ExamTopics

The Power BI certification (PL-300) is a popular choice for professionals looking to prove their proficiency in data analysis and visualization with Microsoft Power BI. In preparing for this exam, understanding which topics are tested most frequently can make a huge difference. After analyzing several exam question sets and categorizing them by topic areas, 

Most Commonly Tested Topics in the PL-300 Exam

The PL-300 exam covers a wide range of skills, but some topics consistently appear more frequently. Below, we’ll take a deeper dive into these core areas:

1. Data Modeling and DAX Functions:

Data modeling is arguably the heart of Power BI. It’s not just about creating reports; it’s about creating a solid, well-structured data model that ensures the accuracy and efficiency of your analysis. During my research, I noticed that many questions focus on the intricacies of DAX (Data Analysis Expressions) and data modeling best practices. DAX is essential, and if you don’t devote a solid amount of time to mastering it, the exam will likely be challenging.

• DAX Formula Functions: These functions are crucial for creating calculated columns, measures, and even tables. Understanding the syntax, how to use these functions in real-world scenarios, and how to debug them will prepare you well for the exam. 
• Modeling Relationships: Understanding the different types of relationships (one-to-one, one-to-many, etc.) and when to use them is also heavily emphasized. Make sure you understand the practical application of these relationships in your model. 

2. Power Query and Data Transformation:

The Power Query Editor allows users to clean and transform data before it even gets loaded into the Power BI model. Power Query functions, like Unpivot, Merge, and Append, are key to preparing your data. Based on my analysis, these transformations show up frequently in the PL-300 exam, as they are vital to ensure the accuracy and quality of data coming into your reports.

• Power Query Functions: Knowing how to transform and clean data with Power Query functions is essential for building high-quality reports. The Unpivot function, for example, is particularly crucial when dealing with data that’s stored in a cross-tab or pivoted format. 

3. Performance and Efficiency:

Performance is often overlooked, but it’s an important aspect of Power BI. Slow reports can cause frustration for end-users and diminish the usefulness of a tool that is meant to make data analysis faster and more accessible. Optimizing reports, queries, and models will not only ensure your exam readiness but also make you a better practitioner in the field.

• Optimizing DAX and Queries: Knowing how to optimize DAX measures and Power Query steps to ensure reports run efficiently is an important skill that is also tested. Key areas to focus on include query folding, the use of variables in DAX, and minimizing the use of complex calculated columns. 

4. Visualizations and Dashboards:

Dashboards and visualizations are key outputs in Power BI, but from my analysis, they seem to be less emphasized compared to other areas. While it’s important to know how to create clear and effective visualizations, the exam tends to focus more on ensuring data is prepared and modeled properly before diving into visualization.

• Visual Best Practices: Understand which visualizations are best suited for different data types and what makes them effective in conveying insights. Be familiar with different chart types, slicers, and how to interact with visuals on the report canvas. 

 Mastering Power BI’s Core Features for the PL-300 Exam

Power BI is a powerful business intelligence tool, and the PL-300 certification exam tests your ability to utilize it effectively for data analysis and reporting. To excel in the PL-300, you must understand the fundamentals of data modeling, transformation, DAX, visualizations, and performance optimization.

Data Modeling in Power BI: A Crucial Skill for Success

The foundation of any Power BI report is a well-structured data model. In the PL-300 exam, you will encounter questions related to designing and managing data models that ensure your reports are accurate, efficient, and scalable. Here’s what you need to know about Power BI data modeling:

Building a Solid Data Model

When creating a data model in Power BI, the goal is to structure your data so that it can be queried easily and efficiently. Power BI uses tables to represent data, and these tables can be linked together using relationships. Properly designing relationships between tables is critical to ensure your reports and dashboards reflect the intended insights.

One of the most effective ways to build a Power BI data model is by using the star schema. This design separates fact tables, which contain transactional data, from dimension tables, which store descriptive data. For example, a Sales fact table might include columns for Product ID, Quantity Sold, and Sales Amount, while a Product dimension table could store Product Name, Category, and Manufacturer.

Types of Relationships

In Power BI, relationships define how tables are connected. The most common types are one-to-many and many-to-one relationships. Understanding how to set up these relationships and how they affect filtering and query behavior is crucial for exam success.

