Note: The column with no header (under the red box) represents null or blank dates in your data. Power BI creates a placeholder column for any records that don't have a corresponding value in the field used for your columns (in this case, the Year field from your DateTable).

5. Remove the phantom column by modifying the Filters for Year.

Filter out the Blanks.
Go to the Filters pane on the right.
Find the filter for Year.
Click the dropdown to see the list of years.
Uncheck the box for (Blank).
Only select 2017 and 2018.

The column will disappear instantly.

Create visualizations using column charts and line charts.

In this visualization, we aim to display categorical data by showing the total revenue across different product categories.

1. Remove all existing visuals to start with a clean page.

2. Before proceeding, we need to clean up the Products table. Specifically, we should split the category || sub_category column into two separate columns.

Go to the Power Query Editor, select the target column, and then click Split Column → By Delimiter.

3. Select Custom delimiter.

Choose a custom delimiter.
Type ||, "Make sure there is a space before and after the." ||
Click OK to split the column.

4. Rename the new columns to more user-friendly names, such as "category" and "sub_category."

Click close & apply

5. Now, create a visualization using a clustered column chart.

Note: Ensure you have created a relationship between the Products table and the Sales table:

From: Products → Sales
Cardinality: One-to-many (1:*) — meaning one product can have many sales
Cross filter direction: Single

6. Use a column chart to display revenue for different product categories:

Drag the Category column from the Products table to the X-axis.
Drag the Revenue measure from the Sales table to the Y-axis.

Note: Try using other chart types for visualization to understand why the clustered column chart is the best choice for differentiating product categories.

7. To compare revenue across product categories by year, drag the Year column from the Date table to the Legend field.

Note: To remove blanks, change the filter to Basic Filtering and select the years 2017 and 2018.

8. Drag the Sub_categories column from the Products table to the Tooltips field to display additional details when hovering over each column.

Note: You can add multiple tooltips to a single data model to provide additional context for your visuals.

9. Change the cluster column chart colors.

Go to "Format your visual."
Under Visual, Expand the column.
Select the year and color of your choice.

10. You also could use an area chart and a line chart for visualization.

Drag and drop MonthNo column from date table to the X-axis
Drag and drop Revenue measure column from Sales table to the Y-axis
Drag and drop Year column from DateTable table to the the Legend

Graph Description:

The graph is a stacked area chart comparing Revenue Measure across months for two years (2017 and 2018).
X-axis: MonthNo – shows months from 1 to 12.
Y-axis: Revenue Measure – shows the total revenue for each month.
Legend: Year – separates the data for 2017 (blue) and 2018 (orange).
Tooltip: First sub_category – allows users to see the breakdown of revenue by sub-category when hovering over a point.

The visual clearly shows month-by-month revenue trends for both years. You can see that some months (like May and October) have spikes, indicating higher revenue. The shading under each line emphasizes the total contribution per year.

Benefits

Year-over-year comparison: Quickly identifies growth or decline between 2017 and 2018.
Trend analysis: Shows seasonal patterns or revenue spikes across months.
Sub-category insights via tooltips: Allows users to drill into which sub-categories contribute most to revenue without cluttering the graph.
Visual clarity: The stacked area format highlights total revenue while maintaining the distinction between years.

Note: Also, switch to a line chart to see what happens.

11. Change the colors of your visual:

Go to Format your visual.
Under the Visual tab, expand the Shaded area section.
In Series, select the year you want to modify.
Choose your preferred color for each year.

Create visualizations using line and clustered column & treemap charts.

Line and Clustered Column charts let you compare values (columns) and trends (line) together, making it easy to see both magnitude and patterns over categories.

Line and Clustered Column chart

1. Under visualization, select the Line and Clustered Column chart.

2. Select Line and Clustered Column chart.

Drag and drop category column from Products table to the X-axis field.
Drag and drop Revenue measure column from Sales table to the Column Y-axis field.
Drag and drop sales column from Sales table to the Line Y-axis field.
Drag and drop Year column from DateTable table to the the Column Legend field.

3. You can change the color of the line.

Go to Format your visual.
Under the Visual tab, expand the Lines section.
Choose your own color.

Treemap chart

A Treemap chart is a visualization that displays hierarchical data using nested rectangles.

