Power BI Charts Types and Explained

Introduction

Step into a world of data with Power BI's interactive charts. Think of data as a vast landscape full of secrets. Power BI lets you explore this data landscape like an adventurer. Start with one chart, and when you click, hover, or scroll, it reacts, showing you new things. It's like magic! Clicking allows you to explore the data in greater detail, while scrolling reveals current changes. the power of interaction, where data isn't boring; it's alive and responds to your questions. Come on this adventure with us, where charts tell stories, and you can uncover insights with a simple click.

Key Terms and Concepts

Data Visualization: The representation of data in a graphical or chart format, making it easier to understand and analyze.

Chart Types: many visual representations of data, including maps, scatter plots, bar charts, line charts, pie charts, and more.

Data Points: Individual values or data elements within a dataset that are plotted on a chart.

Axes: The horizontal (X-axis) and vertical (Y-axis) lines on a chart that provide a reference for data points. They have scales to represent data values.

Categories and Values: In Power BI charts, you typically assign data to categories (e.g., time, products) and values (e.g., sales, quantities) to define what the chart represents.

Legends: A key that explains the colors, symbols, or categories used in a chart. Title and Subtitle: Descriptive text that provides context for the chart and its data.

Slicers: Filters or selectors that allow users to interactively control what data is displayed in a chart.

Drill-Down and Drill-Through: The ability to explore more detailed data by clicking on specific data points in a chart. Drill-through allows you to navigate to another page with more information.

Custom Visuals: Custom-developed visualisations that extend the capabilities of Power BI beyond the standard chart types. Data Labels: Numeric or text labels attached to data points on a chart, making it easier to identify and understand the data.

Tooltips: Pop-up information boxes that provide additional context or details when hovering over data points on a chart.

Aggregation: The process of summarizing data, such as calculating totals, averages, or counts, to provide a high-level view of information. Stacked and

Clustered Charts: Different ways to display multiple data series on a chart, where stacked charts show values on top of each other, and clustered charts place them side by side.

Trendlines: Lines or curves added to charts to represent patterns or trends in data, such as a linear regression line.

Color Coding: Assigning different colors to data points or categories to visually distinguish them.

Conditional Formatting: Changing the appearance of data points based on certain conditions, like highlighting outliers in a different colour. Combo Charts: Charts that combine different chart types (e.g., bar and line) to represent multiple aspects of data in a single chart.

Hierarchical Data: Organizing data into hierarchies, such as time (year, quarter, month, day), for more in-depth analysis.

Data Labels: Adding labels directly to data points in a chart to display specific values or names.

Stakeholders: The individuals or teams who will use and benefit from the insights derived from Power BI charts.

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Types of Charts in Powerbi

Column Chart

A column chart is a straightforward and commonly used data visualisation tool that displays data in a series of vertical bars or columns, each representing a category or data point. The height of each column is proportional to the value it represents, allowing for easy visual comparison between different categories or data sets. Column charts are especially effective in showing relative sizes, trends, and disparities in data. They are versatile and can be used for various data types, making them a fundamental tool for visualising and understanding data in fields such as business, finance, marketing, and more. In Power BI, you can easily create and customise column charts to present your data in a clear and informative manner.

Steps to create a column chart -

• Open Power BI.
• Connect to your data source.
• Go to the "Report" view.
• Select the "Clustered Column Chart" from the "Visualisations" pane.
• Assign category and value fields.
• Customize your chart's appearance.
• Add titles and labels.
• Make the chart interactive.
• Save your report.
• Publish or share as needed.

Bar Chart

A bar chart compares values within various categories or data points using horizontal bars as a visual representation of the data.

The length of each bar is proportional to the value it represents, making it a useful tool for visualising and comparing data easily. Bar charts are effective in showing relative sizes, trends, and disparities in data, similar to column charts. They are commonly used to present data where categories are often lengthy labels or when there is a need to emphasise the horizontal aspect of data presentation.

