways and more on decision-making: recognizing data source locations, connection modes, and refresh requirements.

What Is a Power BI Gateway?

A Power BI gateway is software installed on a local machine or server within a private network. It enables the Power BI service to:

Refresh data from on-premises sources
Query on-premises data in real time (DirectQuery or Live connection)
Maintain secure communication without opening inbound firewall ports

There are two main gateway types:

On-premises data gateway (standard) – supports multiple users and services
On-premises data gateway (personal) – single-user scenarios (limited use, not recommended for enterprise)

When a Gateway Is Required

You must use a gateway when both of the following are true:

The data source is on-premises or in a private network
The Power BI service needs to access the data after publishing

Common Scenarios That Require a Gateway

1. Scheduled Refresh from On-Premises Data

If a dataset connects to:

SQL Server (on-premises)
Oracle, Teradata, SAP
On-premises file shares
On-premises data warehouses

…and you want scheduled refresh, a gateway is required.

2. DirectQuery or Live Connections to On-Premises Sources

A gateway is required for:

DirectQuery to on-premises SQL Server
Live connections to Analysis Services (SSAS) on-premises

This applies even if no refresh schedule exists, because queries are sent at report view time.

3. On-Premises Dataflows

If a Power BI dataflow connects to on-premises data, a gateway is required to refresh the dataflow.

4. Hybrid Scenarios

If a dataset combines:

Cloud data (e.g., Azure SQL Database)
On-premises data (e.g., local SQL Server)

A gateway is still required for the on-premises portion.

When a Gateway Is NOT Required

A gateway is not needed when Power BI can access the data source directly from the cloud.

Common Scenarios That Do NOT Require a Gateway

1. Cloud Data Sources

No gateway is required for:

Azure SQL Database
Azure Synapse Analytics
Azure Data Lake Storage
SharePoint Online
OneDrive
Power BI semantic models
Dataverse
Public web data

2. Import-Only Reports Viewed in Power BI Desktop

While working only in Power BI Desktop, no gateway is needed—even for on-premises data—because Desktop connects directly.

A gateway becomes relevant only after publishing.

3. Manual Refresh in Power BI Desktop

If data refresh happens manually in Desktop and the dataset is republished, no gateway is required (though this is not scalable).

Gateway and Connection Mode Summary

Connection Mode	On-Premises Source	Gateway Required
Import (Scheduled Refresh)	Yes	Yes
Import (Cloud Source)	No	No
DirectQuery	Yes	Yes
Live Connection (SSAS)	Yes	Yes
Dataflows (On-Prem)	Yes	Yes
Desktop-only	Yes	No

Exam-Focused Decision Rules

For the PL-300 exam, remember these rules:

On-premises + Power BI Service = Gateway
Cloud source = No gateway
DirectQuery always needs a gateway if the source is on-premises
Desktop usage alone does not require a gateway
Hybrid datasets still require a gateway

Common Exam Traps

Assuming a gateway is needed for all refresh scenarios
Forgetting that Azure SQL Database does NOT require a gateway
Confusing publishing with refresh
Overlooking gateway needs for dataflows

Key Takeaways

Gateways are about location, not data size
They enable secure, outbound-only communication
The exam tests recognition, not installation steps
Focus on where the data lives and how Power BI accesses it

Practice Questions

Go to the Practice Questions for this topic.

BI Administration, Business Intelligence, Microsoft Certification, PL-300, Power BI January 17, 2026

Configure Subscriptions and Data Alerts in Power BI (PL-300)

This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Manage and secure Power BI (15–20%)
   --> Create and manage workspaces and assets
      --> Configure Subscriptions and Data Alerts

Note that there are 10 practice questions (with answers and explanations) at the end of each topic. Also, there are 2 practice tests with 60 questions each available on the hub below all the exam topics.

Overview

Subscriptions and data alerts in Power BI are notification and monitoring features that help users stay informed about changes in data without actively logging into reports or dashboards. For the PL-300 exam, candidates are expected to understand when to use each feature, how they are configured, their limitations, and how they fit into content distribution and governance.

Power BI Subscriptions

What Is a Subscription?

A subscription sends scheduled email notifications containing a snapshot or link to a report page or dashboard. Subscriptions are designed for passive consumption, allowing users to stay updated on key metrics.

Key Characteristics of Subscriptions

Can be created for:
- Reports
- Report pages
- Dashboards
Delivered via email
Can be scheduled (daily, weekly, etc.)
Can include:
- An image of the visual
- A link to the content
Respect Power BI security and permissions

Types of Subscriptions

Type	Description
User subscription	A user subscribes themselves to content
Subscription for others	Requires appropriate permissions (often via workspace or app)

Requirements and Limitations

Users must have access to the underlying content
Subscriptions do not bypass Row-Level Security (RLS)
Report subscriptions require:
- Content to be hosted in Power BI Service
- Dataset refresh to be functioning correctly
Some advanced features require Power BI Pro or Premium capacity

When to Use Subscriptions (Exam Scenarios)

Executives want regular snapshots of KPIs
Stakeholders prefer email updates over interactive dashboards
Reporting needs are scheduled and predictable

Power BI Data Alerts

What Is a Data Alert?

A data alert notifies users when a numeric value crosses a defined threshold. Alerts are event-driven rather than time-based.

Supported Content for Alerts

Dashboard tiles only
Must display a single numeric value
Examples:
- Card visuals
- KPI tiles
- Gauge tiles

❌ Data alerts cannot be set on report visuals directly.

