Executive Sales Dashboard in Power BI

Build an interactive sales dashboard with DAX measures and star schema modeling.

Introduction

30 Second Summary

Every sales meeting starts the same way. Someone pulls up a dashboard, clicks a filter, and the room watches revenue numbers shift across regions and time periods.

In this project, you will build an interactive executive sales dashboard in Power BI Desktop using real multi-table data from a fictitious bicycle company.

What You'll Build

When you open your finished report, you can click a year in the slicer and watch every chart, map, and matrix update instantly to show that time period's performance.

By the end of this project, you'll have:

A live dashboard where you click a fiscal year and watch an area chart, map, and matrix cross-filter to reveal which countries and products drive the most revenue.
A working star schema data model that correctly connects seven tables, proving you understand how analysts structure real-world datasets.
A custom DAX measure that activates an inactive relationship, demonstrating a skill interviewers specifically ask about in Power BI roles.
Secret Mission: A profit margin KPI card powered by a calculated column and a DIVIDE measure, showing you can derive insights beyond raw revenue.

Are there any prerequisites?

You need Power BI Desktop installed on a Windows machine. No prior Power BI experience or paid licenses are required.

Before We Start

Before we dive in, let's lock in what you're about to build and why it matters.

Download the Dataset and Import into Power BI

Every analytics project starts with getting raw data into your tool. For this dashboard, you'll work with AdventureWorks, a fictitious bicycle company dataset that Microsoft provides as a free sample.

The workbook contains multiple related tables covering customers, products, dates, and sales transactions. In this step, you'll download the Excel file, import its tables into Power BI Desktop, and verify the data types are correct.

In this step, get ready to:

Download the AdventureWorks Sales Excel workbook from Microsoft's GitHub repository.
Import all seven tables into Power BI via Power Query Editor.
Verify and fix data types, then close Power Query.

Download the AdventureWorks Sales workbook

AdventureWorks is Microsoft's official sample dataset for Power BI tutorials. It contains sales data across multiple tables that mirror a real business scenario.

Download the workbook by clicking this link: AdventureWorks Sales Excel workbook.
Save the file to your Downloads folder. The file is called AdventureWorks Sales.xlsx.

Confirm AdventureWorks Sales.xlsx appears in your Downloads folder before continuing.

File didn't download?

Some browsers may block the download because it comes from GitHub. Check your browser's download bar or notification area for a blocked-download prompt and allow it.

If the link opens a blank page, right-click the link and select Save link as to download the file directly.

help me download the AdventureWorks Sales Excel file

Import the Excel data into Power BI

Now you'll connect Power BI Desktop to the Excel file and select which tables to bring in. The workbook contains both named tables and raw data sheets. You only want the named tables.

In Power BI Desktop, look at the Home ribbon at the top.
In the Data section of the ribbon, click Excel.
Navigate to your Downloads folder, select AdventureWorks Sales.xlsx, and click Open.

The Navigator pane opens, listing all available tables and sheets in the workbook.

Check the boxes beside these seven tables: Customer, Date, Product, Reseller, Sales, SalesOrder, and SalesTerritory.
Do NOT select any items with _data in their name. Those are raw worksheet sheets, not the structured tables you need.
Click Transform Data at the bottom of the Navigator pane.

Power Query Editor opens with all seven tables listed as queries in the left panel.

Why Transform Data instead of Load?

Clicking Transform Data opens Power Query Editor, where you can inspect and fix your data before it enters the model. Clicking Load would skip this step and import the data as-is.

Verifying data types now prevents hard-to-debug calculation errors later.

Don't see all seven tables in Navigator?

Scroll down in the Navigator list. The workbook also contains sheets named like Customer_data or Sales_data. Skip any item ending in _data. Only select the seven clean table names listed above.

If Navigator does not appear at all, make sure you selected the Excel option from the Data section of the Home ribbon, not a different connector.

help me find and select the right tables in Power BI Navigator

Verify data types and apply changes

Power Query Editor lets you confirm that each column has the right data type before loading. A column detected as text instead of a number would break calculations silently.

In the Queries panel on the left, click the Sales query to select it.
On the Transform tab in the ribbon, click Detect Data Type.
Repeat for each of the other six queries (Customer, Date, Product, Reseller, SalesOrder, SalesTerritory): click the query name on the left, then click Detect Data Type on the Transform tab.