Steps for Creating a Bar Chart in Power BI:

• Open Power BI. Connect to your data source.
• Navigate to the "Report" view.
• Choose the "Line Chart" option from the "Visualizations" pane.
• Assign the category field to the "Axis" area (typically the X-axis), which represents time or a sequence.
• Assign the value field to the "Values" area (typically the Y-axis), showing the data values.
• Customize your chart by adjusting formatting, labels, and titles in the "Format" options.
• Enhance interactivity by adding slicers, filters, or tooltips as needed.
• Save your report.
• Publish or share your report as required.

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Line Chart

Using a succession of data points connected by straight lines, a line chart is a technique for data visualization.

It's particularly useful for showing trends, changes over time, and continuous data relationships. Line charts are excellent for visualizing data with sequential or time-based categories along the x-axis and corresponding values along the y-axis. They make it easy to identify patterns, fluctuations, and relationships within the data.

Steps for Creating a Line Chart in Power BI:

• Open Power BI. Connect to your data source.
• Navigate to the "Report" view.
• Choose the "Line Chart" option from the "Visualizations" pane.
• Assign the category field to the "Axis" area (typically the X-axis), which represents time or a sequence.
• Assign the value field to the "Values" area (typically the Y-axis), showing the data values.
• Customize your chart by adjusting formatting, labels, and titles in the "Format" options.
• Enhance interactivity by adding slicers, filters, or tooltips as needed.
• Save your report.
• Publish or share your report as required.

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Area Chart

An area chart is a type of data visualization that is similar to a line chart but has a colored area below the line that may be used to demonstrate both the trend of the data as well as its overall impact over time or across categories.

Area charts are effective for visualizing the distribution of data or for comparing the contribution of individual components to a whole.

Steps for Creating an Area Chart in Power BI:

• Open Power BI.
• Connect to your data source. Head to the "Report" view.
• Select the "Area Chart" option from the "Visualizations" pane.
• Assign the category field to the "Axis" area (usually the X-axis), representing time or a sequence.
• Assign the value field to the "Values" area (usually the Y-axis), displaying data values.
• Customize your chart by adjusting formatting, labels, and titles in the "Format" options. Add any required interactivity elements such as slicers, filters, or tooltips.
• Save your report.
• Publish or share your report as necessary

Pie Chart

Using slices or segments to show the percentage of each category inside the total, a pie chart is a circular data visualization tool. It is simple to see how the relative distribution of data is distributed because each slice's size is proportionate to the quantity it reflects.

Pie charts are useful for displaying the composition of a whole and showing the relationship between parts and the whole.

• Data Preparation: Ensure your data is structured with categories and corresponding values, typically representing proportions or percentages.
• Open Power BI: Launch Power BI Desktop.
• Connect to Data: Import your data source.
• Create a New Report: Go to the "Report" view.
• Select Pie Chart: In the "Visualizations" pane, choose "Pie Chart."
• Assign Data: Drag the category field to "Values" and the value field to "Legend."
• Customize Appearance: Adjust colors, labels, and data labels using the "Format" tab.
• Add Titles and Labels: Include a title and data labels for context.
• Interactivity (if needed): Enhance interactivity with tooltips or slicers.
• Save Your Report: Save your Power BI report.

Donut Chart

An alternative to the common pie chart is a donut diagram.

It displays data in a circular shape with a hole (like a donut) in the center. Donut charts are useful for showing the relationship between parts and the whole, much like pie charts. However, they can be more visually appealing and offer some advantages over traditional pie charts, such as the ability to display additional data series within the same chart.

Steps for Creating a Donut Chart in Power BI:

• Data Preparation: Ensure your data is well-structured with categories and corresponding values, typically representing proportions or percentages.
• Open Power BI: Launch Power BI Desktop.
• Connect to Data: Import your data source.
• Create a New Report: Go to the "Report" view. Select the Donut Chart: In the "Visualizations" pane, choose the "Donut Chart" option. This creates an empty donut chart on your report canvas.
• Assign Data to the Chart: In the "Fields" pane, drag and drop the category field to "Values," and the value field to "Legend." This setup will create a basic donut chart showing proportions.
• Customize Your Chart: Customize the appearance of your donut chart, including colors, labels, and data labels, using the "Format" tab in the "Visualizations" pane.
• Add Titles and Labels: Include a title and data labels to provide context and enhance the readability of your donut chart.
• Interactivity (if needed): Enhance interactivity with tooltips or slicers.
• Save Your Report: Save your Power BI report.