Alert Triggers

Users can configure alerts based on:

Greater than
Less than
Equal to

Alerts can be delivered via:

Email
Power BI Service notifications

Alert Behavior

Alerts are evaluated after dataset refresh
Alerts trigger only when thresholds are crossed
Can be turned on/off without deleting

When to Use Data Alerts (Exam Scenarios)

Monitoring thresholds (e.g., sales below target)
Detecting operational issues
Requiring immediate action rather than scheduled updates

Subscriptions vs. Data Alerts (PL-300 Favorite Comparison)

Feature	Subscriptions	Data Alerts
Trigger	Schedule-based	Threshold-based
Content	Reports, pages, dashboards	Dashboard tiles only
Purpose	Informational updates	Exception monitoring
Delivery	Email	Email + notifications
Requires dashboard	No	Yes

Permissions and Governance

Users must have view access to subscribe or create alerts
Alerts and subscriptions respect RLS
Workspace admins can control who can:
- Share content
- Create subscriptions for others
Subscriptions support centralized distribution when combined with Power BI apps

Common PL-300 Exam Pitfalls

Assuming alerts work on report visuals ❌
Confusing subscriptions with data-driven alerts ❌
Forgetting that alerts require dashboard tiles ❌
Assuming subscriptions ignore security ❌

Exam Tip Keywords to Watch For

If the question mentions:

“Notify when a value exceeds a threshold” → Data Alert
“Send weekly email updates” → Subscription
“Dashboard tile” → Data Alert
“Passive consumption” → Subscription

Summary

To succeed on the PL-300 exam, you should be able to:

Configure report and dashboard subscriptions
Understand when subscriptions vs. alerts are appropriate
Recognize feature limitations and permissions
Choose the correct solution based on business requirements

Practice Questions

Go to the Practice Questions for this topic.

BI Administration, Business Intelligence, Microsoft Certification, PL-300, Power BI January 17, 2026January 17, 2026

Choose a Distribution Method in Power BI (PL-300 Exam Prep)

This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Manage and secure Power BI (15–20%)
   --> Create and manage workspaces and assets
      --> Choose a Distribution Method in Power BI

Note that there are 10 practice questions (with answers and explanations) at the end of each topic. Also, there are 2 practice tests with 60 questions each available on the hub below all the exam topics.

Overview

Choosing the correct distribution method in Power BI is a key responsibility of a Power BI Data Analyst. It ensures that the right users get the right content, with appropriate access, performance, and governance. On the PL-300 exam, this topic tests your understanding of how and when to distribute content using different Power BI mechanisms, as well as the trade-offs between them.

Distribution decisions typically involve who the audience is, how often content changes, security requirements, and whether self-service or centralized control is preferred.

Common Power BI Distribution Methods

1. Sharing Reports and Dashboards

What it is:
Directly sharing a report or dashboard with users from the Power BI Service.

Key characteristics:

Users must have Power BI licenses
Access can be view-only or allow reshare
Relies on dataset permissions
Simple and quick to implement

When to use:

Small audiences
Ad hoc or informal sharing
Limited governance requirements

PL-300 tip:
Sharing does not automatically grant access to the underlying dataset unless configured.

2. Power BI Apps (Recommended for Most Scenarios)

What it is:
A packaged collection of reports, dashboards, and datasets published from a workspace.

Key characteristics:

Centralized distribution
Supports versioning and updates
Read-only experience for consumers
Strong governance and consistency

When to use:

Large or stable audiences
Enterprise or departmental reporting
Controlled release of certified content

PL-300 tip:
Apps are the preferred distribution method for most production scenarios.

3. Workspace Access

What it is:
Granting users direct access to a workspace with roles such as Viewer, Contributor, or Member.

Key characteristics:

High level of access
Intended for collaboration
Users can see all workspace content

When to use:

Development and collaboration
Analyst or creator teams
Not ideal for business consumers

PL-300 tip:
Workspace access is not a distribution method for broad audiences.

4. Dashboard Subscriptions

What it is:
Scheduled email snapshots of dashboards or reports.

Key characteristics:

Static image or PDF-like view
Delivered on a schedule
Requires access to the content

When to use:

Executives who prefer email
Regular monitoring without logging into Power BI
Supplement to other methods

PL-300 tip:
Subscriptions do not replace apps or sharing for interactive analysis.

5. Embedding (Power BI Embedded / SharePoint / Teams)

What it is:
Integrating Power BI content into other platforms.

Key characteristics:

Seamless user experience
Can leverage existing authentication
Requires planning and licensing considerations

When to use:

Internal portals (SharePoint, Teams)
External applications (Power BI Embedded)
Centralized business platforms

PL-300 tip:
Understand the difference between secure embed and publish to web.

6. Publish to Web (Public Sharing)

What it is:
Making reports publicly accessible via a URL.

Key characteristics:

No authentication required
Data is publicly available
Cannot be secured

When to use:

Public or marketing data only
Non-sensitive datasets

PL-300 tip:
This method is not appropriate for confidential or internal data and is often disabled by organizations.

How to Choose the Right Distribution Method

When answering exam questions, evaluate:

Consideration	Best Fit
Large business audience	Power BI App
Executive KPIs	Dashboard + App
Collaboration	Workspace access
Email delivery	Subscriptions
External application	Power BI Embedded
Public data	Publish to web

Exam-Focused Decision Guidance

Apps > Sharing for governed distribution
Sharing for quick, limited access
Workspaces for creators, not consumers
Publish to web only for non-sensitive data
Subscriptions for passive consumption

If a question mentions enterprise, controlled access, or production deployment, the correct answer is almost always Power BI App.

Key Takeaways

Distribution is about access, security, and user experience
Power BI offers multiple distribution options, each with trade-offs
The PL-300 exam emphasizes choosing the most appropriate method, not just knowing how they work
Apps are the recommended default for most organizational scenarios