Lesson 31 - Q and A Visual in Power BI Desktop

Q and A visual allows users to ask in plain English and get answers in the form of visuals. Through Natural language processing capabilities, it understands users queries and generate visualizations based on the data.

How to Proceed?

Step 1 

Launch power BI desktop app and open the new report page and import the data required. 

Refer Lesson 7 - Power BI Datasets to build great visuals 

Step 2 

In “Visualizations” pane click on “Q and A” which is highlighted in the given figure

Step 3

Main advantage of Q and A visual is that it can understand complete sentences or shorter phrases too. It can give suggestions based on the data which makes easier for us to phrase questions. 

When we type question, the fields get recognized by power BI and field will be underlined in blue color and unrecognized words will be underlined in red

Type question in the “Ask a question about your data” box, it will show some suggestions by default or you can pick from pre prepared questions. Click on more suggestions option at the bottom to get more questions.

Here I choosed pre prepared question from the list of suggestion. By default Q and A visual shows best suited visual for the question asked about data. If you want specific chart type add “as” along with the end of the question followed by chart type.

Step 4

Creating standard visual from Q and A visual

We can convert the Q and A visual to a standard visual by click on the icon on the top right corner. Once the visual get converted to a standard visual you can make required visual settings to the chart.

Step 5: Setup the Q and A visual

Click on the settings icon to set up questions.

Click on the suggest questions and frame questions. click add and save.

Add synonyms

Adding synonyms helps power BI recognize the words related to field. For E.g., region can also be asked as countries, we can add or remove related terms for a field.

By default, power BI shows synonyms suggestions based on the words used.

Teach Q and A 

Type questions in plain English and click submit.

Step 6 Save the visual

Finally, your Q and A is ready. Click save button to save the visual. 

When to use Q and A visual?

When we want to produce insights quickly, we can go for Q and A visual and also it can be used to give answers in real time when we ask questions.

Pros

• Enables users to interact with data
• User friendly
• Automatically create visualizations which saves time and effort.
• Quick and intuitive data exploration

Cons

• Limited Customization
• May have performance issues when converting complex queries to visualizations.
• We have to setup proper synonyms to get visuals correctly.

Conclusion

The Q&A visual in Power BI is a powerful tool for interactive and user-friendly data exploration. Its natural language querying capabilities make it accessible to users to derive insights and visualize data dynamically.

Tags	Power BI
Useful links	https://www.acuitytraining.co.uk/news-tips/qa-visual-in-power-bi/
MS Learn Modules	https://learn.microsoft.com/en-us/power-bi/visuals/power-bi-visualization-q-and-a?tabs=powerbi-desktop
Test Your Knowledge	Quiz

Lesson 30 - 100% Stacked Column Chart in Power BI Desktop

A 100% Stacked column chart is a type of visual that displays multiple series of data in vertical columns. Each column represents a category, and the height of the column illustrates the total value of the data in percentage for that category. 

The difference between 100% Stacked column chart with regular Stacked column is that it displays each column as a percentage of the whole, allowing for easy comparison of the relative proportions within each category across different groups or variables.

How to proceed?

Step 1

Launch power BI desktop app and open the new report page and import the data required. 

Refer Lesson 7 - Power BI Datasets to build great visuals

Step 2

In “visualizations” pane click on “100% Stacked Column chart” which is highlighted in the given figure.

Step 3

Drag the data fields into “Field Section” that you want to analyze using 100% Stacked column chart.

  

X axis: Represent categories or groups that you want to compare - Year

Y axis: Represents numerical value that you want to display within each category or group in X-axis– Number of Participants

Legend: Represents sub-categories within each group displayed on X-axis. Subcategories are visually stacked within each column - Gender.

Step 4

Filters in 100% stacked column chart enable users to selectively focus on specific categories or subcategories of data for deeper analysis.

By filtering the data specifically for the year range from 2000 to 2016, I'm focusing on analyzing information within this defined time period. This selection allows for a more detailed examination of trends, patterns, and insights that occurred between 2000 and 2016, providing a more targeted and precise analysis of the data.