What does Detect Data Type do?

Power BI scans each column's values and assigns the most appropriate type. For example, it sets Sales Amount to Decimal Number and OrderDateKey to Whole Number. This ensures calculations and relationships work correctly later.

Before you close Power Query, think about what you expect to see in the main Power BI window. How many tables should appear in the Fields pane?

Click the Home tab in Power Query Editor.
Click Close and Apply.

Power BI processes the data and returns you to the main report view. Look at the Fields pane on the right side of the screen. You should see seven tables listed: Customer, Date, Product, Reseller, Sales, SalesOrder, and SalesTerritory.

Tables not appearing in the Fields pane?

If the Fields pane is empty or shows fewer than seven tables, you may have missed selecting some tables in the Navigator. Go to Home ribbon, click Transform data to reopen Power Query Editor, and confirm all seven queries are listed in the left panel.

If Power Query Editor shows the right queries but the Fields pane does not, click Close and Apply again and wait for the loading indicator to complete.

help me get all seven AdventureWorks tables into Power BI

Your data is loaded and ready. Next up, you'll drag your first field onto the canvas to see an instant chart and discover an important limitation.

Build Your First Visual (the Quick Win)

Your data is loaded and ready to go. Before diving into any modeling or configuration, let's do something satisfying first.

In this step, you will drag a field onto the canvas to see an instant chart. This proves your data import worked and gives you an immediate visual payoff.

In this step, get ready to:

Create your first column chart by dragging a single field onto the canvas.
Test whether fields from different tables produce correct results together.
Discover why a data model with relationships is essential for accurate visuals.

Drag Sales Amount onto the canvas

The fastest way to confirm your data loaded correctly is to create a visual. One field, one drag, one chart.

Confirm you are in Report View (the chart icon at the top of the left sidebar).
In the Fields pane on the right, click the arrow next to the Sales table to expand it.
Drag Sales Amount from the Sales table onto the blank canvas in the center of the screen.

Power BI automatically creates a column chart with a single bar showing the total Sales Amount across all rows. The value is approximately $29.4 million.

What just happened?

When you drag a numeric field onto an empty canvas, Power BI defaults to a column chart and sums all values in that column. You did not need to configure anything. One drag gave you a complete visual.

Don't see a chart on the canvas?

Make sure you are in Report View (chart icon), not Data View or Model View.
Confirm you dragged Sales Amount from the Sales table, not from a different table with a similarly named field.
If the Fields pane is empty, go back to Step 1 and run Close and Apply in Power Query Editor.

Why isn't my chart appearing when I drag Sales Amount onto the canvas?

Add a field from a different table

Your chart shows the grand total. An executive dashboard needs that total broken down by time period. The Month field lives in the Date table, which is a separate table from Sales.

What do you think will happen when you drag Month from the Date table onto the chart's X-axis? You would expect to see Sales Amount split by calendar month, right?

In the Fields pane, expand the Date table.
Drag the Month field onto the X-axis of your existing column chart.
Look at the result.

Instead of a clean month-by-month breakdown, you see something unexpected. Power BI sums the Month numbers or shows odd groupings that do not make sense. The chart does not look right.

This is supposed to look wrong

You did not make a mistake. Power BI does not yet know how the Date table and the Sales table relate to each other. Without a defined relationship, Power BI cannot correctly match each sale to its corresponding month.

This is exactly the problem that data modeling solves. Building relationships between tables is what turns disconnected data into an intelligent model.

Delete the visual

You have confirmed two things. Your data loaded correctly (the total Sales Amount appeared). Combining fields from unrelated tables produces garbage (the Month breakdown was wrong).

Click on the broken chart to select it.
Press the Delete key on your keyboard.

Your canvas is now blank again. The visual served its purpose as a diagnostic tool.

Why delete it instead of fixing it?

The fix is not in the visual itself. The fix is in the data model. You need to create relationships between your tables so that Power BI knows which dates belong to which sales. Once those relationships exist, the exact same drag-and-drop action will produce the correct chart.

You have proven your data is loaded and discovered the core problem. Without relationships, Power BI cannot combine fields from different tables correctly. Next up, you will build a star schema data model that connects every dimension table to your Sales fact table.

Create the Star Schema Data Model

In the last step, you discovered something important. Dragging fields from different tables onto a chart produced broken results because Power BI didn't know how those tables connect.

