How to clear the PL-300 exam and become a Microsoft Certified Power BI Data Analyst

Trillions of megabytes of data is created on the Internet every day. Don’t you think there should be someone who specializes in just analyzing this data and making sense of it? Yes, there is one such person - a data analyst. It’s the job of a data analyst to scour through an ocean of data, collect it, analyze it, and pull meaningful insight out of it. There has been a sharp increase in the demand for qualified data analysts to take on data analysis-related roles across different industries and organizations. As a result, the demand for data analyst and data science-related positions has far exceeded the supply, as companies compete with each other to attract the best talent by offering higher salaries and employee benefits.

And if you’re looking to make a career as a data analyst, or you are already a data analyst looking to upgrade your skills to take your career to the next level, this article can be your perfect starting point. Read on and together we will take a deep dive into things that make you a good data analyst, using the magical data visualization tool – Power BI, and how to pass the PL-300 exam to become a certified Microsoft Certified Power BI Data Analyst.

But before we talk about Power BI or the PL-300 exam and certification, let’s first start by learning about the core skills you need to develop to become a good Data Analyst.

Required Skills for becoming a Data Analyst

1) Data preparation

The first skill you need to become a good data analyst is the skill to prepare data. Sounds simple, right? Well, not quite. To acquire data preparations skills, you have to develop sub-skills such as:

• Working with data sources - Let's say if you're getting your data in XML format, then as a good data analyst you should know how to work with the XML data sources.
• Data cleaning - You can't use the data until it's clean. So, you need to be able to have the ability to clean the data by performing actions such as removing duplicate values, removing blanks, errors, and special characters, and filling in missing values.
• Combining data - The next skill you need to learn is combining data. If you're getting some data from a CRM and the other from SAP - as a data analyst, it's your responsibility to combine the data from the two data sources to build one centralized, copy of data for analysis and processing. So, you should know how to append data, use joints, or perform data intersections.
• Data transformation - This is when you have to transform into a format that is useful for your current job on hand. A practical example of this is when you have the computer-generated data in a horizontal format in the sheet when it would be more convenient for you to view the data when it's in a vertical scroll - you as a data analyst should be able to reformat this data.

2) Number crunching

While there are several ways how data analysts crunch their data, here are some of the analysis and number crunching models you should know of:

• Statistical analysis - You should be able to understand simple tools such as mean, median, mode, or distribution. But depending on your current role, you might even need to acquire more advanced skills such as how to know whether your data has been skewed.
• Functional analysis - This skill requires you to understand not just the data in isolation but how it ties in with the industry on the whole. For example, how you'd use data in insurance would be different from how you'd use it in a SAAS technology company. So, you have to be able to learn about these industries. Similarly, if you're working in the manufacturing industry, you as the data analyst should know about the various analysis and modeling methods relevant in this particular industry, such as inventory analysis, supply chain analysis, demand forecasting, etc.
• Adhoc analysis - You might be presented with data without much background information and then be expected to do a quick analysis and come up with useful outputs. These ad hoc analyses can be in the form of trend analysis, distribution etc, and it's up to you as a data analyst to decide which models and tools you should be using to come up with quick results.
• Experimental analysis - This is when you have to experiment to come up with data that can be used for decision making basically, know the potential winning choices.

3) Storytelling

Storytelling in the case of a data analyst doesn't have the prince, princess, dungeons, and dragons. There are charts, dashboards, and tables instead. Thus, it’s crucial for a data analyst to be able to work with dashboards and use his or her presentation skills using tools such as Power BI. Furthermore, you have to understand that when you're doing the data preparation, crunching, or analysis - you're not doing all of that for yourself. You do it for someone else - perhaps a team, department, or the entire organization gets to use the data. This is where your storytelling skills come into play. You should be able to know which chart is relevant to your current task, how to format it and how to present it without overwhelming the end user of the data.

Having good persuasion skills on good storytelling skills works like the cherry on the cake. Furthermore, it also helps to build basic visual design sense. For example - paying attention to the details related to fonts, colors, and how to visually communicate the idea aesthetically - something many data analysts overlook.

4) Asking good questions

A good analyst doesn’t jump to the task without asking questions such as: why do we need the data? How much time do we have? What does this data need to have to be useful? In what format? It’s especially important to know the motivation behind the analysis that you’re supposed to do.