Bubble Chart

A data visualization that goes beyond conventional two-dimensional charts is a bubble chart.

It represents data using bubbles or circular markers in a three-dimensional format, typically illustrating three variables: the x-axis, the y-axis, and the size of the bubbles. The bubble's position on the x and y axes corresponds to two data values, while the bubble's size represents a third data variable. Bubble charts are useful for visualizing and comparing data points with varying values across three dimensions.

Steps for Creating a Bubble Chart in Power BI:

• Data Preparation: Ensure your data is well-structured with three variables: x-axis values, y-axis values, and bubble sizes, representing different aspects of your data.
• Open Power BI: Launch Power BI Desktop.
• Connect to Data: Import your data source. Create a New Report: Go to the "Report" view.
• Select the Bubble Chart: In the "Visualizations" pane, choose the "Bubble Chart" option. This creates an empty bubble chart on your report canvas.
• Assign Data to the Chart: In the "Fields" pane, drag and drop the appropriate fields from your dataset into the bubble chart:
• Assign the x-axis values field to "Axis" (usually the X-axis).
• Assign the y-axis values field to "Axis" (usually the Y-axis).
• Assign the bubble sizes field to "Size," which determines the size of the bubbles.
• Customize Your Chart: Customize the appearance of your bubble chart, including colors, labels, and data labels, using the "Format" tab in the "Visualizations" pane.
• Add Titles and Labels: Include a title and labels for the x-axis, y-axis, and bubble size to provide context and enhance the readability of your chart. Interactivity (if needed): Enhance interactivity with tooltips or slicers. Save Your Report: Save your Power BI report.

Waterfall Chart

A data visualization tool called a waterfall chart displays the overall impact of successively inputted positive or negative values.

It is particularly effective for displaying financial data, budget analysis, and identifying the impact of each value in a sequence. The chart's bars or columns visually "flow" from one value to another, showing the cumulative effect.

Steps for Creating a Waterfall Chart in Power BI:

• Data Preparation: Ensure your data is organized with the necessary variables for creating a waterfall chart. This typically includes a sequence of categories and corresponding positive and negative values.
• Open Power BI: Launch Power BI Desktop.
• Connect to Data: Import your data source.
• Create a New Report: Go to the "Report" view.
• Select the Waterfall Chart: In the "Visualizations" pane, choose the "Waterfall Chart" option. This creates an empty waterfall chart on your report canvas.
• Assign Data to the Chart: In the "Fields" pane, drag and drop the category field to the "Category" area, the value field to the "Y" area, and any additional fields representing positive or negative values to the respective areas.
• Customize Your Chart: Customize the appearance of your waterfall chart, including colors, labels, and data labels, using the "Format" tab in the "Visualizations" pane.
• Add Titles and Labels: Include a title and labels for the x-axis and y-axis to provide context and enhance the readability of your chart.
• Interactivity (if needed): Enhance interactivity with tooltips or slicers.
• Save Your Report: Save your Power BI report.

Funnel Chart

A funnel chart is a type of data visualization used to show how data is gradually reduced at each stage of a process.

It is commonly used for visualizing sales or marketing funnels, showing the number of potential customers at each stage of the sales or conversion process. Funnel charts are effective for identifying where drop-offs occur in the process.