A Treemap chart is used for:

Showing part-to-whole relationships – how categories contribute to a total.
Comparing proportions – quickly seeing which category is largest or smallest.
Analyzing hierarchical data – such as Category → Subcategory → Product.
Identifying dominant segments – spotting top-performing areas at a glance.

1. Click on empty space then select Tremap chart

Drag and drop the category column from the Products table to the Category field.
Drag and drop the revenue measure column from Sales table to the Values field.

2. Drag the SubCategory column from the Products table into the Details field to analyze the data at a more granular level.

Create visualizations using Donut and Pie charts.

Pie Chart

A Pie chart displays how categories contribute to a whole using slices. Each slice represents a proportion of the total.

It is used to show part-to-whole relationships in a simple and easy-to-understand way.

Note:

Use them to show percentage distribution.
Best when working with a small number of categories.

*
1. Visualize revenue with a pie chart and a donut chart.

Click on empty space
Select pie chart
Drag and drop Revenue measure column from Sales table to the Value field.
Drag and drop category column from Products table to the Legend field.

Donut Chart

A Donut chart is similar to a Pie chart but has a hollow center, which can be used to display additional information (such as a total value).
It is used for the same purpose as a Pie chart but provides a cleaner layout and better space utilization.

1. Select donut chart.

Create visualizations using Card chart.

Card Chart

A Card chart displays a single key value, such as total revenue, total orders, or profit.
It is used to highlight important metrics clearly and prominently, making it easy for users to see critical numbers at a glance.

1. Click on empty space, then under visualization, select Card chart.

2. Drag and drop Revenue measure column from Sales table to the Value field.

Select Currency format under the Measure Tools tab.

3. You can modify the colors for the card chart and enable shadow.

Select format your visual
Under Cards tab select the color and enable shadow.

Note: You can add shadow effect to any visual.

Create visualizations using Scatter, and Azure map charts.

Scatter Chart

A Scatter chart plots points on an X and Y axis to show relationships or correlations between two numerical variables.

Used for: Identifying patterns, trends, or outliers in data.

1. Create a new page.

2. Compare prices with scatter chart.

Select scatter chart under visualization
Drag and drop Revenue measure column from Sales table to the Y Axis field.
Drag and drop price column from Sales table to the X Axis field.

What was done:

Data Mapping: You plotted Price on the x-axis and Revenue Measure on the y-axis.
Filtering: You applied an advanced filter to only show products with a price less than 100.

What we see:

High-Volume Low-End: Most products are clustered at the low price point ($0–$20) with relatively low individual revenue.
Top Performers: A few "outliers" (the high dots) show that certain products priced between $10 and $40 are your biggest revenue drivers.
Diminishing Returns: As the price approaches 100, the products become more scattered and generally produce less total revenue.

Azure Map Chart

A Map chart displays data geographically using locations like countries, regions, or cities.

Used for: Visualizing spatial patterns and comparing metrics across different geographic areas.

Note: Make sure there is a one-to-many relationship between the Stores and Sales tables.

1. Select table chart

Drag and drop the State column from the Stores table to the canvas empty space.

Note: As you can see, some data cleaning is required.

2. Clean the data and split the combined location field to create separate State and City columns.

Go to Power Query Editor by clicking Transform Data.

3. Select the Stores table, then split the column by delimiter.

4. Rename the columns to something meaningful.

5. Do the same with the lat/long column.

Select the Stores table, then split the lat/long column by delimiter.

6. Rename the columns to something meaningful.

Click Close and Apply

Note: Delete the State column visual that was created earlier.

7. Select Azure maps chart under visualization.

Drag and drop City column from Stores table to the Location field.
Drag and drop Revenue measure column from Sales table to the Size field.

What we see:

Core Market: Your primary revenue is heavily concentrated in the Eastern and Central United States, specifically around the Midwest and Southeast regions where the bubbles are largest and most dense.
Revenue Distribution: Larger bubbles indicate high-performing cities; for example, there is a notably large bubble in the south-central US (likely the Texas area) representing a top-tier revenue city.

Note: For more reliable results, use latitude and longitude instead of the city.

Configure and customize the visuals.

1. Change the visual title in some charts.

Select visual
Go to format your visual
Under general tab expand the title.
Adjust the configuration to match your preferences.

2. Configure the page itself by clicking on the page space, then click "Format Your Report Page."

Adjust the configuration to match your preferences.

