Roadmap

December 1, 2023

How to become a Power BI expert in 2024?

Here's a comprehensive guide to Power BI, whether you are a Data Scientist, Data Analyst or Business Analyst. This guide guide is must do for all.

Organisations across industries are constantly collecting vast amounts of information. However, turning this raw data into actionable insights can be a challenging task. This is where Power BI acts as your friendly guide in the data world, helping you turn complex information into clear pictures and smart decisions. But, Is Power BI worth this popularity? Absolutely, Power BI would be an excellent career option not just in 2023 but for many decades ahead with a 36% market share, Power BI is the most popular data analytics platform among businesses. Power BI's market share is 1.8x higher than Tableau.

Whether you're new to data or a professional, join us on this exciting journey to unlock the potential of Power BI and enhance your skills in business intelligence. So, Let's dive into the world of data together and discover how Power BI can be your helping hand in data analysis!

This blog is your go-to guide for understanding Power BI,  from tools, reports, skills and learning resources to getting certified and building experience.

What is Microsoft Power BI?

Microsoft Power BI is a Business Intelligence tool that empowers users to transform data into stunning visuals and share insights with ease. It provides a comprehensive suite of analytics tools for connecting to data sources, transforming and modelling data, creating interactive reports and dashboards, and sharing them with colleagues or clients.

Why Do We Need Power BI?

  • Data Visualisation: Power BI makes it easy to convert complex data into visually appealing charts, graphs, and reports, which are much easier to understand and act upon.
  • Data Integration: Power BI can connect to a wide variety of data sources, including databases, cloud services, spreadsheets, and web services, allowing you to bring all your data into one place for analysis.
  • Real-time Insights: With Power BI's live data connections, you can get real-time insights into your business performance, enabling rapid decision-making.
  • Data Exploration: It enables users to drill down into data, filter, and explore it interactively, empowering users to find answers to their specific questions.
  • Collaboration: Power BI Service facilitates collaboration by allowing teams to share and collaborate on reports and dashboards in a secure and user-friendly environment.

Power BI Reports

Power BI reports are at the heart of the tool, providing a canvas for creating interactive visualisations and insights. Here are some key features:

  • Visualisations: Power BI offers a wide range of customizable visualisations, including bar charts, pie charts, tables, maps, and more. Users can select the visualisation that best represents their data.
  • Interactivity: Reports are highly interactive. Users can click on data points to see details, apply filters, and explore data from different angles.
  • Dashboards: Dashboards are collections of related visualisations and reports, providing an at-a-glance view of key metrics and KPIs.

Career path for Power BI developers

There is a high demand for Power BI skilled professionals in almost every type of industry such as software, retail, healthcare, etc. So, those who are still in a dilemma whether it is a bright career option or not can definitely go ahead with this option. Not only data analyst, but you can apply for various other profiles such as:

1. Power BI Project Manager: Project managers plan and designate project resources, prepare budgets, monitor progress, and keep stakeholders informed 

Salary: ₹15L - ₹23L/yr

2. Power BI Developer: Primary role involves creating and maintaining Power BI reports and dashboards.

Salary: ₹3.6L - ₹11L/yr

3. SQL Server Power BI Developer: this involves familiarity with MS SQL Server BI Stack tools and technologies, such as SSRS and TSQL.

Salary: ₹7L - ₹14L/yr

4. Power BI Administrator: Regularly fields questions and issues related to stability, performance, and permissions/access. 

Salary: ₹4.0L - ₹16L/yr

How to learn Microsoft Power BI?

Power BI, a powerful data visualisation and business intelligence tool from Microsoft, can be your ticket to success. In this guide, we'll take you through a step-by-step process to learn Power BI, prepare for the PL-300 certification exam, and get job-ready.

Step 1: Get Familiar with the Interface

The journey to becoming a Power BI expert starts with getting comfortable with its interface. Luckily, Power BI is a free download from Microsoft for Windows users. If you're not on Windows, you can run it in a virtual machine.

To get started, install Power BI and acquaint yourself with its main components. Here are some resources to help you with this initial step:

  • YouTube Channel to Follow :
  1. Alex the Analyst | 589k Subscribers
  2. Guy in a Cube | 374k Subscribers
  3. Avi Singh | 192k  Subscribers

Remember, your goal here is to start working with real data as soon as possible.

Step 2: Foundational Knowledge

After understanding the interface of powerBI, now it's time to learn some fundamentals of power BI. By mastering these foundational concepts and functionalities, you'll establish a strong foundation for your Power BI expertise.

1. Fundamentals of Data Modeling

Data modeling in Power BI involves organizing data into tables and fields, connecting them with relationships, and choosing accurate data types. This allows you to combine and analyze data from various sources effectively. Understanding tables, relationships, and data types is important for building a well-structured model that gives insightful visualizations and accurate analysis.