Building relationships between tables is what turns disconnected data into an intelligent model. Once Power BI knows that each sale belongs to a specific date, customer, and product, your visuals can accurately combine information from any table.

In this step, get ready to:

Create relationships between the Date table and the Sales table in Model View.
Hide key columns to keep the Fields pane clean.
Test your data model by rebuilding the Sales Amount by Month chart.

Create relationships in Model View

A star schema is a data model where one central fact table (Sales) connects to multiple dimension tables (Date, Customer, Product, etc.). You will build this structure now by creating relationship lines between tables.

Select Model View from the left sidebar (the diagram icon, below the table icon).

You see all seven tables as boxes with lines between some of them. Power BI auto-detected several relationships during import because the column names matched. However, the Date table has NO relationship line to Sales. That is the gap you need to fix.

Drag DateKey from the Date table onto OrderDateKey in the Sales table.

A solid line with 1 and * appears between the two tables. This means one-to-many: one date can appear in many sales rows.

Drag DateKey from the Date table onto DueDateKey in the Sales table.
Drag DateKey from the Date table onto ShipDateKey in the Sales table.

These two new lines appear as dashed lines, not solid. That means they are inactive relationships.

What are active vs inactive relationships?

Power BI only allows ONE active relationship between two tables at a time. Since you already have an active relationship on OrderDateKey, the relationships on DueDateKey and ShipDateKey become inactive by default.

Inactive relationships still exist in your model. You can activate them on demand using a DAX function called USERELATIONSHIP. You will do this in a later step.

You should now see the Date table connected to Sales by three lines: one solid (active) and two dashed (inactive). The other dimension tables (Customer, Product, Reseller, SalesOrder, SalesTerritory) should already show solid relationship lines to Sales from the auto-detection.

Don't see three lines from Date to Sales?

Double-click any relationship line to open its properties. Confirm one endpoint is DateKey in the Date table and the other is the correct Key column in Sales.

If you accidentally dragged to the wrong column, delete the relationship (right-click the line, select Delete) and re-drag to the correct column.

Help me fix my relationships in Model View.

Hide key columns from the report

Key columns are only used for building relationships. They clutter the Fields pane and confuse report viewers who might accidentally drag them onto a visual. Hiding them keeps the pane clean.

In Model View, right-click CustomerKey in the Customer table and select Hide in report view.
Repeat for DateKey and MonthKey in the Date table.
Repeat for ProductKey in the Product table.
Repeat for ResellerKey in the Reseller table.
Repeat for SalesOrderLineKey in the SalesOrder table.
Repeat for SalesTerritoryKey in the SalesTerritory table.
In the Sales table, hide OrderDateKey, DueDateKey, ShipDateKey, SalesOrderLineKey, ResellerKey, CustomerKey, ProductKey, and SalesTerritoryKey.

Hidden columns appear greyed out in Model View. They are still usable for relationships but will not show in the Fields pane when you build visuals.

Speed up hiding with multi-select

You can hold Ctrl and click multiple columns in the same table, then right-click and select Hide in report view to hide them all at once.

Test your data model with a visual

In Step 2, dragging Month from the Date table onto a chart produced broken results. Now that your relationship is in place, the same action should produce a correct breakdown.

Switch back to Report View by clicking the chart icon on the left sidebar.
In the Fields pane on the right, expand the Sales table and drag Sales Amount onto the blank canvas.
Expand the Date table in the Fields pane and drag Month onto the X-axis of your chart.

Before you look at the result, what do you expect to see this time? Think about what changed between now and Step 2.

This time the chart correctly shows Sales Amount broken down by calendar month. Each bar represents a different month's total sales. The relationship you built between Date and Sales is what made this work.

Chart still looks wrong?

If the months appear as numbers rather than names, or the bars look oddly grouped, check that you dragged the Month field (not MonthKey) from the Date table. If MonthKey does not appear in the Fields pane, you already hid it correctly. Look for Month under the Date table.

Also confirm in Model View that the solid line runs from DateKey to OrderDateKey (not to one of the other key columns).

Help me troubleshoot my Sales Amount by Month chart.

Your data model is solid. Every dimension table connects to Sales, and your visuals can now accurately slice data by any field. Next up, you will create a DAX measure and build the full dashboard with multiple visual types.

Create DAX Measures and Build the Dashboard Visuals

Your star schema is working. The Sales Amount by Month chart you built in the last step proves that relationships let you combine data from different tables correctly.

