Power BI is a powerful business intelligence tool for analyzing data. It allows users to quickly and easily visualize, analyze, and share their data. Power BI is a great tool for discovering insights into your data and helping make better decisions in your business. It is easy to use and provides a wide range of features to help you get the most out of your data.
This tutorial will provide step-by-step instructions on how to use Power BI. We will cover topics such as creating visualizations, connecting to data sources, using the Power Query Editor, and creating dashboards. We will also discuss best practices for setting up and using Power BI. By the end of this tutorial, you should have a good understanding of how to use Power BI to analyze and visualize data.
Audience
Power BI is a powerful business intelligence tool that enables users to easily create interactive visualizations and reports. This tutorial is designed to provide an overview of Power BI and to help users get started with building their own reports and dashboards. The tutorial will cover topics such as creating custom visuals, setting up data sources, developing reports and dashboards, and sharing with others. By the end of the tutorial, users will have a solid understanding of how to use Power BI to create engaging and informative visuals.
Prerequisites
To be successful with this Power BI tutorial, you should have a basic understanding of the following:
1. Database concepts and terminology
2. Basic knowledge of SQL
3. Basic knowledge of Microsoft Excel
4. Understanding of data visualization concepts
5. Familiarity with Microsoft Power BI Desktop
Power BI – Introduction
Power BI is a business intelligence tool developed by Microsoft that enables companies and organizations to visualize data, get insights from the data, and share those insights with others. It provides a powerful suite of software solutions for data analysis, visualization, and reporting. Power BI can be used to analyze data from multiple sources, including Excel, Access, and SQL Server. With Power BI, organizations can quickly and easily create interactive visualizations and data-driven dashboards to gain deeper insights into their data. Additionally, Power BI can be used to create custom applications to help businesses make better decisions.
Power BI – Installation Steps
1. Download the Power BI Desktop installer from the Microsoft website.
2. Run the installer and follow the on-screen instructions to install Power BI Desktop.
3. Once the installation is complete, open the Power BI Desktop application.
4. Create a free Power BI account if you don’t already have one.
5. Sign in to Power BI Desktop with your Power BI account.
6. Connect to data sources from which you can create reports and dashboards.
7. Create and publish reports and dashboards.
8. Share reports and dashboards with other users.
9. Access the Power BI service to view, edit, and analyze reports and dashboards.
Power BI – Architecture
Power BI is an analytics and business intelligence platform developed by Microsoft. It is built on the Azure platform and uses a range of Microsoft technologies, including SQL Server Analysis Services, Power Pivot, and Power Query. Power BI also integrates with other Microsoft products such as Excel, SharePoint, and Office 365.
At its core, Power BI is a data visualization and analytics platform. It provides users with tools to create interactive visuals, dashboards, and reports from their data. It also provides tools to perform data analysis, data cleansing and transformation, and data modeling.
Power BI uses a three-tier architecture. The first tier is the client tier, which is the user interface. The second tier is the server tier, which is responsible for managing data access, query processing, and data storage. The third tier is the data warehouse tier, which stores the data and powers the analytical capabilities.
The Power BI architecture is designed to be highly scalable and secure. It supports multiple users and can scale up to millions of users. It also provides a secure environment for data storage, access, and manipulation.
Power BI – Supported Data Sources
Power BI supports data from a wide range of sources, including files, databases, Hadoop, the cloud, and online services. Some of the most popular sources are:
1. Microsoft Excel
2. Microsoft SQL Server
3. Microsoft Access
4. Oracle Database
5. IBM DB2
6. SAP Business Warehouse
7. SAP HANA
8. MySQL
9. PostgreSQL
10. Teradata
11. Salesforce
12. Google Analytics
13. Microsoft Azure SQL Data Warehouse
14. Microsoft Azure Blob Storage
15. Microsoft Azure HDInsight
16. Microsoft Dynamics CRM
17. SharePoint Lists
18. Web
19. OData
20. HDFS
21. Hive
22. Impala
23. Spark
24. Azure Machine Learning
25. R
26. GitHub
Data sources listed in Power BI desktop
1. Files: Power BI Desktop can connect to a variety of file types including Excel, CSV, text, XML and JSON.
2. Databases: Power BI Desktop can connect to a variety of databases such as SQL Server, Oracle, IBM DB2, MySQL, PostgreSQL, and Access.