Step 5

Customize the appearance.

You can customize the appearance of the visual.  You can change Title, Font size, Style, Colors and Data labels. Click anywhere on the visual and set the below properties in the Format section.

Refer Lesson 6 - Formatting the visuals in Power BI Desktop

You are allowed to choose colors for sub-categories to differentiate them. This improves clarity and helps viewers easily identify and understand the distinctions between various sub-categories within your chart, all displayed as percentages relative to the whole.

“Reverse stacked order” option allows you to rearrange the order of data series easily. 

Data labels represent the exact percentages of each part in the column. These labels provide direct information about the specific contribution of each segment or category to the whole, making it easier for viewers to comprehend and compare the proportions of various components within the chart.

you can customize the orientation, position, and density of the data labels in a 100% stacked column chart. This customization allows you to control how and where the labels appear, their angle or orientation, the precise positioning within or outside the columns, and the density or frequency of these labels. 

Adjusting these settings can help optimize the readability and presentation of the information within the chart, tailoring it to meet specific preferences or requirements.

Step 6

Save the visual

Finally, your 100% Stacked column chart is ready. Click save button to save the visual.

When to use 100% Stacked column chart?

You can use 100% Stacked column chart for following scenarios.

• When your aim is to visualize and comprehend the distribution of data within each category or group in terms of percentages or proportions.
• Effective for showcasing how each part contributes to the total across different categories or groups.

Pros

• It enables straightforward comparison of proportions across various categories or groups.
• Shows how each part adds up to the whole, helping to understand differences and patterns in the data.

Cons

• When dealing with numerous categories or groups, a 100% stacked column chart can become visually complex, potentially making it harder read the information, especially if there are many segments or categories represented in the chart.
• It does not represent actual values or exact numbers since it focuses more on proportions relative to the whole.

Conclusion

The 100% stacked column chart is great for comparing parts within groups. It shows how each piece makes up the whole as percentages. People in business, finance, marketing, and statistics use it to compare things quickly. It helps to see patterns and differences in data, making it useful for making decisions based on the information.

Tags	Power BI
Useful links	Power BI - 100% Stacked Column Chart - Power BI Docs
MS Learn Modules	Visualization types in Power BI - Power BI | Microsoft Learn
Test Your Knowledge	Quiz

Lesson 29 - Clustered Bar Chart in Power BI Desktop

A clustered bar chart is a type of graph that represents data in vertical bars. Each bars represents a different category or group, and the height of the bar corresponds to the value of the data it represents.

How to Proceed?

Step 1

Launch power BI desktop app and open the new report page and import the data required. 

Refer Lesson 7 - Power BI Datasets to build great visuals

Step 2

In “visualizations” pane click on “clustered bar chart” which is highlighted in the given figure.

Step 3

 

Drag the data fields into “Field Section “that we want to compare and analyze. 

Y axis:  represent categories – Continent

X axis: Shows the values – Medal Count

Legend: Explain the groups in clustered column chart – Medal

Step 4

Filters in 100% stacked bar chart enable users to selectively focus on specific categories or subcategories of data for deeper analysis.

Here I applied basic filter eliminating NA in continent and for Medals eliminated No medal category

Step 5

Customizing the appearance of clustered bar chart

You can customize the appearance of the visual.  You can change Title, Font size, Style, Colours and Data labels. Click anywhere on the visual and set the below properties in the Format section.

Refer Lesson 6 - Formatting the visuals in Power BI Desktop

In this visual, I chose background colour as blue and gave 87% transparency which reduces the intensity of the colour. 

Gave suitable title for the visual and customize the font size, colour and position of the title.

Chose colours for the vertical bars to show different categories.

To add data labels to the bar chart, click on the “Data Labels” section under “Visual”. Here you can choose which data to display in the labels and adjust their position, font, and color.

In this visual, I chose to display “All” data labels are placed outside at the end which shows the values on each bar. 