But a single sum only tells part of the story. What if you want to compare sales by order date versus sales by due date? That requires a custom calculation called a DAX measure. In this step, you will write your first DAX measure and then build four visuals that together form the complete executive dashboard.

In this step, get ready to:

Create a custom DAX measure using CALCULATE and USERELATIONSHIP.
Build an area chart comparing Sales Amount by order date and due date.
Add a map, matrix, and slicer that cross-filter each other.

Create the Sales Amount by Due Date measure

Your data model has three relationships between the Date table and Sales: one active (OrderDateKey) and two inactive (DueDateKey, ShipDateKey). By default, Power BI uses only the active relationship in calculations. A DAX measure can temporarily activate an inactive relationship to answer a different question.

In the Fields pane on the right, click the Sales table to select it.
On the Home ribbon, click New Measure. A formula bar appears at the top of the canvas.
Type the following DAX formula into the formula bar and press Enter:

Sales Amount by Due Date = CALCULATE(SUM(Sales[Sales Amount]), USERELATIONSHIP(Sales[DueDateKey],'Date'[DateKey]))

What does this measure do?

CALCULATE modifies how a calculation is evaluated by changing the filter context. Inside it, USERELATIONSHIP tells Power BI to temporarily use the inactive relationship between Sales[DueDateKey] and 'Date'[DateKey].

The result is a Sales Amount total grouped by due date instead of order date. This lets you compare when revenue was earned versus when payment was due.

After pressing Enter, look at the Fields pane. You should see Sales Amount by Due Date listed under the Sales table with a small calculator icon (indicating it is a measure, not a column).

Don't see the measure in the Fields pane?

Make sure you selected the Sales table before clicking New Measure. If you had no table selected, the measure may have been created under a different table.
Check the formula bar for red underlines. A typo in Sales[DueDateKey] or 'Date'[DateKey] will prevent the measure from saving.
help me fix my DAX measure formula

Build the area chart

Now you will replace the existing column chart with an area chart that plots both Sales Amount (by order date) and your new Sales Amount by Due Date measure on the same time axis.

Click the existing column chart on the canvas to select it.
Press Delete to remove it. Your canvas is now blank.
In the Fields pane, expand the Sales table and drag Sales Amount onto a blank area of the canvas.
Expand the Date table in the Fields pane. Expand the Fiscal hierarchy and drag Month to the X-axis well in the Visualizations pane.
Power BI may add Year, Quarter, and Month to the X-axis. Remove Year and Quarter by clicking the X next to each in the X-axis well, leaving only Month.
In the Visualizations pane, click the Area Chart icon to change the visual type.

You should now see a shaded area chart showing Sales Amount across the twelve months.

With the area chart still selected, drag Sales Amount by Due Date from the Sales table in the Fields pane to the Y-axis well alongside Sales Amount.
A second line appears on the chart. To distinguish it, click the Format visual icon (the paint roller) in the Visualizations pane.
Expand Lines, then expand Colors.
Find Sales Amount by Due Date in the color list and set it to red.

Your area chart now shows two overlapping areas: the default color for Sales Amount (by order date) and a red line for Sales Amount by Due Date. The gap between them reveals how timing differences between orders and due dates affect monthly totals.

Only seeing one line on the chart?

Check the Y-axis well in the Visualizations pane. Both Sales Amount and Sales Amount by Due Date should be listed there.
If the measure was accidentally placed in the Legend or Tooltips well, drag it from there into the Y-axis well instead.
help me get two lines on my area chart

Build the map, matrix, and slicer

Three more visuals complete the dashboard. Each one answers a different executive question: where are orders coming from, which products and resellers drive revenue, and how do I filter everything to a specific time period?

Click a blank area of the canvas (away from the area chart) to deselect it.
In the Fields pane, expand the Reseller table and drag Country-Region onto the blank canvas. Power BI automatically creates a map visual.
From the Sales table, drag Order Quantity onto the Bubble size well in the Visualizations pane.

You should see a map with bubbles on different countries. Larger bubbles indicate more orders from that region.

Why use bubble size instead of color?

Bubble size makes it instantly obvious which countries dominate order volume. An executive can glance at the map and spot the largest market without reading numbers.

Next, build the matrix visual.