3. Online Services: Power BI Desktop can connect to a variety of online services such as Salesforce, Dynamics CRM, Google Analytics, and Microsoft Azure.
4. Analysis Services: Power BI Desktop can connect to Microsoft Analysis Services models to access data.
5. Power BI Service: Power BI Desktop can connect to the Power BI Service, allowing users to access data stored in the cloud.
6. OData Feeds: Power BI Desktop can connect to OData feeds to access data from a variety of sources.
7. SharePoint Lists: Power BI Desktop can connect to SharePoint lists to access data from a variety of sources.
8. Reports and Dashboards: Power BI Desktop can connect to existing reports and dashboards created in Power BI.
Power BI – Comparison with Other BI Tools
Power BI is a business intelligence tool that is gaining popularity due to its cloud-based data visualization and analytics capabilities. While there are many other BI tools in the market, Power BI stands out due to its ease of use and flexibility. It is also cheaper than most of its competitors and allows users to quickly create and publish reports.
When compared to other BI tools, Power BI can provide a more comprehensive view of data through its advanced visualizations and interactive dashboards. It also offers a wider range of data sources and tools for data integration. Additionally, Power BI is integrated with Microsoft Office 365, making it easier to collaborate on reports and dashboards.
Finally, Power BI is a great choice for those looking for a cost-effective BI solution. Its pricing model is based on usage, allowing users to pay only for the features they need. This makes it a great choice for small and medium businesses.
Power BI vs Tableau
Power BI and Tableau are both data visualization and business intelligence tools. Both provide excellent data visualization capabilities and can be used to create interactive dashboards and reports.
Power BI is a cloud-based platform that is easy to use with a clean and intuitive user interface. It provides a wide range of features, including natural language query, advanced analytics, and AI-driven insights. It also offers a wide range of data connectors, allowing users to easily connect to data sources such as SQL, Oracle, and Salesforce.
Tableau is a desktop-based data visualization tool that provides powerful data exploration and analytics capabilities. It offers more advanced features, such as predictive analytics, custom visuals, and a wide range of data connectors. However, it is more expensive and requires more technical expertise to use.
Ultimately, it comes down to the user’s needs and preferences. Those who need a comprehensive data platform that is easy to use and provides a wide range of features may prefer Power BI. Those with more advanced data needs and technical expertise may prefer Tableau.
Power BI vs SSRS
Power BI and SSRS are both Microsoft business intelligence tools. Power BI is a powerful suite of business analytics tools that allow users to visualize and analyze data with greater speed, efficiency, and understanding. It offers a wide range of features, including drag-and-drop visualization tools, interactive dashboards, and AI-powered insights. SSRS, on the other hand, is a platform for creating and managing Microsoft SQL Server reporting services. It is a more traditional BI tool, with features such as report creation, data access, and report delivery.
Power BI is more feature-rich, modern, and user-friendly than SSRS, making it the better choice for most businesses. Additionally, it offers more flexibility and scalability, as well as the ability to create interactive and visually appealing dashboards. However, SSRS is still a viable choice for businesses with legacy systems that are already built on SQL Server.
Power BI – Data Modeling
Data modeling in Power BI is the process of creating a logical structure for the data collected from various data sources. The data model is designed to represent the relationships between the individual data elements, allowing the user to make better decisions from the data. Data modeling helps to organize data in a manner that is easier to understand and analyze. The data model consists of tables and columns that can be used to create relationships between the data. The data model is also used to define the calculations and measures that will be used to analyze the data. Data modeling can be used to identify patterns and trends in the data, as well as to identify outliers and anomalies. Data modeling is an essential part of Power BI, as it allows users to gain more insights from their data.
Using Data Modeling and Navigation
Data modeling is the process of developing a logical representation of data stored in an organization’s databases. It involves the creation of a data model, which is a graphical representation of the data structure and relationships between the data elements. Once the data model is created, it can be used to navigate the data and help to identify the relationships between different data elements. Data navigation involves exploring the data model by moving through the data elements and analyzing the relationships between them. This process helps to understand the data structure and to identify patterns and trends in the data. Data navigation is also used to locate specific information within the data, such as records or values, and to provide insight into the data structure.
Creating Calculated Columns
In Power BI, calculated columns can be created by using the DAX (Data Analysis Expressions) language. To create a calculated column, open the Modeling tab and then select New Column. This will open the Formula Bar, where you can type the DAX expression for the calculated column. Once the formula is entered, click the check mark to create the column.