What can be done here:

Customize the Outer Area: You can change the appearance of the "wallpaper," which is the background area surrounding your report canvas.
Set a Background Color: Use the Color dropdown to pick a solid shade or enter a specific hex code to match your branding.
Add an Image: Click Browse... to upload a .PNG or .JPG file to use as a background for the entire report area.
Adjust Fit & Transparency: * Change the Image fit (Fit, Fill, or Normal) to control how your background scales.
Use the Transparency slider to fade the wallpaper, allowing it to be subtle so it doesn't distract from your data.

Enhance Visuals with Conditional Formatting.

Conditional Formatting is a feature that automatically changes the appearance of data based on specific rules or conditions.

In tools like Power BI, it allows you to:

Change background or font colors based on values.
Add data bars to compare magnitudes visually.
Display icons (arrows, flags, indicators).
Highlight high or low values dynamically.

Why it’s useful

Helps users quickly identify trends and patterns.
Makes important values stand out (e.g., high revenue, low profit).
Improves readability of tables and matrices.
Adds visual meaning without creating extra charts.

For example, you can highlight revenue in green when it exceeds a target and red when it falls below it. This makes the report easier to interpret at a glance.

1. Select Line and cluster column chart under visualization.

Drag and drop category column from Products table to the X-axis field.
Drag and drop Revenue measure column from Sales table to the Column Y-axis field.
Drag and drop sales column from Sales table to the Line Y-axis field.

Note: This chart compares total revenue (blue bars) and sales volume (orange line) across product categories for 2017 and 2018, highlighting “Snacks & Sweets” as the top-performing category.

2. Enhance Visuals with Conditional Formatting.

Go to the "Format your visual" section.
Under the Visual tab, expand Columns.
Next to Color, click the Conditional Formatting (Fx) icon.

3. Set the color based on field values.

In the Color Scale window:

Select Gradient as the format style.
Set it to be based on the Revenue measure.
Choose your preferred colors for the lowest and highest values.

4. This results in a color gradient where categories with higher revenue, like "Snacks & Sweets," are shaded in a darker navy blue.

Note: You can modify or remove this effect.

5. Rename the visual to “Revenue Gradient by Category & Total Sales (2017–2018)”.

6. Use rules to format styles.

Go to the Format your visual section.
Under the Visual tab, expand Columns.
Next to Color, click the Conditional Formatting (Fx) icon.

In the Color scale window:

Select Gradient as the format style.
Set it to be based on the Revenue measure.
Set a rule where any category with a value greater than or equal to 10,000 (Number) and less than or equal to 100% is colored in a dark navy blue.

Note: When multiple rules are added, the most recent rule will override all previous rules.

7. This highlights the top two categories (Snacks & Sweets and Fruits & Vegetables) in dark blue, while the remaining categories that fall below the $10k threshold retain a lighter, default shade.

Applying Slicers and Filters to Refine Your Data.

Slicers and filters are powerful tools in data visualization that allow you to focus on specific subsets of your data. By applying them, you can highlight trends, compare categories, and gain insights without altering the underlying dataset. This makes it easier to analyze complex information quickly and effectively.

Create a slicer (filter) to display stores in specific states.

1. Make space on the left side of the canvas to insert the slicer chart.

Select the slicer visual under Visualizations and adjust its size to fit the canvas.
Drag and drop State column from Stores table to slicer visual.

2. Select different states, and the data in all visuals will update accordingly.

Note: To select multiple states, hold the Ctrl key.

3. If you don’t want to hold the Ctrl key, you can adjust this in the Format your visual section:

Expand Slicer settings → Selection
Deselect Multi-select with Ctrl

Note: You can select Single select to allow only one value to be chosen at a time.

4. Apply a filter to the (blank) field.

Note: As you can see, the blank field shows nothing.

5. In the Filters section under State:

Click Select all
Deselect (Blank)

Note: You can also specify only the states you want to appear in the slicer visual.

6. You also could filter by certain stores.

Drag and drop the Store ID column from the Stores table into the Filters on this page field, then select only the stores you are interested in.

Synchronize slicers across pages.

Slicers allow users to filter data visually on a report page. Synchronizing slicers ensures that selections made on one page automatically apply to other pages, providing a consistent and seamless filtering experience across the entire report.

Note: An alternative method for synchronization is to copy and paste the slicer between pages. A pop-up window will appear asking if you want to synchronize the slicers.

*
1. Go to Page 2 and add a slicer using the State column from the Stores table.