Step 6 Save the visual

Finally, your Clustered bar chart is ready. Click save button to save the visual.

When to use Clustered bar chart?

You can use Clustered bar charts to compare data points within discrete categories or display multiple data series side by side. Here are some scenarios when to use clustered bar chart effectively

• Analyzing time series data for categorical variables
• Comparing multiple metrics for different categories

Pros

• Clustered bar chart allows users to compare multiple data series side by side. This makes it easy to see patterns and trends in the data.
• It helps users to group data based on categories, allowing them to logically organize and present information.
• Best suits for explaining categorical data with distinct groups.
• Clustered bar charts enhance the visual appeal of reports and presentations, making them more engaging for the audience.

Cons

• Using clustered bar charts to handle time series data may not be the most effective approach.
• When the differences between data points are small, it can be challenging to visually compare the heights of the columns accurately.
• When dealing with large number of categories, the chart becomes crowded and difficult to read.
• They might not be ideal for representing continuous data with wide range of values.

Conclusion 

Bar charts are a user-friendly and popular way to visualize data. They effectively display trends, comparisons, and patterns, making complex information easier to grasp. Whether you're examining sales figures, survey results, or any data with clear categories, column charts are a valuable tool to present information clearly.

Tags	Power BI
Useful links	https://www.geeksforgeeks.org/power-bi-format-clustered-bar-chart///
MS Learn Modules	Visualization types in Power BI - Power BI | Microsoft Learn
Test Your Knowledge	Quiz

Lesson 28 - Stacked bar chart in Power BI Desktop

A stacked bar chart is a visual representation that uses horizontal bars to display data. Each bar represents a category or group, and it is divided into segments to depict subcategories or individual components of the data. It helps illustrate the composition of a whole while showing the contribution of individual parts.

How to Proceed?

Step 1

Launch power BI desktop app and open the new report page and import the data required. 

Refer Lesson 7 - Power BI Datasets to build great visuals 

Step 2

In “visualizations” pane click on “Stacked bar chart” which is highlighted in the given figure.

Step 3

Drag the data fields into “Field Section “that you want to analyze 

using the stacked bar chart.

Y-axis: Represent categories or groups that you want to compare - Continent

X-axis: Represents numerical value that you want to display within each category or group in X-axis – Medal Count

Legend: Represents sub-categories within each group displayed on Y-axis. Subcategories are visually stacked within each bar - Gender

Step 4

Filters in 100% stacked bar chart enable users to selectively focus on specific categories or subcategories of data for deeper analysis.

Here I applied basic filter eliminating NA in continent and for Medals eliminated No medal category

Step 5

Customizing the appearance

You can customize the appearance of the visual.  You can change Title, Font size, Style, Colours and Data labels. 

Click anywhere on the visual and set the below properties in the Format section.

Refer Lesson 6 - Formatting the visuals in Power BI Desktop

You are allowed to choose colours for sub-categories to differentiate them. This improves clarity and helps viewers easily identify and understand the distinctions between various sub-categories within your chart.

“Reverse stacked order” option allows you to rearrange the order of data series easily. 

Spacing refers to the gap or distance between individual columns or bars within the chart. Adjusting the spacing can impact the overall appearance and readability of the chart.

Data labels are used to display specific numerical values associated with each individual stack within each bars. You can adjust the font, colour and position of the data labels within the chart. 

Total labels represent the sum or total value of all the individual segments in a given bars. This label shows combined value of all the sub-categories within each category.

In this figure, I have highlighted total labels using red-colored circles.

Step 6 Save the visual

Finally, your Stacked bar chart is ready. Click save button to save the visual.

When to use Stacked bar chart?

Stacked bar chart and a stacked column chart in Power BI is chosen by number of categories, the length of category names, and the visual preferences of the clients. Both charts serve the purpose of illustrating the composition of total values, but the orientation differs based on whether we are using bars or columns.

