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Power BI is a business analytics platform utilized for generating interactive dashboards from intricate and raw data, enabling the retrieval of valuable insights with ease. The TOP N function serves as a beneficial feature within Power BI. This DAX function is particularly advantageous for filtering and returning the top or bottom N records based on specified criteria. In this article, we will delve deeply into the TOP N function.

Table of Contents

• What is Power BI and TOPN?
• Why is it essential to identify the ‘Top’ Element?
• Tables and Measures
• How TOPN Utilizes Data?
• Comprehending the TOPN formula in Power BI
• Real-World Scenarios
• Displaying Your Results in Power BI
  • Stacked Bar Chart in Power BI
  • Pie Chart in Power BI
  • Donut Chart in Power BI
  • Stacked Column Chart in Power BI
• Optimal Approaches for Employing TOPN
• Conclusion

What is Power BI and TOPN?

Power BI is a user-friendly analytics application created by Microsoft, empowering users to convert raw information into interactive dashboards. TOPN is a Power BI function that enables quick identification of the top items from a dataset. It provides an efficient method for searching and retrieving your information.

Why is it essential to identify the ‘Top’ Element? 

Envision operating a business and having awareness of your best-selling products. Understanding your primary customers enables you to foster strong relationships with them. Identifying leading regions helps you manage your resources efficiently.

Tables and Measures

• In Power BI, your data is structured in tables, akin to spreadsheets. Each table comprises columns that contain distinct data points. For instance, columns might include Product name, Sales amount, and region.
• Measures are personalized calculations that you create to interpret your data. They condense information and yield insights.

How TOPN Utilizes Data?

• TOPN utilizes a table as its data source and relies on a measure or column to establish the ranking sequence. It subsequently returns a new table that consists solely of the top “N” items according to your criteria.
• Consider having a vast dataset comprised of thousands of products, and you wish to spotlight the top 10 best selling items. By using TOPN, Power BI organizes your product data by sales numbers and presents only the top 10 items, making it simpler to analyze and visualize the “highest” performing goods.
• The TOPN DAX functions integrate well with other DAX functions, facilitating the resolution of more intricate calculations.

Comprehending the TOPN formula in Power BI

The TOPN formula is structured as follows:

TOPN(<n_value>, <table>, <order_by_expression>, [<order>])

Explanation:

• <n_value>: The quantity of top items you wish to view (e.g., 3 for the top 3)
• <table>: The table that contains your data
• <order_by_expression>: The column or measure by which you want to rank.
• [<order>] (Optional): DESC (Descending) to sort from highest to lowest, ASC (Ascending) for sorting from lowest to highest. </pre>

Step-by-Step Instructions

• Select your data: Identify the table you wish to utilize.
• Determine your ranking criteria: Choose a column you intend to rank by.
• Select how many “Top” items: Specify n_value.
• Compose the formula: Employ the TOPN functions with the appropriate parameters.
• Visualize the result: Develop charts or tables for enhanced decision-making.

Real-World Scenarios

To gain deeper insights into the TOPN function, let’s examine its functionality.

Example 1:

Assuming you have a “Sales” table containing “ProductID”, “ProductName”, ” Amount”, and Quantity.

This illustrates the Sales Table before executing the TOPN DAX Function.

Now, let’s implement the TOPN Function to discover the TOP 5 Products based on Sales.

Top 5 Products by Sales =

TOPN(
    5,               -- Number of rows to be returned.
    Sales,           -- Substitute ‘Table’ with your actual Table
    Sales[Amount],   -- Replace Table[amount] with your actual column
    DESC             -- Arrange from  highest to lowest
)

Output:

Explanation: The TOPN(5, Sales, Sales[Amount], DESC) command will yield the top 5 products exhibiting the highest sales figures from the Sales table, arranged by the Amount column in descending order.

Example 2:

Assuming you possess a “Sales” table that includes “CustomerID”, “CustomerName”, ” Amount”, and Year.

This is what the Sales Table looks like prior to executing the TOPN DAX Function.

Let’s continue…
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execute the TOPN Function to determine the TOP 3 Clients by Revenue.

Top 3 Clients by Revenue =

TOPN(     
          3,                        -- Quantity of rows to be returned (Top 3 rows)
          Sales,                    -- Name of the table (Sales)
          Sales[Amount],            -- Column to organize by (Amount)
          DESC                      -- Arrange in descending order
)

Output:

Description:. The TOPN(3, Sales, Sales[Amount], DESC) will yield the top 3 clients with the greatest sales amounts from the Sales table, sorted by the Amount column in descending order.

Displaying Your Findings in Power BI

After you’ve computed your TOPN findings in Power BI, the following phase is to present the data in a manner that is easy to understand. Power BI provides various types of charts for representation that can effectively showcase your TOPN information.

Here are several traditional visualization types:

Stacked Bar Chart in Power BI

Let’s go over the Steps required to construct a Stacked Bar chart.

Step 1: Prepare your dataset.

We will utilize the dataset discussed earlier.

We will evaluate the TOP 3 clients based on Sales amount and depict them using a stacked bar chart.

Step 2: Establish TOP 3 Clients by Sales Measure

Below is the DAX formula to generate this measure:

Top 5 Products by Sales =
TOPN(
    5,                 -- Return number of rows (top 5)
    Sales,            -- Swap ‘Table’ with your Actual Table
    Sales[Amount],    -- Swap Table[amount] with your actual column
    DESC              -- Sort from highest to lowest
)

This will compute the Top 5 clients based on their sales amount in descending order.