One-to-many relationships are used when one record in a dimension table corresponds to multiple records in a fact table. For example, one product can appear in many sales transactions. When defining relationships, it’s important to determine the cardinality (i.e., the number of distinct values in a column) and cross-filtering direction. These factors impact how data flows between tables.

Handling Complex Data Models

As data models grow in complexity, it becomes important to manage them efficiently. Power BI allows you to define calculated tables and columns using DAX (Data Analysis Expressions), which lets you extend the functionality of your model. In the exam, expect questions related to creating calculated columns and using DAX to implement custom business logic.

Mastering Power Query for Data Transformation

The ability to transform and clean data is another key skill for passing the PL-300 exam. Power Query is Power BI’s built-in tool for data extraction, transformation, and loading (ETL). This tool allows you to clean, shape, and structure data before it’s loaded into your data model. You will likely encounter several questions on the exam about working with Power Query to manipulate data.

Using Power Query to Clean Data

Power Query provides a wide range of transformation options, from basic tasks like renaming columns and removing duplicates, to more advanced operations like pivoting, unpivoting, and merging tables. One of the most useful transformations you will need to understand is unpivoting. This operation is often required when your data is stored in a pivoted format (e.g., sales data in a table where each column represents a different month), and you need to convert it into a more usable form.

For example, to unpivot sales data, you would select the columns containing months and apply the unpivot transformation. This creates a new column for each of the months and associates each sales value with the corresponding month and product. Understanding how to use Power Query transformations efficiently is critical for ensuring your data is clean and ready for analysis.

Merging and Appending Queries

Another important Power Query skill is merging and appending queries. Merging allows you to combine data from two or more tables based on a common column, while appending lets you stack multiple datasets with the same structure. For example, if you have sales data stored in separate monthly files, you can append them into a single table for easier analysis.

Both operations are fundamental to working with data from multiple sources, and you will likely encounter these types of tasks on the exam. Understanding when and how to apply them is crucial for working with large datasets and ensuring that your reports are based on accurate, complete information.

Data Analysis Expressions (DAX): The Heart of Power BI Calculations

Once your data model is in place, DAX (Data Analysis Expressions) comes into play for creating calculated columns, measures, and tables. DAX is a formula language used to define calculations that add business value to your reports. Mastering DAX is one of the most challenging, yet rewarding, aspects of preparing for the PL-300 exam.

Creating Calculated Columns and Measures

DAX allows you to create both calculated columns and measures, each serving different purposes. A calculated column is a new column added to your data model, and its values are calculated row by row based on a formula you define. Measures, on the other hand, are calculations that are performed at the aggregate level and are used in reports and visuals.

For example, a calculated column might be used to calculate the profit margin for each sale, while a measure could calculate the total sales for a given period. Understanding the difference between the two and knowing when to use each is essential for success on the exam.

Common DAX Functions

Some of the most important DAX functions that you need to know for the PL-300 exam include:

• SUMX: This function allows you to iterate over a table and sum the values based on a specified expression. It’s useful when you need to perform calculations over rows or perform complex aggregations. 
• CALCULATE: One of the most powerful DAX functions, CALCULATE allows you to modify the filter context of a measure and apply additional conditions. It’s frequently used to create time-based calculations, such as year-over-year growth. 
• FILTER: The FILTER function allows you to create dynamic filters in your DAX formulas. You can use it to filter a table based on specific conditions and return a subset of data for analysis. 
• RELATED: This function is used to retrieve values from related tables in your data model. It’s often used when you need to look up a value from a different table and include it in a measure or calculated column. 

Time Intelligence in DAX

Time-based calculations are common in business scenarios, and Power BI provides a set of Time Intelligence functions to simplify this process. These functions allow you to calculate Year-to-Date (YTD), Month-to-Date (MTD), and Quarter-to-Date (QTD) values. Understanding how to create and work with these time-based calculations is crucial for exam success.

For example, to calculate YTD sales, you would use the DAX function TOTALYTD, which aggregates sales from the beginning of the year to the current date.

Visualizing Data in Power BI: Best Practices and Design Tips

Once your data is modeled and transformed, it’s time to visualize it. Power BI offers a wide range of visualization options, from basic bar and line charts to more advanced visualizations like maps and tree maps. As a PL-300 candidate, you must be able to select the appropriate visualization for different data types and business scenarios.

