How to Create Your First Power BI Dashboard in 4 Easy Steps
A beginner’s guide for getting started with Microsoft Power BI data visualization
Data visualization has the capability to simplify complex facts and figures, transforming raw data into actionable business insights. Microsoft’s premium data visualization suite is Power BI lt=10-Day Power BI Program, which is available as a free web service or comes with the business edition of Office 365. Indeed, it just takes a few mouse clicks to create a custom dashboard report if you follow the right steps.
Before you begin using the visualization tool Power BI, make sure that you have registered for an account. You can use your corporate email address or if you are a student, use your university email address, to signup.
Once you have completed the registration process, follow this step-by-step tutorial and create your custom dashboard.
Step 1: Collect the data
The first step after you launch the Power BI application is to gain access to your data.
You can easily import your dataset from an MS Excel Workbook. In Office 365, simply open Power BI., click on the Get Data button located at the bottom of the navigation pane or on the lower left corner of the screen.
The navigation pane shows the option of Files. Click on Files and browse to the location where your Excel Workbook is located. Locate your file and then click on the Connect button. It takes a little time to process, and this is largely dependent on the file size.
After the file has been imported, you will see a blank workspace. From the navigation pane on the left, choose the dataset you have imported. The blank workspace should then change into a visualization creation tool. You will see navigation panes on the right with a multitude of options.
Step 2: Explore your dashboard
Microsoft Power BI has various icons to represent different visualizations. There are charts of all types like bar charts, column charts, stacked bars and columns, pies, half donuts, line graphs, area charts, waterfall charts among others - all represented through icons. Get familiar with these charts.
The right pane also has a Fields section which allows you to choose and switch between various data fields.
For instance, imagine the dataset you imported has a table with columns (fields) like employee name, employee age in years, salary range, increase in salary over 10 years, employee address and employee ID.
Depending on what you wish to display, you will first have to tick the checkbox for a particular data field, and then you can choose a chart type from the right pane.
For example, if you wish to display the salary range composition of employees, you can tick the age checkbox from the right pane and then select a pie chart. The pie chart will best display how many employees have a salary in which range.
Step 3: Choose the right chart
While you have created your dashboard and are off to a good start, it is equally important to learn which type of chart will be most suitable for which kind of data. If not properly considered, data visualization can become misleading.
Here are some strategies to keep in mind:
There are four general classifications of charts based on their functionality:
Pie charts are best used to show composition in percentages. Make sure that all values add up to hundred.
Stacked charts are used to show comparison and composition together.
Scatter plots are the best at showing a relationship between two variables. For instance, you may wish to see how number of years worked in the organization varies by salary for an employee.
Bar charts and column charts are mostly used for distribution and comparison. You can display the salary range versus a number of employees on a bar chart. This can show comparison among different ranges of salary. They can also be used to show periodic data.
Line charts and area charts are used for comparison. They are the most suitable for viewing time series data. For instance, if you wish to see how the salary of an employee has grown over the last 10 years, a line chart will give you the best visual representation.
Step 4: Save & publish your dashboard
Once you have created your dashboard and populated it with insightful charts, click on the Save button on the toolbar. Since Power BI charts are dependent on the Excel data, they will keep updating as the Excel sheet is updated.
You can also publish the dashboard to the Power BI service and share it with your colleagues.
Custom Power BI data visualization
Getting started with Microsoft’s premier data visualization software is easy. Customizing Power BI for your organization and gaining maximum insight into your business data, however, is more challenging.
At Innovative Architects, our Microsoft Gold Certified consultants specialize in leveraging Power BI analytics - turning raw big data into actionable business intelligence. Contact us today to find out our plan for helping your business succeed.