• When we want to track changes on data composition over a period of time, you can use stacked bar chart.
• To  enhance the ability to spot patterns, anomalies, or trends in data composition more effectively, utilize the  color-coded segments in a stacked bar chart.

Pros

• Stacked bar charts are easy to make and understand, so wide audience can use them. 
• Effectively displays trends over a period, especially when a time series is placed on the X-axis.
• The automatic aggregation of values within each category simplifies the presentation of cumulative data.

Cons

• We may get confused if the bar stacks have 4 or 5 layers.
• It is difficult to read the values when we have too many bars

Conclusion

Stacked bar charts are a useful visualization tool for displaying proportions ,tracking trends over time and highlighting relative compositions within datasets. Whether you are analyzing budget breakdowns, sales distribution, or market segment compositions, a stacked bar chart often serves as the most effective visualization tool.

Tags	Power BI
Useful links	https://www.geeksforgeeks.org/power-bi-create-a-stacked-bar-chart///
MS Learn Modules	Visualization types in Power BI - Power BI | Microsoft Learn
Test Your Knowledge	Quiz

Lesson 27 - 100% Stacked Bar Chart in Power BI Desktop

A 100% Stacked Bar chart is a type of visual that displays multiple series of data in horizontal bars. Each column represents a category, and the height of the bar illustrates the total value of the data in percentage for that category.

The difference between 100% Stacked bar with regular bar chart is that it displays each bar as a percentage of the whole, allowing for easy comparison of the relative proportions within each category across different groups or variables.

How to Proceed?

Step 1

Launch power BI desktop app and open the new report page and import the data required. 

Refer Lesson 7 - Power BI Datasets to build great visuals

Step 2

In “visualizations” pane click on “100% Stacked bar chart” which is highlighted in the given figure. 

Step 3

Drag the data fields into “Field Section” that you want to analyze

using 100% stacked Bar chart

Y axis: Represent categories or groups that you want to compare - Continent

X axis: Represents numerical value that you want to display within each category or group in X-axis– Medal count

Legend: Represents sub-categories within each group displayed on Y-axis. Subcategories are visually stacked within each bars- Medal

Step 4

Filters in 100% stacked bar chart enable users to selectively focus on specific categories or subcategories of data for deeper analysis.

Here I applied basic filter eliminating NA in continent and for Medals eliminated No medal category

Step 5

Customize the appearance

You can customize the appearance of the visual.  You can change Title, Font size, Style, Colours and Data labels. Click anywhere on the visual and set the below properties in the Format section.

Refer Lesson 6 - Formatting the visuals in Power BI Desktop

You are allowed to choose colours for sub-categories to differentiate them. This improves clarity and helps viewers easily identify and understand the distinctions between various sub-categories within your chart, all displayed as percentages relative to the whole. 

“Reverse stacked order” option allows you to rearrange the order of data series easily. 

Data labels represent the exact percentages of each part in the bar. These labels provide direct information about the specific contribution of each segment or category to the whole, making it easier for viewers to comprehend and compare the proportions of various components within the chart.

you can customize the orientation, position, and density of the data labels in a 100% stacked bar chart. This customization allows you to control how and where the labels appear, their angle or orientation, the precise positioning within or outside the columns, and the density or frequency of these labels. 

Adjusting these settings can help optimize the readability and presentation of the information within the chart, tailoring it to meet specific preferences or requirements.

Step 6 Save the visual

Finally, your 100% Stacked bar chart is ready. Click save button to save the visual.

When to use 100% Stacked bar chart?

The main difference between 100% stacked column chart and 100% stacked bar chart is in the orientation (vertical columns vs. horizontal bars) and the way the data is visually presented while it still maintains the concept of a 100% stacked chart where each part contributes to the whole. 

The choice between the two types of charts often depends on the specific data and the visual representation that best communicates the intended message.

You can use 100% Stacked bar chart for following scenarios.

when your aim is to visualize and comprehend the distribution of data within each category or group in terms of percentages or proportions.

Effective for showcasing how each part contributes to the total across different categories or groups.