Creating Calculated Tables
Creating calculated tables in data modeling in Power BI is a process of transforming data from one form to another by using the Power BI Data Modeling tools. Calculated Tables are created by using the DAX language to perform calculations on existing tables in the data model, or by creating new tables from scratch. Calculated tables can be used to add additional information to the data model, to further refine the relationships between tables, or to perform complex calculations such as forecasting and time series analysis.
In order to create a calculated table in Power BI, the user needs to access the data modeling tab in the ribbon and select ‘New Table’. This will open a blank DAX expression editor, where the user can enter the DAX expression to create the calculated table. The user can use the DAX functions and operators to construct the expression and can also use existing tables and columns in the data model to make the calculations. Once the expression is completed, the user can save the table and it will appear in the data model.
Calculated tables can be used for a variety of purposes, including joining tables together, performing calculations on existing columns, and creating new columns with values derived from existing columns. Calculated tables are an important part of data modeling in Power BI and can help to improve the accuracy and reliability of the data model.
Managing Time-Based Data
Managing time-based data in Power BI can be achieved by using the Time Intelligence feature. This feature allows users to analyze and visualize time-based data over different periods and intervals. Users can also compare data across different timeframes, such as year-over-year or month-over-month. The Time Intelligence feature also supports the use of dynamic date functions that can automatically adjust date ranges based on the most current data available. Additionally, users can create visuals and reports that show data from different perspectives, such as cumulative or rolling averages. Finally, users can use the Time Intelligence feature to compare data from different years and create custom date ranges to further refine their analysis.
Power BI – Dashboard Options
1. Standard Dashboard: This type of dashboard is used to display visualizations such as tables, charts, and graphs. It can be used to quickly gain an overview of data and to identify trends, patterns, and outliers.
2. KPI Dashboard: This type of dashboard is used to measure and track key performance indicators (KPIs). It typically includes charts, gauges, and other visualizations that allow users to quickly assess the status of the KPIs.
3. Analytical Dashboard: This type of dashboard is used to slice and dice data to uncover deeper insights. It typically includes interactive visualizations that allow users to explore and analyze data in more detail.
4. Storytelling Dashboard: This type of dashboard is used to tell a story about the data. It typically includes several visualizations that are organized in a way that allows users to gain insight into the data and to identify relationships between different data points.
Power BI – Visualization Options
Power BI has a variety of visualization options available. These include:
• Bar Chart: A bar chart is a graphical representation of data where the length of each bar is proportional to the value it represents. It’s a great way to compare values and identify trends.
• Line Chart: A line chart is a type of chart which displays information as a series of data points connected by straight lines. It can be used to compare and contrast data across multiple categories.
• Pie Chart: A pie chart is a circular graph that is divided into slices representing the relative proportions of each value in the data set. It can be used to compare relative proportions of different values.
• Scatter Plot: A scatter plot is a type of chart which displays data as points on a two-dimensional graph. It can be used to visualize the relationship between two variables.
• Map: A map is a visualization that displays geographic data in a two-dimensional format. It can be used to visualize relationships between geographical locations and other data points.
• Bubble Chart: A bubble chart is a type of chart which displays data as points with varying sizes. It can be used to visualize the relationship between three variables.
• Pivot Table: A pivot table is a type of table which displays data in a grid format. It can be used to quickly summarize and analyze data.
Creating Simple Visualizations
Power BI is a data visualization tool that enables users to easily create and share interactive visualizations. It is a powerful tool for quickly transforming raw data into meaningful insights. Power BI enables users to create simple visualizations from a variety of data sources, including Excel spreadsheets, databases, and web services.
To create a simple visualization in Power BI, first you need to connect to a data source. Depending on the nature of the data source, this can be done using either Excel or a web service. Once connected, the data can be explored using the Power BI desktop.
For simple visualizations, Power BI offers a range of graphs and charts, including bar charts, line graphs, scatter plots, and pie charts. To create a chart, simply select the required data fields and then click ‘visualize’. This will open a chart window with options to customize the type of chart, the data labels, and the color palette.
The Power BI interface also offers a range of advanced features that enable users to create more complex visualizations. For example, users can add interactive elements such as filters and slicers to make their visualizations more dynamic and interactive. Additionally, users can also add custom calculated fields and use Power BI’s data modeling capabilities to transform and combine data from different sources.