Choosing the Right Visual

Selecting the right type of visualization is critical to effectively communicating insights. For example, a line chart is ideal for showing trends over time, while a bar chart can be used to compare different categories. A pie chart is useful for displaying proportions, but it’s best to avoid using it when there are many categories, as it can become difficult to interpret.

Power BI also offers a range of advanced visualizations, including scatter plots, waterfall charts, and heat maps. Understanding when to use each visualization and how to interpret the results will help you create reports that provide valuable insights.

Interactivity with Slicers and Filters

Interactivity is a key feature of Power BI. Using slicers and filters, you can allow report users to dynamically interact with the data. Slicers are often used to filter data by dimensions like Product Category or Date, while filters can be applied at the visual, page, or report level.

It’s important to understand how slicers and filters interact with each other and how to set them up for optimal user experience. On the PL-300 exam, you may be asked to configure slicers and filters to create dynamic, user-driven reports.

Optimizing Power BI Reports for Performance

Creating beautiful and insightful reports is one thing, but ensuring they perform well is another. Optimizing the performance of your Power BI reports is essential for providing a smooth user experience, especially when working with large datasets.

Reducing the Size of Data Models

Large data models can slow down report performance. One way to optimize your model is by removing unnecessary columns or reducing the granularity of the data. Additionally, using query folding (where transformations are pushed back to the data source) can significantly improve performance.

Efficient DAX Queries

Writing efficient DAX queries is crucial for improving report performance. Avoid using complex row-by-row calculations and iterators like SUMX when possible, as they can increase the computational cost of your measures.

Advanced Techniques and Best Practices for Power BI Exam Success

The PL-300 exam tests more than just basic Power BI knowledge; it also examines your ability to apply advanced techniques and best practices. Whether you’re preparing to optimize your reports, automate data refreshes, or build complex data models, mastering these advanced topics will give you the edge you need to succeed on the exam

Managing and Optimizing Data Refreshes in Power BI

One of the challenges in working with Power BI, especially in a professional setting, is ensuring that your reports are updated with the latest data. For the PL-300 exam, you’ll need to understand how to manage data refreshes and optimize their performance.

Understanding Data Refresh Types

There are several types of data refreshes in Power BI:

• Manual Refresh: A manual refresh is initiated by the user. It is typically used for small datasets or during the development phase of a report. 
• Scheduled Refresh: This is the most common type of refresh. You can set up scheduled refreshes to run at specified times or intervals, ensuring that the data in your reports is up-to-date without manual intervention. 
• DirectQuery and Live Connections: Instead of importing data into Power BI, you can use DirectQuery or Live Connections to query the data source in real-time. This approach ensures that your reports always reflect the latest data, but can sometimes lead to slower performance if the underlying data source is not optimized. 

Configuring and Monitoring Refreshes

In the PL-300 exam, you may be tested on how to set up and manage scheduled refreshes. In Power BI, you can configure data refresh settings within the Power BI Service. The key to managing refreshes efficiently is to monitor the refresh history for any failures and to resolve issues promptly. Power BI offers the option to receive email notifications if a scheduled refresh fails, allowing you to quickly address any issues.

For advanced refresh scenarios, you may also need to leverage incremental refresh, which updates only the data that has changed since the last refresh. This is especially useful when working with large datasets, as it reduces the time and resources needed for refresh operations.

Using Power BI Templates and Deployment Pipelines

In Power BI, templates and deployment pipelines are powerful tools for automating the report creation and deployment process. They help streamline the workflow, making it easier to manage and distribute reports across different environments.

Power BI Templates

A Power BI template (.pbit file) is a report file that includes the structure of a report, along with queries, relationships, and visualizations, but without the actual data. Templates are useful when you want to reuse a report design across multiple workspaces or clients. They allow you to standardize reporting and speed up the deployment process.

To create a template, you simply save your report as a template file, and when you open the template, it prompts you to connect to a data source. This ensures that your report can be reused and adapted to different datasets.

Deployment Pipelines

Power BI deployment pipelines allow you to manage the lifecycle of a report, from development to testing to production. You can move content from one stage of the pipeline to another, ensuring that changes are tested before they’re pushed to end-users. This is particularly useful in large organizations where multiple teams are working on the same Power BI reports.

In the exam, you may encounter questions about deploying reports to different environments and ensuring that best practices are followed for version control and testing.