Pros

• It enables straightforward comparison of proportions across various categories or groups.
• Shows how each part adds up to the whole, helping to understand differences and patterns in the data.

Cons

• When dealing with numerous categories or groups, a 100% stacked bar chart can become visually complex, potentially making it harder read the information, especially if there are many segments or categories represented in the chart.
• It does not represent actual values or exact numbers since it focuses more on proportions relative to the whole.

Conclusion

The 100% stacked bar chart is great for comparing parts within groups. It shows how each piece makes up the whole as percentages. People in business, finance, marketing, and statistics use it to compare things quickly. It helps to see patterns and differences in data, making it useful for making decisions based on the information.

Tags	Power BI
Useful links	https://powerbidocs.com/2020/01/25/power-bi-100-stacked-bar-chart/#google_vignette
MS Learn Modules	Visualization types in Power BI - Power BI | Microsoft Learn
Test Your Knowledge	Quiz

Lesson 26 - Clustered Column Chart in Power BI Desktop

A clustered column chart is a type of graph that represents data in vertical bars. Each column represents a different category or group, and the height of the column corresponds to the value of the data it represents.

How to proceed?

Step 1

Launch power BI desktop app and open the new report page and import the data required. 

Refer Lesson 7 - Power BI Datasets to build great visuals

Step 2

In “visualizations” pane click on “clustered column chart” which is highlighted in the given figure.

Step 3

Drag the data fields into “Field Section “that we want to compare and analyze.

X axis-  represent categories – Region & Medal

Y axis- Shows the values - Medals

Legend- Explain the groups in clustered column chart – Medal

Step 4

Filters in the chart are like special tools that allow us to focus on specific parts of the data, making it easier to understand. 

Here, I used filters in ‘medal’ (Chose only Gold, Bronze and Silver) and in ‘Region’ (Top 7 countries which has highest medal count).          

Using the Filters Pane, you can focus on the Top 7 countries and see the type of medal each of them won. It helps us easily view and analyze the specific achievements of these countries in the Olympic Games.

Step 5

Customizing the appearance of clustered column chart

You can customize the appearance of the visual.  You can change Title, Font size, Style, Colors and Data labels. Click anywhere on the visual and set the below properties in the Format section.

Refer Lesson 6 - Formatting the visuals in Power BI Desktop

In this demo, I chose background color as blue and gave 87% transparency which reduces the intensity of the color.

Gave suitable title for the visual and customize the font size, color and position of the title.

Chose colors for the vertical bars to show different categories.

To add data labels to the column chart, click on the “Data Labels” section under

“Visual”. Here you can choose which data to display in the labels and adjust their position, font, and color.

In this demo, I chose to display “All” data labels in “Horizontal” orientation and its placed outside at the end which shows the values above each bar. 

Step 6

Save the visual

Finally, your Column chart is ready. Click save button to save the visual.

When to use Clustered column chart?

You can use Clustered column charts to compare data points within discrete categories or display multiple data series side by side. Here are some scenarios when to use clustered column chart effectively.

• Analyzing time series data for categorical variables
• Comparing multiple metrics for different categories

Pros

• Clustered column chart allows users to compare multiple data series side by side. This makes it easy to see patterns and trends in the data.
• It helps users to group data based on categories, allowing them to logically organize and present information.
• Best suits for explaining categorical data with distinct groups.
• Clustered column charts enhance the visual appeal of reports and presentations, making them more engaging for the audience.

Cons

• Using clustered column charts to handle time series data may not be the most effective approach.
• When the differences between data points are small, it can be challenging to visually compare the heights of the columns accurately.
• When dealing with large number of categories, the chart becomes crowded and difficult to read.
• They might not be ideal for representing continuous data with wide range of values.

Conclusion

Column charts are a user-friendly and popular way to visualize data. They effectively display trends, comparisons, and patterns, making complex information easier to grasp. Whether you're examining sales figures, survey results, or any data with clear categories, column charts are a valuable tool to present information clearly.