Power BI also offers the ability to share visualizations with others. Visualizations can be published to the web or embedded in other applications. Additionally, users can create dashboards to monitor and track changes in their data over time.
Power BI is a powerful tool for quickly transforming raw data into meaningful insights. With its easy to use interface and range of features, Power BI enables users to create simple visualizations from a variety of data sources. By leveraging the power of Power BI, users can quickly create and share interactive visualizations for quickly gaining insights from their data.
Creating Map Visualizations
1. Select the Visualizations tab in the top right corner of Power BI.
2. Select the Map visual from the list of visuals.
3. Choose the data fields you want to map.
4. Select a color scheme and other map settings.
5. Click the play button to preview your map visual.
6. Use the formatting pane to customize the look and feel of your map.
7. If needed, use the drill down and zoom features to focus on specific areas.
8. Save and share your map visual with others.
Using Combination Charts
In data visualization, combination charts are charts that combine two or more chart types to make the data easier to understand. Combination charts are especially useful when comparing different types of data, such as a combination of a line chart and a bar chart. Combination charts can also be used to display multiple trends or data points within the same chart. For example, a combination chart may be used to compare sales performance over time and also show the number of sales each month. Combination charts can also be used to show the relationship between two or more variables such as the relationship between sales and customer satisfaction. Combination charts can also be used to compare data from different sources, such as sales performance between different regions or countries. Combination charts are an effective way to present complex data in a clear and concise manner.
Using Tables
Tables are a great way to present data in Power BI, and they are easy to create and use. Tables are made up of columns and rows, and they can be used to present both numerical and descriptive data. Tables can be used to display information in a variety of different ways, such as comparing different categories or displaying a timeline of events. Tables can also be used to create visualizations such as bar charts, line graphs, and scatter plots. Tables are a great way to organize and present data, and they can help make data analysis easier and more efficient.
Modify Colors in Charts
In Power BI, you can modify colors in charts by selecting the Color tab in the Visualizations pane. There you can select a color palette or customize the colors in the chart by selecting a color for a specific data point or chart element. You can also modify the color transparency, or even select a different color for each category in the chart.
Adding Shapes, Images and Text box
To add shapes, images, and text boxes to your Power BI report, first select the “Insert” tab at the top of the report. From there, click the “Shapes”, “Images”, or “Text Box” button to insert the corresponding item into your report. You will then be able to resize, move, and customize the shape, image, or text box in the report.
Styling Reports
Power BI offers a number of tools for styling reports. You can customize the appearance of your report in a variety of ways, including changing colors, fonts, and the layout of visualizations. You can also add images, logos, and backgrounds to your report to enhance its visual appeal. Additionally, there are a variety of tools for styling charts and other visualizations, such as axis labels, data labels, and trend lines. Finally, you can add annotations and other text boxes to your report to help convey important messages.
Duplicating Reports
Duplicating reports in Power BI is a simple process.
1. Open the Power BI Desktop application and select the report you want to duplicate.
2. Click the “File” menu and select “Save As.”
3. Name the report and select a location to save it.
4. Click “Save.”
The new report will now be available in the list of reports in Power BI Desktop.
Power BI – Excel Integration
Power BI and Excel can be integrated in several ways. One of the most common ways to integrate them is through the Power BI Desktop application. This allows users to connect their Excel data to Power BI so that they can use the data in their Power BI reports. Additionally, users can use Power Query to connect and import data from Excel into Power BI. This allows users to easily access and analyze their Excel data in Power BI. Lastly, users can also use Power BI to create and manage dashboards, charts, and visuals based on Excel data.
Using Excel Data
Excel data can be used in Power BI in several different ways. The most common method is to connect to an Excel workbook that contains the data. To do this, select “Get Data” from the ribbon and select “Files” from the Get Data dialog. Select “Excel” from the list of file types and then select the file that contains the data. Power BI will then read the Excel workbook and import the data into the Power BI report.
Once the data is imported into Power BI, it can be used in various ways. The data can be used to create visuals, such as charts and graphs, to analyze the data and find trends. The data can also be used to create interactive dashboards that allow users to explore and interact with the data. Finally, the data can be used in Power BI reports or Power BI datasets to combine multiple data sources and create more complex data visualizations.