Data Security and Row-Level Security (RLS)

Security is a critical aspect of any reporting tool, and Power BI provides several features to control who can access specific data within reports. For the PL-300 exam, understanding Row-Level Security (RLS) and how to implement it in Power BI is crucial.

Implementing Row-Level Security

Row-Level Security (RLS) allows you to restrict access to specific rows of data based on the user’s role. For example, in a sales report, a regional manager may only be able to view sales data for their specific region, while the sales director can view data for all regions.

To implement RLS, you create security roles within Power BI Desktop and then define DAX filters for those roles. When users access the report in the Power BI Service, they will only see the data that their role allows them to view.

For example, you might define a DAX expression that filters the Region column based on the user’s identity.This ensures that users only see data relevant to their role or geographic location. Understanding how to configure RLS is important for both exam success and ensuring that your reports are secure in real-world applications.

Testing and Managing RLS

Once RLS is implemented, you must test it to ensure that it’s working as expected. Power BI allows you to test RLS by using the “View as Role” feature, which simulates the report experience for a specific role. This helps you verify that the security settings are applied correctly before deploying the report to users.

Power BI Service: Sharing, Collaborating, and Publishing Reports

While Power BI Desktop is where the report creation happens, the Power BI Service is where collaboration, sharing, and publishing take place. Understanding how to use the Power BI Service effectively is essential for the PL-300 exam, as many exam questions will focus on tasks related to report sharing and collaboration.

Sharing Reports and Dashboards

In Power BI, you can share reports and dashboards with other users within your organization. This is done by publishing the reports to the Power BI Service and using the Share feature. You can grant users access to the report either via email or by sharing a link.

Power BI also allows you to control what users can do with the report. For example, you can allow users to view the report, interact with the visuals, or even export the data. Understanding these sharing options and when to use them is key to passing the exam.

Collaborating in Workspaces

Power BI Workspaces allow teams to collaborate on reports and dashboards. In the Power BI Service, workspaces are used to organize content and manage access. A workspace can be shared with multiple users, allowing them to collaborate on reports, datasets, and dashboards. As a Power BI admin or report developer, you’ll need to manage workspace access and ensure that only the right people have editing or viewing privileges.

There are also app workspaces in Power BI, which are typically used for deploying content to end-users. Apps allow users to access a curated set of reports and dashboards without being able to edit the underlying content.

Publishing to Web and Embedding

For sharing reports externally, you can use the Publish to Web feature in Power BI. This creates a public URL that can be shared on websites or social media platforms. However, this method should only be used for non-sensitive data, as it makes the report publicly accessible.

For embedding reports within other applications or websites, Power BI provides options like Power BI Embedded and Power BI for Apps. These options allow organizations to integrate Power BI reports seamlessly into their own apps, with custom branding and user access management.

Power BI Performance Optimization: Best Practices

Power BI performance is an important consideration when working with large datasets or complex reports. Slow report performance can lead to frustration among users and hinder data-driven decision-making. For the PL-300 exam, it’s important to know how to optimize your Power BI reports for faster load times and smoother interactions.

Optimizing Data Models for Performance

The first step in optimizing Power BI performance is to focus on the data model. A well-designed data model can greatly improve report speed and responsiveness. Key steps for optimizing data models include:

• Reducing data load: Only load the data you need for the report. Remove unnecessary columns and rows, and filter data during the query process. 
• Choosing the right data types: Use appropriate data types for each column to minimize storage and processing requirements. For example, use Integer instead of Decimal when possible. 
• Minimizing calculated columns: While calculated columns are useful for adding custom business logic, they can also slow down performance if used excessively. Whenever possible, try to replace calculated columns with measures. 

Improving DAX Query Performance

DAX queries can become slow when dealing with large datasets or complex calculations. To improve DAX performance:

• Use variables: Using variables within DAX expressions can help reduce the need for repetitive calculations and make queries more efficient. 
• Avoid using complex iterators: Functions like SUMX and FILTER can be computationally expensive. Where possible, try to simplify the logic or use other methods to perform the calculation. 

Query Folding and DirectQuery

Query folding is a process where Power Query pushes transformations back to the data source, allowing the data source to handle the computations rather than Power BI. This can significantly improve performance. However, not all data sources support query folding, so it’s important to check the compatibility of your data source.

