Everything You Need To Know About Power BI

What does Power BI stand for?

Power BI stands for "Power Business Intelligence." It is a combination of "Power," which implies strength and capability, and "BI," which stands for "Business Intelligence." Power BI is designed to provide powerful tools and capabilities for business intelligence and data analysis, enabling users to gain insights and make data-driven decisions to improve their business processes and performance.

What is Power BI?

Microsoft Power BI is a Business Intelligence (BI) Dashboarding and Reporting platform that provides powerful data and analytics capabilities, that can be tailored to any business user.

It’s garnered a well-deserved reputation as one of the top performers in this space and is known for providing more meaningful insights through end-to-end solutions and highly customisable data visualisations.

It features over 200 out-of-the-box, native data source connections, powerful programming languages through Data Analytics Expressions (DAX) and M Query, an extensible visualisation library, and enterprise features such as Deployment Pipelines, Dataflows, and more.

Is Power BI Free?

Power BI Desktop is a free application that allows users to connect to a wide range of data sources, explore data, build data models, create and publish reports. There are both free plans, which contains limited features, and paid plans, including Power BI Pro and Power BI Premium which have many more capabilities.

View the costs and capabilities of each plan here.

What is DAX in Power BI?

DAX stands for Data Analysis Expressions. It is a formula expression language. It can be applied to Microsoft Power BI, as well as other Microsoft tools such as Azure Analysis Services, Power Pivot in Excel.

DAX allows users to perform a wide range of data manipulation and analysis tasks, such as creating calculated columns or calculated tables, and measures. It is particularly useful for tasks like creating custom calculations, defining business logic, and performing advanced and effective calculations on the data.

How to use Power BI

Here’s a simple guide to help start with using Power BI desktop:

1. Install Power BI desktop. Type in browser: https://powerbi.microsoft.com/en-us/desktop/ to visit the Power BI Desktop download page -> Click on the prominent Download free button. It will automatically navigate to Microsoft App Store if the computer system is Windows 10 or later -> Run the installation file.

2. Connect to data sources. Launch Power BI Desktop on local computer -> Sign in using Power BI credentials -> Click on the Get Data option to load different data sources, including csv, excel, dataflow, database, etc.

3. Transform and clean data. Click on Transform Data, the Power Query Editor will open. Rename columns, fill empty value, merge queries, pivot data, etc. are included in this process.

4. Build model. click on the Model view icon on the left panel to see the tables that have imported along with relationships. Double-click on the relationship line to open the Manage Relationships dialog. Define the cardinality (one-to-one, one-to-many) and cross filter direction (both, single) for each relationship.

5. Create dashboards. Drag and drop fields onto the report canvas to create visualisations like charts, tables, maps, and more. Use filters, slicers, and drill-through options to add interactivity to dashboards.

How to create dashboards in Power BI

Creating a dashboard in Power BI involves several steps:

1. Data import

Connect to various data sources, such as Excel files, databases, online services, and more by opening Power BI Desktop application -> Navigate to Home ribbon -> Click on Get data -> Choose the desired data sources.

2. Data transform

Under Home tab -> Click on Transform Data. The Power Query Editor will open, allowing to clean data as needed, for instance, rename tables or columns; change data type; fill empty values; remove or add columns; merge queries. Click on Close & Apply after shaping the data.

3. Data relationship build

• Click on the Model view icon on the left panel to see the tables that have imported along with relationships.
• The Power BI Desktop can often automatically infer relationships between the tables. For creating relationships manually, drag and drop fields from one table to matching fields in another table to create relationships.
• Double-click on the relationship line to open the Edit Relationship dialog. Define the Cardinality (one-to-one, one-to-many) and Cross filter direction (both, single) for each relationship. Click on OK.

4. Dashboard creation

• Add visualisations by clicking on a visualisation type which will instantly create a new blank visualisation on the canvas.
• Once you have added a blank visualisation to the canvas, the Build visual section helps to configure it by dragging and dropping fields to determine how data is displayed in the visual.
• Open the Format visual section from the right-side menu to access customisation options, this includes adjusting colors, fonts, labels, and other stylistic elements to match the design preferences.

How to learn Power BI

Some resources to help to get started and become proficient in Power BI:

• Beginner tutorials and documentations: start with introductions provided by Microsoft. They offer a comprehensive range of resources to help beginners understand the basics of Power BI. https://learn.microsoft.com/en-us/power-bi/fundamentals/desktop-getting-started
• Online courses and tutorials: consider enrolling in online courses on platforms like Coursera, edX, LinkedIn Learning, and Udemy. These courses offer structured learning paths with hands-on exercises.
• YouTube tutorials: there are many YouTube channels and creators who offer free Power BI tutorials. Search for topics of interest and follow along with their videos.
• Download and install Power BI to regularly practice with sample data: visit the official Power BI website, download the Power BI Desktop application, and install it on computer. It's free to use.
• Advanced features: once is comfortable with the basics, explore more advanced features like DAX (Data Analysis Expressions) for creating complex calculations and measures.
• Stay updated: Power BI is continually evolving, so stay up-to-date with new features and updates by following official announcements and reading Power BI blogs.

How long does it take to learn Power BI?

The time it takes to learn Power BI can vary significantly depending on several factors, including the prior experience with data analysis, the depth of knowledge that users want to acquire, the amount of time that can be dedicated to learning, the overall familiarity with similar tools and concepts, and the complexity of the dashboards that you wish to create. Here are some general guidelines to consider:

1. Basic proficiency (2-4 weeks): if you have a basic understanding of data analysis and visualisation, you can become proficient in creating simple dashboards in a few weeks. This level of proficiency allows users to perform common tasks and create straightforward visualisations.
2. Intermediate skills (1-6 months): to gain a deeper understanding of Power BI's features and capabilities, it might take a few months of consistent learning and practice. This level of proficiency enables users to work with more complex data sources, create advanced visualisations, and use DAX for calculations.
3. Advanced expertise (6 months - 1 year or more): achieving advanced expertise in Power BI, including mastering advanced modeling, DAX, and data transformation, can take several months to a year of learning. At this level users can tackle complex projects, troubleshoot issues, and optimise performance.

How to export Power BI to Excel

There isn't a direct way to export a Power BI report to Excel. However, users can export the underlying data from a Power BI report in multiple ways.

1. Export data from a visual to csv: open the Power BI report in Power BI Desktop. Select the visual (e.g., bar chart) from which want to export data. Click on the three dots on the top of the visual and choose Export data. Give a File name and click on the Save button to save it to the desired location.

2. Analyse in Excel: In Power BI Service, click on the three dots beside the report / dataset, choose Analyse in Excel to export the data for analysing.

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