Click a blank area of the canvas to deselect the map.
Drag Sales Amount from the Sales table onto the blank area.
Drag Product Category from the Product table to the visual.
Drag Business Type from the Reseller table to the visual.
In the Visualizations pane, click the Matrix icon to change the visual type.
If Business Type appears under Columns, drag it down to the Rows well (below Product Category).
In the Filters pane on the right, find Business Type and uncheck [Not Applicable] to filter it out.
Click the Format visual icon (paint roller). Expand Cell elements and toggle Data bars to On.

Your matrix now shows Sales Amount broken down by Product Category and Business Type, with colored bars that make it easy to compare values at a glance.

Finally, add the slicer so viewers can filter the entire dashboard by fiscal year and month.

Click a blank area of the canvas to deselect the matrix.
In the Fields pane, expand the Date table and drag the Fiscal hierarchy onto the blank canvas.
In the Visualizations pane, click the Slicer icon to change the visual type.
In the Field well, remove Quarter and Date by clicking the X next to each, leaving only Year and Month.

Your slicer should display a list of fiscal years with expandable months underneath.

Before you test the slicer, take a moment. What do you think will happen to the other three visuals when you click a year?

Click FY2019 in the slicer.

All four visuals update simultaneously. The area chart shows only FY2019 months. The map resizes its bubbles to reflect FY2019 orders. The matrix recalculates its Sales Amount values and data bars for that year only. This is cross-filtering in action. Every visual on the page responds to the slicer selection without any extra configuration.

Why do all visuals update at once?

Power BI visuals on the same page share a filter context. When the slicer restricts the Date table to FY2019, every visual that uses data related to Date (through your star schema relationships) automatically recalculates. This is one of the biggest benefits of building a proper data model.

Slicer not filtering the other visuals?

Make sure the slicer uses the Fiscal hierarchy from the Date table, not a text field. If it shows plain text instead of expandable years, delete it and re-drag the Fiscal hierarchy.
Confirm your Date-to-Sales relationship (DateKey to OrderDateKey) is active by switching to Model View. A solid line should connect the two tables.
help me fix my slicer cross-filtering

Your dashboard now has the full set of executive visuals: trends over time, geographic distribution, a detailed breakdown, and interactive filtering. In the next step, you will apply professional formatting to turn this from a working report into a polished portfolio piece.

Apply Professional Formatting and Save

Your dashboard now has DAX measures and four visuals that respond to the slicer. It is functional, but it does not yet look like something you would present to a hiring manager.

Formatting is what separates a practice exercise from a portfolio piece. In this step, you will apply a professional theme, build a branded title bar, and add consistent styling to each visual.

In this step, get ready to:

Apply the Executive theme for professional colors and fonts.
Create a branded title bar with a blue rectangle and white text.
Format each visual with shadows, consistent titles, and save the report.

Apply the Executive theme

A theme applies a coordinated color palette and font set across every visual at once. This saves you from manually picking colors for each chart.

On the View ribbon at the top of Power BI Desktop, select Themes.
From the gallery that appears, select Executive.

All four visuals instantly update with the Executive theme's professional colors and fonts.

What does the Executive theme do?

Themes change the default color palette, font family, and visual formatting across your entire report in one click. The Executive theme uses muted blues and grays that look clean in a business context.

Add a title bar

A title bar gives the report a clear identity. You will layer a text box on top of a colored rectangle to create a professional header.

On the Insert ribbon, select Text Box.
Type Executive Summary - Sales Report into the text box.
Select all the text you just typed.
Set the font size to 20 and click Bold.
Set the Font color to White.

You now have white bold text floating on the canvas. Next you will place a colored rectangle behind it.

On the Insert ribbon, select Shapes, then select Rectangle.
Drag the rectangle to the top of the page and stretch it to span the full page width.
With the rectangle selected, set its Fill color to Theme color 5 (#6B91C9 blue).
On the Format ribbon, select Send backward, then select Send to back.

Your text box now sits on top of the blue rectangle, creating a professional title bar across the top of the report.

Text disappeared behind the rectangle?

If your text is hidden, the rectangle is layered on top of it. Select the rectangle, then use Format ribbon and select Send to back to push it behind the text box.

If you cannot select the rectangle, try clicking an empty area of the canvas first, then click directly on the blue shape.

Why is my text hidden behind the rectangle?