Importing xls Files
Power BI makes it easy to import Excel files into the platform. To do so, open Power BI and select the Get Data option from the Home menu. Select the Excel option from the list of data sources. Then, select the file you wish to import. You can also select multiple files at once by selecting the ‘Combine & Transform Data’ option. The data will then be imported into the Power BI platform.
Sharing Power BI Dashboards
To share Power BI Dashboards, click the File tab, then click the Share button. You can then choose to share the dashboard with specific people, or to create a link that can be shared with anyone. You can also restrict the dashboard to certain users or groups.
Using Power BI Desktop for Report Sharing
Power BI Desktop is a powerful reporting solution that is used to create engaging visualizations and share insights with colleagues and partners. It allows users to create interactive reports and dashboards that can be shared with others. The reports can be exported to various formats such as PDF, PowerPoint, and Excel. Additionally, Power BI Desktop includes features such as data exploration, natural language queries, and automated data refresh. This makes it easy to create visually appealing reports that can be easily shared with others.
Printing Power BI Dashboards
Power BI dashboards can be printed by using the browser print command. To do this, go to the dashboard you wish to print and press Ctrl + P (Windows) or Cmd + P (Mac) on your keyboard. This will open up the browser print menu, where you can select the printer and other printing options. After you have selected your options, click the Print button to print the dashboard.
Publishing Report to Web
Power BI provides a feature that allows users to publish their reports to the web. This feature allows users to share their reports with other users without requiring them to have a Power BI account. Reports published to the web are also accessible from any device, including mobile devices.
To publish a report to the web, open the report in Power BI. Select the File menu, and then select Publish to the web. On the Publish to the web pane, choose the Publish button.
Once the report is published, a URL is generated. This URL can be copied and shared with other users. When the recipient clicks the link, the report will open in a browser window.
In addition to publishing reports to the web, users can also embed reports in webpages. This allows users to embed reports in blogs, websites, or other webpages. To embed a report, select the File menu and then select Embed report. On the Embed report pane, choose the Generate code button. This will generate a code snippet that can be copied and pasted into a webpage.
Publishing and embedding reports to the web provides a great way to share Power BI content with others. Reports can be accessed from any device, allowing users to easily stay up to date with their data.
Using Content Pack
1. Open Power BI and go to the Home tab.
2. Select Get Data and select the Content Pack option.
3. Select the Content Pack you want to use, either from the list of available packs or by typing in the name.
4. Once the Content Pack is selected, Power BI will prompt you to enter the credentials to access the data. Enter the credentials and click Connect.
5. After the connection is established, Power BI will display the data in the report canvas.
6. The data can now be used to create visuals, reports, and dashboards.
Editing Content Pack in Power Bi
1. Open Power BI Desktop.
2. From the Welcome Screen, select the Get Data option.
3. Select the Content Packs option from the left-hand side menu.
4. Select the content pack you would like to edit.
5. Select the Edit option from the top menu bar.
6. Make changes to the data or visuals within the content pack.
7. Once you are done making your changes, select the Save button to save them.
8. Select the Publish button to upload your changes.
9. Enter any additional information, such as a description of your changes, and select Publish.
10. Your changes will now be available to other Power BI users.
DAX Basics in Power BI
DAX Basics in Power BI is a comprehensive introduction to Data Analysis Expressions (DAX) language in Power BI. DAX is a powerful language that enables users to create complex calculations, perform dynamic data analysis, and generate meaningful insights from their data. This course introduces the basics of DAX, including expression syntax, functions, and data types. It covers the fundamentals of working with tables and columns in DAX, as well as how to perform calculations in Power BI. Additionally, it explores how to create complex visualizations with DAX and how to apply DAX to various scenarios. Finally, the course provides an overview of best practices for working with DAX and troubleshooting common errors.
DAX Introduction
DAX (Data Analysis Expressions) is a language used by Power BI, PowerPivot and Analysis Services Tabular to define calculations used in Power BI reports and PowerPivot workbooks. It is a library of functions and operators that can be combined to build formulas and expressions that manipulate data and calculate values. DAX includes functions for working with related tables, iterating calculations, manipulating text, and more advanced functions for statistical analysis and data mining. DAX is based on the Excel formula language and is designed to help users create and analyze data models in a variety of ways.