Step 3: Create a stacked bar chart.

From the visualization panel, select the Stacked Bar Chart icon and assign the axis by dragging CustomerName to the Y-Axis and Amount to the X-Axis.

This is an overview of how the visualization panel appears.

Step 4: Resulting visualization:

Use Case: A sales department wishes to assess the sales performance of various regions over multiple quarters. A Stacked Bar Chart presents each quarter as a bar with segments illustrating sales from different regions.

Significance: The Stacked Bar Chart aids in visualizing both the total value and its components.

Pie Chart in Power BI

Let’s review the Steps required to establish a Pie chart.

Step 1: Prepare your dataset

We will leverage the previously discussed dataset.

We will compute the TOP 3 clients by Sales amount and express them through a Pie chart.

Step 2: Establish TOP 3 Clients by Sales Measure

Here is the DAX formula to formulate this measure:

Top 5 Products by Sales =

TOPN(
           5,                     -- Return number of rows (top 5)
           Sales,                 -- Swap ‘Table’ with your Actual Table
           Sales[Amount],         --  Swap Table[amount] with your actual column
           DESC                   -- Sort from highest to lowest

)

This will calculate the Top 3 clients based on their sales amount in descending order.

Step 3: Create a Pie chart

From the visualization panel, click on the Pie Chart icon and arrange the Legends by dragging CustomerName and Amount into values.

This is an overview of what the visualization panel resembles.

Step 4: Resulting visualization:

Use Case: A retail enterprise aims to visualize its sales distributions across various regions. The Pie Chart will illustrate the percentage of overall sales produced from each region (e.g., North America, Asia, Europe).

Significance: This allows companies to swiftly identify which region is performing best.

Donut Chart in Power BI

Let’s analyze the Steps necessary to create a Donut chart.

Step 1: Prepare your dataset

We will again apply the previously discussed dataset.

We will determine the TOP 3 clients by Sales amount and illustrate them using a Donut chart.

Step 2: Establish TOP 3 Clients by Sales Measure

Below is the DAX formula to create this measure:

Top 5 Products by Sales =
TOPN(
          5,                     -- Return number of rows (top 5)
          Sales,                 -- Swap ‘Table’ with your Actual Table
          Sales[Amount],         -- Replace Table[amount] with your actual column
          DESC                   -- Sort from highest to lowest
)

This will identify the Top 3 clients based on their sales amount in descending order.

Step 3: Create a Donut chart.

In the visualization panel, click on the Donut chart icon and set the Legends by dragging CustomerName and Amount into values.

This is how the visualization panel appears.

Step 4: Resulting visualization:

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Use Case: Intellipaat aims to display its sales distribution categorized by Course (e.g., Data Science, Digital Marketing). A donut chart will effectively illustrate the sales percentage derived from each category in a straightforward and easily interpretable way.

Importance: A donut chart facilitates the comprehension of parts in relation to the whole; its circular design with a void center enhances the visual comparison of proportions.

Stacked Column Chart in Power BI

Let us explore the steps necessary to construct a Stacked Column chart.

Step 1: Prepare your dataset

We will utilize the dataset mentioned earlier.

We will identify the TOP 3 customers based on sales amount and depict them using a donut chart.

Step 2: Establish TOP 3 Customers by Sales Measure

Here is the DAX formula to create this measure:

Top 5 Products by Sales =
TOPN(
          5,                      --Number of Rows to be Returned
          Sales,                 -- Substitute “Table name” with your Actual Table name
          Sales[Amount],         -- Substitute “Table[amount] with Actual Table
          DESC                   -- Sort from highest to lowest
)

This formula will compute the Top 3 customers according to their sales amounts in descending order.

Step 3: Generate a Stacked Column chart.

Within the visualization panel, click on the Stacked Bar Chart icon, and arrange the axes by dragging CustomerName to the Y-Axis and Amount to the X-Axis.

This illustrates the layout of the visualization panel.

Step 4: Resulting Visualization:

Use Case: A Marketing department seeks to monitor monthly earnings by product and region. A stacked column can illustrate the total revenue for each month, with various segments highlighting each region’s contribution.

Importance: A Stacked column chart enables the comparison of total figures while simultaneously breaking them down into distinct sub-categories, aiding in the understanding of both overall and individual contributions.

Best Practices For Utilizing TOPN

• Begin with Simple Data and Calculations: It is advisable to practice TOPN with smaller datasets to familiarize yourself with the functions and their operations.
• Always Verify Your Results: Data validations are vital. After applying TOPN to your dataset, visualize the results to confirm accuracy.

Conclusion

The TOPN function is a compact tool for Power BI that assists you in determining the TOP N within your data. It is user-friendly and offers various applications for analysis, visualizing that analysis, and decision-making based on that analysis. By swiftly presenting the best N in data, TOPN saves time and directs immediate attention to the most critical aspects. It is an invaluable resource for enhancing effective data-driven decision-making and serves as a beneficial complement for creating impactful reports.

To deepen your knowledge of Power BI and its functionalities, explore this Power BI Course and also check out Power BI Interview Questions curated by industry experts.

TOPN DAX Function in Power BI – FAQs

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