After you know what Power BI is and what it is used for, the practical step comes: building your first dashboard yourself. The good news is that your first dashboard does not need huge data or advanced knowledge, just a simple data file and a clear question you want to answer.
This article gives a practical, step-by-step walkthrough for creating a sales tracking dashboard in Power BI Desktop, from importing an Excel file to publishing and sharing the report, along with design rules that make the dashboard clear and mistakes beginners make. It suits beginners and employees who want hands-on practice.
If you have not yet got to know the tool, start with the article What Is Power BI and What Is It Used For in Companies on the Bayan Learning blog.
The difference between a report and a dashboard in Power BI
Many people use the word dashboard to mean any page full of charts, but Power BI distinguishes between two terms:
| Term | What it means | Where it is built |
|---|---|---|
| Report | One or more pages of interactive charts and filters built on a data model | In Power BI Desktop or in the cloud service |
| Dashboard | A single page in the cloud service that gathers pinned tiles from different reports to show the most important indicators | In the Power BI Service |
In everyday use inside organizations, the two words often refer to the same thing, so we will use dashboard in this article to mean a report page that displays the main indicators, and then we will point out how to pin it to a dashboard in the cloud service.
What you need before you start
- Power BI Desktop installed on a Windows computer, available from the official Microsoft website.
- A simple data file, such as an Excel sales file with columns for date, order number, branch, product, quantity, and revenue.
- One or two questions you want the dashboard to answer, such as: How are sales developing month by month? Which branch or product earns the highest revenue?
- An account in the cloud service if you want to publish and share the report; plans and licenses vary according to what Microsoft announces.
If you do not have a ready file, create a table of about a hundred rows in Excel with the columns above, or use open data from the Saudi Open Data Platform or from the General Authority for Statistics to practice on real data.
Steps to create your first dashboard
Step one: Define the questions and indicators
Before opening the program, write down what the reader wants to know. A simple sales dashboard might need the following indicators:
- Total revenue.
- Number of orders.
- Average order value.
- Revenue trend by month.
- Revenue by branch.
- Top-selling products.
Defining the indicators in advance helps you avoid adding many charts that do not serve a clear question.
Step two: Import the data
Open Power BI Desktop, then from the Home ribbon choose Get data, then Excel workbook, select the file, and then choose the table or sheet you need. You will find two options: Load to import the data directly, or Transform data to clean it before loading. It is better to choose Transform data so you can review it first.
Step three: Clean and prepare the data
The Power Query window opens, which is where you prepare the data. The most important things to do in it are:
- Make sure each column has the right type: date as a date type, revenue and quantity as numbers, and branch and product as text.
- Delete columns not needed for the analysis.
- Handle empty or duplicate rows.
- Standardize how names are written, so that a branch name appears in a single form across all rows.
- Give the table and columns clear names.
When finished, click Close and Apply to load the data into the model. In real projects this step takes the largest part of the time, and the quality of the dashboard depends on the quality of the data cleaning.
Step four: Create a date table and relate the tables
If you have multiple tables, such as sales, products, and branches, open Model view and make sure they are related through shared columns, such as product code or branch code. If you will calculate time comparisons such as the previous month, create a separate date table and relate it to the date column in the sales table. If you have only one table, you can postpone this step in your first attempt.
Step five: Write the basic measures
A measure is a formula that calculates an indicator and whose result changes with filters. From New measure in the Table tools tab, you can write the following DAX formulas, assuming the table is named Sales, the revenue column is Revenue, and the order number column is OrderID:
Total Revenue = SUM(Sales[Revenue])
Orders = DISTINCTCOUNT(Sales[OrderID])
Average Order Value = DIVIDE([Total Revenue], [Orders])
And for comparison with the previous month, after relating a date table named Date with its column Date:
Revenue Last Month = CALCULATE([Total Revenue], PREVIOUSMONTH(‘Date'[Date]))
Growth % = DIVIDE([Total Revenue] – [Revenue Last Month], [Revenue Last Month])
Replace the table and column names with ones that match your data. Using the DIVIDE function instead of the division operator is useful because it handles division by zero without errors.
Step six: Build the charts
Go to Report view and you will find the Visualizations pane and the Fields pane. Drag the fields to the suitable visuals:
| Question | Suitable visual | Fields |
|---|---|---|
| What are the total revenue and number of orders? | Cards | Total Revenue, Orders, and Average Order Value |
| How does revenue develop over time? | Line chart | Axis: Month, Value: Total Revenue |
| Which branch earns the highest revenue? | Bar chart | Axis: Branch, Value: Total Revenue |
| What are the top-selling products? | Horizontal bar chart or table | Axis: Product, Value: Total Revenue, with a Top 10 filter |
| How are sales distributed across categories? | Pie chart or treemap when there are few categories | Category and value |
Step seven: Add interactive filters
Add a slicer visual to control how the data is displayed, such as a slicer for the time period, another for the branch, and a third for the product. When you select a value in a slicer, the other charts change automatically. You can also click an element in any chart to filter the other charts by it, which gives the dashboard its interactive character.