For real-time reporting with large datasets, consider using DirectQuery mode, which queries the data source directly without importing it into Power BI. This can improve performance but may come with some limitations in terms of features and interactivity.

Final Tips and Advanced Best Practices for Power BI Certification

As you approach the final stage of your preparation for the PL-300 exam, it’s crucial to solidify your understanding of Power BI’s advanced features and capabilities. 

Designing Effective Reports and Dashboards for End Users

The PL-300 exam not only tests your technical skills but also evaluates how well you can apply those skills to design reports and dashboards that provide actionable insights. Effective report design is about more than just creating visually appealing charts—it’s about making data accessible and understandable for decision-makers.

Understanding User Needs and Business Requirements

Before you even start building a report or dashboard, it’s essential to understand the needs of the end users. Every organization has different goals, and the data you present should be aligned with those goals. For instance, a financial manager might be interested in profit and loss statements, while a sales manager might focus on customer segmentation and sales performance metrics.

You must learn how to gather these requirements by interviewing stakeholders and understanding the key performance indicators (KPIs) that matter most to them. This step is crucial for ensuring that your reports are relevant and that they provide the insights needed to drive business decisions.

Keeping Reports Simple and Focused

Once you’ve gathered the requirements, simplicity becomes a key principle in report design. Complex reports with too many visuals can overwhelm users, making it difficult for them to extract meaningful insights. Instead, focus on a clean, minimalist design that highlights the key metrics and visualizations necessary for decision-making.

Here are some design tips that will help improve the effectiveness of your Power BI reports:

• Prioritize key metrics: Make sure your most important KPIs are front and center. Use larger visuals or cards to make them stand out. 
• Limit the number of visuals: Don’t overcrowd the report with unnecessary visuals. Use a maximum of three to five key visuals per page. 
• Consistent formatting: Ensure that fonts, colors, and chart types are consistent throughout your report. This makes it easier for users to interpret the data. 

Creating Interactive Dashboards

One of the powerful features of Power BI is the ability to create interactive dashboards. Adding filters, slicers, and drill-through capabilities enables users to explore data more deeply and gain insights on demand.

Slicers are one of the most effective ways to provide interactivity. They allow users to filter the report by specific categories, such as time periods, product categories, or regions. Using slicers with hierarchical data (e.g., region > country > city) enables users to drill down and explore data at different levels of detail.

Drill-through allows users to right-click on a data point in a visualization and access detailed information about that data point in another page or report. It’s an excellent way to allow users to explore data in a more granular manner without overwhelming them with too much detail in the main dashboard.

Data Preparation and Advanced Transformations

Power BI’s Power Query Editor provides a comprehensive set of tools for transforming and shaping data. As you prepare for the PL-300 exam, you must understand how to apply advanced transformations to clean, format, and prepare data for analysis.

Merging and Appending Queries

Power Query allows you to combine data from multiple sources using merge and append operations. These two operations are fundamental when working with large datasets that come from different tables or data sources.

• Merging Queries: Merging allows you to combine two tables based on a common column. For instance, you might have two tables—one containing sales data and another containing customer information. By merging the tables on a common customer ID, you can create a single table that contains both sales and customer details. 
• Appending Queries: Appending queries is useful when you need to combine rows from two or more tables with the same structure. For example, if you have sales data from multiple regions in separate tables, you can append them into one consolidated table for analysis. 

Advanced Power Query Transformations

In addition to basic transformations like filtering and grouping, Power Query offers advanced features such as:

• Unpivoting Data: When your data is in a wide format, such as when months are represented as columns, you can use unpivoting to convert the data into a long format where each row represents one data point. 
• Custom Columns and Conditional Logic: You can create custom columns in Power Query based on conditional logic. For instance, you can categorize sales data by creating a custom column that assigns a “high,” “medium,” or “low” value depending on the sales amount. 
• Data Type Conversions: Understanding how to properly set the data types for each column in your dataset is essential for accurate analysis. For example, ensure that numeric columns are set to the correct integer or decimal types, and date columns are set to the Date type. 

Handling Missing Data

Handling missing or incomplete data is another essential skill for Power BI users. When you encounter missing values, you can use Power Query’s fill operations or replace errors to handle them. For example, if certain records are missing sales data, you can replace them with the average sales value or simply remove those rows from the dataset.