DAX Functions
DAX functions are used to perform calculations on data stored in a data model in Power BI and other applications. Common functions include statistical functions, mathematical functions, financial functions, and text functions. Examples include COUNT, SUM, AVERAGE, MAX, MIN, DATEDIFF, DATEADD, and CONCATENATE. These functions can be used in combination with other functions, such as IF and SWITCH, to create powerful formulas and calculations.
DAX Functions
1. SUM: The SUM function is used to add up all of the numeric values in a column or set of columns.
2. COUNT: The COUNT function is used to count the number of rows in a table that contain a specific value or expression.
3. AVERAGE: The AVERAGE function is used to calculate the average of all of the numeric values in a column or set of columns.
4. MAX: The MAX function is used to find the maximum value in a column or set of columns.
5. MIN: The MIN function is used to find the minimum value in a column or set of columns.
6. RANKX: The RANKX function is used to rank a value in a table.
7. FILTER: The FILTER function is used to filter a table based on a set of criteria.
8. RELATEDTABLE: The RELATEDTABLE function is used to return a table of related records from a related table.
9. CALCULATE: The CALCULATE function is used to modify the filter context of a measure or calculation.
10. DISTINCTCOUNT: The DISTINCTCOUNT function is used to count the number of distinct values in a column or set of columns.
DAX Calculation Types
1. Simple Moving Average (SMA): The Simple Moving Average is calculated by taking the average of a given set of data points over a specific period of time (usually a few days).
2. Weighted Moving Average (WMA): The Weighted Moving Average is a type of moving average that gives more weight to recent data points than older ones. This is done by adjusting the weighting factor for each data point.
3. Exponential Moving Average (EMA): The Exponential Moving Average is a type of moving average that gives more weight to recent data points than older ones, but the weighting factor is adjusted exponentially.
4. Time Series Forecasting: Time Series Forecasting is the process of using historical data to predict future trends. It can be used to forecast short-term or long-term market trends.
5. Correlation Analysis: Correlation Analysis is a statistical technique used to measure the strength and direction of a relationship between two variables. It can be used to identify relationships between different stocks or index components.
6. Volatility Analysis: Volatility Analysis is a technique used to measure the amount of risk associated with a given security or market. It is calculated by measuring the standard deviation of the price movements of a security or market over a period of time.
7. Technical Analysis: Technical Analysis is a form of analysis that uses charts and other technical indicators to identify and interpret trends in the market. It can be used to identify support and resistance levels, as well as overbought and oversold conditions.
Power BI – Administration Role
The Power BI Administration role is responsible for the deployment, maintenance, and support of the Power BI platform. This role is typically held by a Power BI administrator, who is responsible for managing the implementation and ongoing maintenance of the Power BI platform. The administrator is also responsible for managing user access to the platform and ensuring that the platform is secure and compliant with the organization’s security policies. The administrator is also responsible for providing training and support to users, as well as developing and deploying custom reports and dashboards.
REST API
Power BI REST APIs allow users to manage content and access data in the Power BI service. The Power BI REST API provides programmatic access to dashboard, dataset, and other resources. The API also allows users to manage access to their dashboards, datasets, and other resources, as well as query data from their Power BI dashboards. The API is based on Representational State Transfer (REST) principles and uses OAuth 2.0 for authentication and authorization. With the API, users can create, retrieve, update, and delete dashboards, datasets, and other resources.
Security In Power BI
Security in Power BI is provided in multiple layers and can be tailored to meet an organization’s security requirements. These layers include authentication and authorization, data privacy and encryption, data masking, and data governance.
Authentication and Authorization: Power BI offers various authentication methods, such as Azure Active Directory (AAD), Microsoft Account, and Organizational Accounts. These authentication methods enable users to securely access their Power BI content and resources. Authorization is used to control user access to Power BI content. This includes setting up roles and permissions for managing data access and restricting user access to sensitive data.
Data Privacy and Encryption: Power BI provides data privacy and encryption features to protect data from unauthorized access. This includes using Transport Layer Security (TLS), encryption at rest, and data-level encryption.
Data Masking: Power BI offers data masking features to help protect sensitive data from unauthorized access. This includes hiding data from users who are not authorized to view it, and masking data for users who are not authorized to view it in full.
Data Governance: Power BI provides data governance features to help ensure the accuracy and quality of data. This includes setting up data quality rules, creating data policies, and monitoring data usage.