You can also use these references to learn how to model and clean data in Power BI:

2. Connect PowerBI to Various Data Sources

You can explore how to import data into Power BI from different sources like Excel, databases (SQL Server, MySQL), and online platforms (SharePoint, Salesforce). Understand how to refresh data and keep it up-to-date.

Step 3: Advanced Data Transformation and Cleansing 

Once you understand the user interface and data modeling, you’re ready to move forward with data transformation and cleansing.This step involves preparing your data to ensure its accuracy, consistency, and reliability before you analyze and visualize it. 

1. Data Cleaning and Transformation

Effective data cleaning and transformation in Power BI starts with the Query Editor. It involves handling missing data, removing duplicates, and transforming data types. This process ensures that your data is accurate and suitable for analysis, with tasks like filling missing values and converting text fields to date formats.

Learning resources

2. Query Editor for data transformation

Power BI's Query Editor is a versatile tool for shaping data. It allows users to filter, sort, and create calculated columns, enabling tasks like calculating profit margins. Merging and appending queries consolidate data from different sources, while conditional columns add flexibility. Features like data preview and step history ensure transparency in the transformation process.

Learning resources

3. DAX (Data Analysis Expressions) for calculations, filtering and aggregation

Data Analysis Expressions (DAX) is a powerful formula language in Power BI that enables users to extract meaningful insights from their data. Through DAX, you can perform complex calculations, create custom metrics, compare data across time periods, filter data based on criteria, and transform raw data into actionable intelligence.

Learning resources:

Step 4: Get familiar with Data Visualization and Dashboard Design

As you become more experienced with Power BI, you can start exploring more advanced techniques. It includes Data visualization with charts and graphs, creating reports and dashboards using Power BI.

1. Visualization Best Practices

When it comes to presenting data in Power BI, it's essential to follow some guidelines for effective visualization. Choose the right types of charts and graphs that best represent your data. Use colors purposefully to highlight important information and maintain clarity. Applying these best practices ensures that your audience can easily understand and derive insights from your visualizations.

Learning resources
1. Books: 

The Visual Display of Quantitative Information by Edward R. Tufte 

Data Visualization: A Practical Guide by Andy Kirk 

2. Courses:

 9 free courses of data visualization for beginners

2. Dashboard Design:

Creating a dashboard involves putting together various visual elements to tell a cohesive and interactive story. Learn how to arrange visuals in a way that makes sense, utilizing features like slicers and filters to add interactivity. A well-designed dashboard guides users through the data, helping them grasp key insights quickly and intuitively.

Learning resources:
1. Books: 

Dashboard Design for Business Intelligence by Stephen Few 

Effective Practice for Building Dashboards by Andy Kriebel

2. Courses: 

Power BI Dashboard design 

3. Power BI Customization

Power BI offers customization options to make your reports stand out. Explore different themes to give your reports a consistent look and feel. Utilize tooltips to provide additional context to your visuals, enhancing the user experience. Experiment with various report layouts to find the most effective way to convey information.

Step 6: Real-world Projects and Optimization

Now, it's time to put your Power BI skills into action by working on real projects with actual data. Imagine you're solving problems just like you would in a job. This hands-on practice helps you get comfortable using Power BI in practical situations. You'll tackle challenges similar to those you might face in a work setting, showing that you can use data to solve real business problems.

1. Real-world datasets for Power BI projects

  • Kaggle: Kaggle is a popular platform for data science competitions and data sets. It offers a wide variety of datasets from various domains, including finance, healthcare, and marketing.
  • UCI Machine Learning Repository : The UCI Machine Learning Repository is a collection of datasets for machine learning and data mining tasks.
  • Data.gov: Data.gov is a U.S. government website that provides access to a vast collection of public datasets. It includes datasets from various government agencies, such as the Census Bureau, the Bureau of Labor Statistics, and the National Institutes of Health.

2. Performance Optimization

As data models grow in complexity, performance can become an issue. This step explores best practices for data model optimization, ensuring your Power BI projects perform efficiently. By implementing optimization techniques, you can minimize query times, improve data refresh performance, and enhance the overall user experience.

Here are some recommended resources for learning about Power BI performance optimization:

Step 7: Getting Certified with Microsoft  PL-300 

After you've gained practical experience and finished different projects using Power BI, you can take the PL-300 certification exam. This test checks how good you are at getting data ready, organizing it, making it look good, and putting it all together. The steps we talked about in this guide cover everything you need to know to do well on the exam and succeed in jobs that involve using Power BI. So, you're all set to show off your Power BI skills!

Conclusion

In conclusion, getting proficient in Power BI is like investing in your job future. Just go through these steps, practice a lot, and keep learning. If you stick with it and use the right tools, you can become an expert in Power BI. This can lead to job opportunities in analyzing data and helping businesses make smart decisions. So, stay determined, practice, and you'll be on your way to a great career using Power BI!

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