Time Intelligence in DAX: Essential for Business Reports

Many Power BI reports involve time-based analysis. Calculating year-over-year (YoY), quarter-over-quarter (QoQ), and month-to-month (MoM) growth is a fundamental aspect of business intelligence. Understanding how to use Time Intelligence functions in DAX will help you create powerful time-based calculations for your reports.

Key DAX Time Intelligence Functions

Power BI includes several Time Intelligence functions that allow you to perform calculations based on time periods. Some of the most important functions include:

• TOTALYTD(): This function calculates the year-to-date value for a given measure. For example, you can use TOTALYTD to calculate total sales from the start of the year to the current date. 
• SAMEPERIODLASTYEAR(): This function compares a measure’s value to the same period from the previous year. It’s useful for calculating YoY growth or performance comparisons. 
• DATESYTD(): Similar to TOTALYTD, but it returns a table with a subset of dates corresponding to the current year up to the current date, which can be used for more complex calculations. 

Customizing Time Periods

While the standard time periods (e.g., year, quarter, month) work for most cases, businesses may have unique time periods, such as fiscal years or custom date ranges. You’ll need to understand how to create custom time periods using DAX to handle these scenarios effectively.

For example, if your organization follows a fiscal year that starts in October, you can create a custom fiscal year column that shifts the start and end dates of your year. This enables you to perform time-based analysis according to your company’s fiscal calendar rather than the standard calendar year.

Best Practices for Power BI Deployment and Governance

Power BI is a powerful tool, but to make the most of it in an enterprise environment, you must have a solid strategy for deployment, governance, and ongoing maintenance. These best practices will ensure that your reports remain reliable, secure, and scalable as they grow.

Once you’ve created a report in Power BI Desktop, you’ll need to publish it to the Power BI Service for sharing with stakeholders. In the service, you can manage access to reports using workspaces. Workspaces allow you to collaborate with others and manage permissions for both report creators and consumers.

Additionally, you can create apps within Power BI to package multiple reports and dashboards into a single, easy-to-use application. This is particularly useful when you have different departments or teams that need access to a set of related reports.

Managing Data Governance and Security

Data governance is critical when working with Power BI in an enterprise setting. Power BI offers several features to manage data security and ensure compliance with company policies:

• Row-Level Security (RLS): As mentioned earlier, RLS allows you to control which rows of data a user can view based on their role or identity. This is essential for ensuring that sensitive data is only accessible to authorized users. 
• Data Sensitivity Labels: Power BI integrates with Microsoft Information Protection to label reports and datasets with sensitivity labels. These labels help ensure that sensitive data is properly classified and protected. 

Maintaining Reports and Ensuring Scalability

As reports evolve over time, it’s important to manage their performance and ensure they scale with growing data volumes. Use best practices for data model design, data refresh schedules, and query optimization to maintain high performance.

For large datasets, consider using aggregation tables to store pre-calculated summary data, which can be used to speed up performance in reports.

Conclusion: 

The PL-300 exam, also known as the Microsoft Power BI Data Analyst certification, is an essential step for professionals looking to showcase their expertise in business intelligence and data analysis. Throughout this blog series, we’ve explored key areas such as data modeling, Power Query transformations, DAX, visualizations, report design, and performance optimization—all of which are crucial for success in the exam and for practical application in real-world business environments.

To excel in the PL-300 exam, you need more than just theoretical knowledge. Hands-on experience with Power BI is essential to reinforce your understanding and skills. Practical work with data transformations, creating complex DAX measures, building interactive reports, and optimizing performance will not only prepare you for the exam but also help you create impactful solutions in your professional career.

The PL-300 exam tests your ability to handle various aspects of Power BI, from data loading and cleaning to designing efficient and interactive dashboards that provide actionable insights. Understanding the importance of data governance, security measures, and best practices for report sharing will ensure that your reports are reliable, scalable, and accessible to stakeholders.

One of the most important skills is the ability to align your reports with business goals. This involves understanding the needs of the end-users, keeping your reports simple and focused, and designing them to provide the right insights in a clear and actionable manner.

As you continue your exam preparation, make sure to take advantage of practice exams, study guides, and online resources to deepen your knowledge. By combining theory with practical application and focusing on the key areas outlined in this series, you’ll be well on your way to mastering Power BI and successfully achieving the PL-300 certification.