Step eight: Arrange the design
- Put the most important cards at the top of the page.
- Put the time chart below them because it gives the overall picture.
- Put the detailed charts at the bottom.
- Place the slicers at the side or top of the page in a fixed position.
- Give every chart a clear title that explains what it shows.
- Use a small number of colors consistently, and reserve one color for alerts.
- Make sure the elements are aligned and the spacing between them is even.
Step nine: Publish the report and share it
Save the file first, then choose Publish from the Home ribbon and select the workspace in the cloud service. After publishing, open the report in the browser, and you can pin visuals from it to a dashboard in the cloud service, set a data refresh schedule if the source is connected to a service or a data gateway, and then decide who can view it. Sharing options vary according to the license plan your organization uses.
Design rules for a clear indicator dashboard
- Start with the question: Every chart answers a question, and anything that does not answer a question should be removed.
- Reduce elements: Six to eight visuals per page are usually enough; clutter confuses the reader.
- Choose the right chart: Line for time, bars for comparison, and cards for key numbers.
- Avoid pie charts with many slices: They are hard to read when there are many categories.
- Standardize formatting: Fonts, colors, and the formatting of numbers and dates.
- Display numbers in an understandable format: Such as thousands or millions instead of long numbers.
- Mind the reading direction: For Arabic, put the most important item at the top right and test the order of elements on screen.
- Test the dashboard with a real user: and ask them whether they find the answer quickly.
Common mistakes when creating your first dashboard
- Neglecting data cleaning: This leads to incorrect or duplicated numbers.
- Adding many charts with no purpose: The main message gets lost.
- Using calculated columns where a measure fits: Measures are the better fit for most aggregation indicators.
- Not verifying the numbers: Compare the dashboard totals with the original source before sharing.
- Ignoring data types: For example, a date appearing as text, so time comparisons do not work.
- Neglecting permissions: When sharing sensitive data such as employee or salary data.
- Copying a design without understanding its purpose: It is better to base the design on the user’s need.
Dashboard ideas you can build after the first one
- HR dashboard: Headcount, turnover rate, absence rates, and localization.
- Expenses dashboard: Expenses by item and month versus the budget.
- Marketing dashboard: Visits, conversions, and customer acquisition cost by channel.
- Inventory dashboard: Stock levels and slow-moving items.
- Customer service dashboard: Number of tickets, response time, and reasons for complaints.
For those who work in Human Resources, you can read the article The Duties of an HR Specialist in Saudi Arabia to learn which indicators are prepared periodically. And for those who want to speed up some analysis tasks using AI while reviewing the results, you can read the article AI Tools to Boost Productivity at Work.
From the first dashboard to a professional skill
Learning the basic path from import to publishing gives you a good foundation, but working in a real environment requires broader skills: modeling data with multiple relationships, writing more complex DAX formulas, optimizing performance, managing permissions, and designing dashboards for different users. A structured course helps build these skills gradually with a hands-on project and feedback from an instructor.
Bayan Learning offers programs in data analysis, and you can browse the Power BI and data analysis courses and enroll in the program that suits your level. If you represent an organization and want to train your team in building reports and indicator dashboards, you can contact the Bayan Learning team.
Frequently asked questions about creating a dashboard in Power BI
How do I create my first dashboard in Power BI?
Define the questions and indicators, then import and clean the data in Power Query, relate the tables, write the basic measures, build the charts and filters, arrange the design, and then publish the report.
What is the difference between a report and a dashboard in Power BI?
A report is one or more pages of interactive visuals built on a data model, and a dashboard is a single page in the cloud service that gathers pinned visuals from different reports.
Do I need to know DAX to get started?
You can build a basic report by simply dragging fields, but knowing simple DAX measures helps with indicators such as averages, growth, and comparison with previous periods.
How long does it take to build a first dashboard?
Someone with a clean data file can build a simple dashboard in a few hours, and the time increases with multiple sources and their need for cleaning and modeling.
Can I use Power BI on a non-Windows device?
Power BI Desktop runs on Windows, while the cloud service opens in the browser, and there are mobile apps for viewing reports. Building models requires Windows or a virtual environment.
What is the best data file to practice with?
A sales, expenses, or employee attendance file with about a hundred rows or more, with clear columns, a date, an amount, and a category, or an open dataset from a government source.
Are these steps enough to work as a data analyst?
They are enough as a start, but professional work requires skills in modeling, advanced formulas, design, and communicating with users, and structured courses and hands-on projects help build them.
Creating your first dashboard in Power BI follows clear steps: defining the question, importing the data, cleaning it, relating the tables, writing the measures, building the charts and filters, arranging the design, and then publishing and sharing. The quality of the dashboard rises when the data is clean, the design is simple, and the indicators are tied to real user questions.
If you want to learn these skills in a structured way and apply them to data close to your work, see the available training programs at Bayan Learning and enroll in the Power BI course that suits you.