Tags	Power BI
Useful links	Clustered column chart in Power BI - Power BI Docs
MS Learn Modules	Visualization types in Power BI - Power BI | Microsoft Learn
Test Your Knowledge	Quiz

Lesson 25 - Stacked Column chart in Power BI Desktop

 A stacked column chart is a visual representation that uses vertical columns to display data. Each column represents a category or group, and it is divided into segments to depict subcategories or individual components of the data. It helps illustrate the composition of a whole while showing the contribution of individual parts.

How to proceed?

Step 1

Launch power BI desktop app and open the new report page and import the data required. 

Refer Lesson 7 - Power BI Datasets to build great visuals

Step 2

In “visualizations” pane click on “Stacked column chart” which is highlighted in the given figure.

Step 3

Drag the data fields into “Field Section “that you want to analyze.  
using the stacked column chart.

X-axis: Represent categories or groups that you want to compare - Country

Y-axis: Represents numerical value that you want to display within each category or group in X-axis – Number of Participants

Legend: Represents sub-categories within each group displayed on X-axis. Subcategories are visually stacked within each column - Gender.

Step 4

Filters in a stacked column chart enable users to selectively focus on specific categories or subcategories of data for deeper analysis.

Here, I utilized a "Top N" filter, specifying "Bottom" as the selection in "Show items" and set the number to 6 to display the six countries with the fewest participants.

The "By value" option enables us to filter data based on specific conditions. In this case, I used it to filter out the bottom 6 countries with low participant counts.

Step 5

Customizing the appearance

You can customize the appearance of the visual.  You can change Title, Font size, Style, Colors and Data labels. Click anywhere on the visual and set the below properties in the Format section.

Refer Lesson 6 - Formatting the visuals in Power BI Desktop

You are allowed to choose colors for sub-categories to differentiate them. This improves clarity and helps viewers easily identify and understand the distinctions between various sub-categories within your chart.

“Reverse stacked order” option allows you to rearrange the order of data series easily. 

Spacing refers to the gap or distance between individual columns or bars within the chart. Adjusting the spacing can impact the overall appearance and readability of the chart.

Data labels are used to display specific numerical values associated with each individual stack within each column. You can adjust the font, color and position of the data labels within the chart.

Total labels represent the sum or total value of all the individual segments in a given column. This label shows combined value of all the sub-categories within each category.

In this figure, I have highlighted total labels using red-colored circles and data labels with blue-colored circles.

Step 6

Save the visual

Finally, your Stacked column chart is ready. Click save button to save the visual.

When to use Stacked column chart?

Stacked column charts are used when you want to visually represent the composition of data points or categories by stacking segments to show how they contribute to the whole. You can use the stacked column chart for following scenarios.

• When you want to analyze and contrast various categories or subcategories within a dataset.
• When you want to track changes on data composition over a period of time, you can use stacked column chart.
• To enhance the ability to spot patterns, anomalies, or trends in data composition more effectively, utilize the color-coded segments in a stacked column chart.

Pros

• Stacked column charts are easy to make and understand, so wide audience can use them. 
• Effectively displays trends over a period, especially when a time series is placed on the X-axis.
• The automatic aggregation of values within each category simplifies the presentation of cumulative data.

Cons

• Stacking can lead to loss of precision in showing each separate piece of data because the values are aggregated.
• Using excessive subcategories in a stacked column chart can result in confusion and misunderstanding.
• When dealing with a large number of categories over time, the chart can appear crowded and become challenging to comprehend.

Conclusion

Stacked column charts are a useful visualization tool for displaying proportions, tracking trends over time and highlighting relative compositions within datasets. Whether you are analyzing budget breakdowns, sales distribution, or market segment compositions, a stacked column chart often serves as the most effective visualization tool.

Tags	Power BI
Useful links	Power BI - Stacked Column Chart Example - Power BI Docs
MS Learn Modules	Visualization types in Power BI - Power BI | Microsoft Learn
Test Your Knowledge	Quiz