Drag and drop State column from Stores table to slicer visual.

Note: The slicer is not synchronized yet, so selections on Page 2 will not affect Page 1.

2. Synchronize slicers across pages.

Go to View and click Sync slicers.

3. The Sync slicer section will appear on the right.

The Sync slicers pane only shows a list of pages where a slicer based on the exact same data field (like "State") has been added. Because Overview and Page 1 both have a checkmark in the "Visibility" (eye icon) column, we can confirm:

Overview contains the "State" slicer.
Page 1 contains the "State" slicer.
Page 2 does not physically show the slicer, as its visibility box is unchecked.

4. Check both boxes to synchronize slicers across pages.

5. You can hide the slicer on Page 2, but it will still filter the data when you change the synced slicer on the Overview page.

6. Adjust the visuals for a better view.

Use a theme to apply formatting to all visuals in the report at once.

Themes allow you to quickly standardize colors, fonts, and styles across all visuals in a report. By using a theme, you ensure a consistent look and feel without having to format each visual individually.

1. You can select any theme to apply its color scheme to all visuals in your report.

2. You can also download and load a .json file from the online library.

Note: You can also save your current theme for future reports by clicking Save current theme.

2. To apply the downloaded theme to your report, click “Browse for themes” and select the downloaded .json file.

Implement Page Navigation.

Page navigation lets users move between different report pages easily, improving the flow and usability of your report.

1. Create a new page, name it “Navigation Page,” and move it to the beginning of your report.

2. Insert a logo image of your choice.

Go to the Insert tab.
Click on the image.
Browse your files and select the image you want to insert.

3. Create navigation buttons between pages.

Go to the Insert tab.
Click on Buttons.
Choose a button style (for example, Blank or Arrow).
Place the button on the page.

4. Name the button “Overview.”

Select the button.
In the Format pane, expand Button text.
Turn Text on (if it’s off).
Enter Overview as the button label.

Note: In Desktop (Edit mode) → You must press CTRL + Click to follow the button or link.

In Reading View or after publishing to Power BI Service → You can click the button normally (no CTRL needed).

5. In the Format pane, turn on Action.

Set Type to Page navigation.
Select the destination page. (Overview)

6. Rename your pages to something more meaningful.

Right-click on a page tab at the bottom of the report.
Select Rename.
Type a clear and descriptive name (for example, Overview, Sales Analysis, or Revenue Dashboard).
Press Enter to confirm.
Clear page names make your report look more professional and easier to navigate.

7. Create a Back button on the Overview page.

Go to the Overview page.
Click the Insert tab.
Select Buttons → choose the Back button.
Place the button on the page.
Change color or other settings.
In the Format pane, make sure Action is turned on.
Set Type to Back.

Now the button will take users to the previous page when they click it.

8. Repeat these steps for each page to create smooth navigation between your report pages.

9. Create buttons for each page on the Navigation page.

Go to the Navigation page.
Click the Insert tab.
Select Buttons → choose a button style (for example, Blank).
Place the button on the page.
In the Format pane, turn Action on.
Set Type to Page navigation.
Select the destination page.
Turn on Button text and enter the page name (for example, Overview, Revenue Dashboard, Sales analysis).

Note: Repeat the same steps for each button.

10. Design the Navigation page as you like.

Add a background color to the page.

Click on an empty area of the page.
Open the Format pane.
Expand Canvas background and choose a color.

Add a background color to the buttons.

Select a button.
In the Format pane, expand Style or Fill.
Choose a background color that matches your design.
Adjust the text size, font, and alignment to make the page look clean and professional.

Take your time with the design, a well-styled navigation page makes your report look much more polished and organized.

11. Hide all report pages except the Navigation page to create a cleaner, more professional layout. This prevents users from switching pages using the default tabs and ensures they navigate the report using the designed buttons for a controlled and structured experience.

Conclusion

By mastering these visualization and reporting techniques, you can transform complex datasets into intuitive, interactive reports. From tables and charts to conditional formatting, slicers, and page navigation, each step helps ensure your reports are both insightful and visually engaging. Applying these best practices in Power BI allows you to deliver data-driven insights with clarity, consistency, and impact.

Written by Kirill.A - Azure & Cybersecurity Consultant at AntusNet

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Visualization and Report Creation with Power BI

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Visualization and Report Creation with Power BI - antusnet.ca

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Visualization and Report Creation with Power BI

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