Also, biases can especially be your biggest enemy. So making sure that your data is unbiased, is extremely important data analyst puts context before analysis. For example, if you don’t understand your industry, there might be things that you think are remarkable but are quite normal in your industry’s context.

5) Knowing data visualization tools

As a data analyst, you have to be able to go beyond just knowing excel and learn more advanced and specialized data visualization software, such as PowerBI. As more and more companies use Power BI for their data intelligence, the demand for data analysts is growing rapidly.

And this brings us to the perfect Segway to talk about Power BI and what makes it such an in-demand skill for data analysts.

Power BI - the data visualization tool of choice for data analysts

Raw data can be in different forms, such as SQL database, CSV, Excel, Java API, etc. Power BI is a Microsoft tool designed as a collection of pre-built architecture, processes, technologies, and services working together to convert raw data into meaningful insights, presented in easy-to-understand visuals. These insights can be in various forms, such as graphs, charts, reports, or a dashboard.

Thanks to Power BI’s simple interface, with a high adoption rate - it is catching fast in its popularity as compared to its competitors such as Tableau. It's backed by Microsoft and it has access to all popular cloud features and capabilities making it a data visualization tool of choice by data engineers, data analysts, and database administrators. The platform can stretch up to the full scope of the business, and not just data visualization.

Roles & Responsibilities of a Power BI Data Analyst

The Power BI data analyst provides meaningful insights by using accessible data and using his or her domain expertise to not only make sense out of it but illustrate it to the team in an easy-to-understand format. It’s the job of a Power BI data analyst to collaborate with key stakeholders across different verticals of the organization to determine business requirements for the data while cleaning and transforming the data and then designing data models using Power BI.

A Power BI data analyst delivers meaningful value through easy-to-understand data while enabling the team to perform self-service analytics. He or she then implements and set-up solutions for the consumption of that data.

They clean and transform data using their advanced technical abilities to deliver value to their business. As subject matter experts data analysts are responsible for designing and developing data models.

They communicate and collaborate with stakeholders to provide relevant insights based on the established requirements.

The Power BI exam

Candidates for the PL-300 exam (earlier DA-100 which was retired on 31 March 2022) should be proficient in Power Query and coding expressions using DAX.

You will be required to answer the following types of questions, and the passing score to clear this exam is 700/1000:

• Single choice
• Multiple choice
• Drag and drop
• Scenario-based (yes or no)
• Case study

Here are some important tips, if you are giving your exam from home.

• Do a thorough system check to ensure that your computer is working fine, especially the webcam and microphone as the exam is conducted in a proctored environment, and a proctor will monitor your exam using your webcam.
• No breaks are allowed during the exam
• Don’t get stuck on questions for too long

A data analyst looking to clear this exam needs to have a solid understanding of data processing and data repositories both on-premises and in the cloud.

Is the PL-300 exam and the Certified Power BI Data Analyst Certification worth it?

While a PL-300 certification isn't mandatory to apply for a job as a Power BI data analyst - having this certification does significantly multiply your odds of getting this job. It works like a stamp of approval for your employer that you know what you're talking about. Furthermore, new technology can especially look intimidating when you're starting new. Having a certification can be a great starting point as it's hard to know where to start when you're just a beginner. You don't know which resources to refer to, what to study, what to skip, what matters, and what doesn't.

This certification helps you validate your skills and helps you demonstrate your expertise and knowledge in Power BI. It also helps you attract lucrative salary packages and allows you to attract opportunities from top companies.

How to Prepare for the PL-300 exam?

This certification validates your expertise in data engineering but it doesn’t guarantee you a job. If you have the time and discipline for self-learning then Microsoft offers excellent learning resources to help you clear the exam, including a laid-down learning path.

Here are some free resources you can check as the starting point for self-learning:

• Check out PL-300 Exam Prep videos at Microsoft Learn
• Download the PL-300 study guide
• Demo the exam at Microsoft’s Exam Sandbox

However, if you have limited time because you have a full-time job then self-learning with a parallel job might not be your surest way to clear the PL-300 exam. This exam is easy to pass only if you’re prepared for it. And as someone new to the role a of Data analyst, you might find it hard to know where even to begin.

We would highly recommend you to check this 3-day instructor-led training from Readynez where you get not only get practical training, but also the necessary mentoring and guidance from specialized Power BI data analysts whose only job will be to help you clear the PL-300 exam.

If you have any questions related to this article or the PL-300 exam, you can get in touch with us here.