Add finishing touches and save

Consistent formatting across all visuals makes your dashboard look intentional. You will add shadows, set uniform title sizes, and configure visual-specific settings.

Select the area chart on the canvas.
In the Visualizations pane, select the Format visual icon (the paint roller).
Select the General tab.
Under Title, set the text size to 16 pt.
Under Effects, toggle Shadow to On.

A subtle shadow now appears behind the area chart, giving it visual depth.

Repeat the same two changes (Title size 16 pt and Shadow On) for the map, matrix, and slicer visuals. Select each visual, open the General tab in the Format pane, and apply both settings.

All four visuals now have matching title sizes and shadows.

Select the map visual.
In the Format pane, find the map style setting and change Style to Grayscale.

The map background switches to a clean grayscale, letting the colored bubbles stand out.

Select the slicer visual.
In the Format pane, under Slicer settings, toggle Show "Select all" to On.

Why enable Select all on the slicer?

Adding a "Select all" option lets report viewers quickly reset the slicer to show every year and month at once. Without it, they would have to manually click each item to remove a filter.

Your dashboard is now fully formatted. Time to save it.

Select File, then select Save.
In the Save As dialog, navigate to your Downloads folder.
Name the file Executive Sales Dashboard and click Save.

Before you verify the final result, take a moment to predict what you expect to see. If you close the file and reopen it, do you think all your formatting (theme, title bar, shadows, slicer settings) will persist?

Close the file by selecting File, then Close.
Reopen the .pbix file from your Downloads folder by double-clicking it.

The report loads showing the Executive theme, a blue title bar reading "Executive Summary - Sales Report" in white text, shadows on each visual, and the slicer filtering all visuals when you click a year.

Formatting looks different after reopening?

Make sure you clicked Save before closing. If you closed without saving, your changes were lost. Reapply the formatting and save again.

If the title bar text is misaligned, select both the text box and rectangle and reposition them at the top of the canvas.

Why did my formatting disappear after reopening the file?

Secret mission

Add a Profit Margin KPI Card

Revenue is only half the story. In this bonus challenge, you will create a calculated column and a DAX measure to display profit margin as a dynamic KPI card on your dashboard.

Clean Up Your Resources

This project runs entirely locally using Power BI Desktop. There are no cloud resources or ongoing costs to worry about.

Decide whether to keep your resources running, pause them to come back later, or delete them entirely.

Resources you used:

Power BI report file (.pbix) saved in your Downloads folder.
AdventureWorks Sales Excel workbook (AdventureWorks Sales.xlsx) in your Downloads folder.

Keep everything running

No action needed. Choose this if you plan to keep building on your dashboard or want it ready to show in interviews.

Your .pbix file stays in your Downloads folder. Consider moving it to a dedicated portfolio folder so it is easy to find later.
The AdventureWorks Sales.xlsx workbook can safely be deleted since all data is embedded inside the .pbix file. However, keeping it does no harm.
If you want to share your report interactively, you can publish to the Power BI service using a free Microsoft Fabric account at app.powerbi.com. Others can then view and interact with your report in a web browser.

Pause - I'll come back to this later

Close Power BI Desktop to free up memory. Your files remain on disk and are ready to reopen any time.

Save your work if you have not already (File > Save).
Close Power BI Desktop.
To resume later, double-click the .pbix file in your Downloads folder. Power BI Desktop opens with your full dashboard intact.

Delete - I don't want to use this again

Remove all project files from your machine. This frees up disk space and leaves no leftover artifacts.

Close Power BI Desktop.
Open File Explorer and navigate to your Downloads folder.
Delete the AdventureWorks Sales.xlsx file (the source workbook).
Delete your .pbix report file.
Empty your Recycle Bin to permanently remove the files.

Nice Work!

You just built a publication-ready executive sales dashboard in Power BI Desktop, from raw Excel data all the way to polished, interactive visuals.

You've learned how to:

Create a star schema data model with active and inactive one-to-many relationships connecting dimension tables to a central fact table.
Write DAX measures using CALCULATE, SUM, USERELATIONSHIP, and DIVIDE to compute business KPIs that respond dynamically to filters.
Design interactive visuals (area chart, map, matrix, slicer) with professional formatting that cross-filter each other when a viewer clicks a year or month.
Secret Mission: Added a profit margin KPI card using a calculated column and a DIVIDE measure to show executive-level profitability insights.

Ready to quiz yourself?