Steps for Creating a Funnel Chart in Power BI:

• Data Preparation: Ensure your data is well-structured with stages or categories and corresponding numerical values representing the number of entities at each stage.
• Open Power BI: Launch Power BI Desktop. Connect to Data: Import your data source. Create a New Report: Go to the "Report" view. Select the Funnel Chart: In the "Visualizations" pane, choose the "Funnel Chart" option. This creates an empty funnel chart on your report canvas.
• Assign Data to the Chart: In the "Fields" pane, drag and drop the stage or category field to the "Axis" area, and the numerical value field to the "Values" area.
• Customize Your Chart: Customize the appearance of your funnel chart, including colors, labels, and data labels, using the "Format" tab in the "Visualizations" pane.
• Add Titles and Labels: Include a title and labels to provide context and enhance the readability of your chart.
• Interactivity (if needed): Enhance interactivity with tooltips or slicers. Save Your Report: Save your Power BI report.

Radar Chart

A spider chart, commonly referred to as a radar chart or star plot, is a type of data visualization that a two-dimensional chart with three or more quantitative variables that shows multivariate data shown on axes radiating outward from a central point.

Each variable is represented by a different axis, and data points are plotted along these axes to show how each variable relates to others. Radar charts are effective for visualizing and comparing data across multiple categories or variables.

Steps for Creating a Funnel Chart in Power BI:

• Data Preparation: Ensure your data is well-structured with multiple variables that you want to compare across different categories or data points. Open Power BI: Launch Power BI Desktop.
• Connect to Data: Import your data source. Create a New Report: Go to the "Report" view to start building your visualizations.
• Select Radar Chart (Custom Visual): As of my last knowledge update in September 2021, Power BI does not offer a built-in radar chart, but you can use custom visuals available in the Power BI Marketplace. To use a radar chart, you may need to download a custom visual, import it into Power BI, and then select it from the "Visualizations" pane.
• Assign Data to the Chart: In the "Fields" pane, drag and drop the relevant fields for your radar chart. Typically, you would assign each variable to a different axis, and your data points to categories or data series. Customize Your Chart: Customize the appearance of your radar chart, including colors, labels, and data labels using the custom visual's settings and formatting options.
• Add Titles and Labels: Include titles and labels for the axes and data points to provide context and enhance readability.
• Interactivity (if needed): Enhance interactivity with tooltips or slicers. Save Your Report: Save your Power BI report.

Real-time project descriptions where PowerBI Charts can be employed effectively

Project: Sales Performance Analysis for a Retail Company

Project Goal: To analyse the sales performance of a retail company over the past year, identify key trends, and provide actionable insights to improve sales.

Steps in the Project:

Data Collection and Import: Acquire a dataset containing sales data, including information on products, customers, sales transactions, and dates.

Data Cleaning and Transformation: The Power Query Editor in Power BI can be used to clean and alter the data.

Perform tasks such as data type conversion, filtering, and merging datasets.

Data Model Building: Create a data model within Power BI to establish relationships between tables and enable data analysis.

Data Visualization: Utilise various chart types in Power BI to visualize different aspects of sales performance.

Here are some examples:

Line Chart: Show the trend in sales revenue over time.

Column Chart: Display product sales by category.

Pie Chart: Illustrate the distribution of sales by region.

Area Chart: Compare monthly sales for different product categories.

Scatter Plot: Analyse the relationship between the number of customers and sales.

Funnel Chart: Visualise the conversion rate of leads to sales.

Radar Chart: Display performance ratings for sales representatives.

Waterfall Chart: Explain the changes in monthly sales performance.

Bubble Chart: Compare sales, profit, and discount values for products.

Donut Chart: Represent the distribution of sales channels.

Dashboard Creation: Design a user-friendly dashboard with interactive elements such as slicers, filters, and drill-through actions to allow users to explore the data.

Measures and Calculations: Create DAX (Data Analysis Expressions) measures to calculate key performance indicators (KPIs) such as total revenue, profit margin, and year-over-year growth.

Some potential business insights that can be derived from Power BI charts used in a sales data project:

Revenue Trends: Line charts can reveal trends in revenue over time, helping businesses understand seasonal fluctuations and long-term growth patterns.

Product Performance: Column charts can show which products or product categories are top performers and which may need additional marketing or improvement.

Regional Sales: Maps and geospatial visualisations can highlight areas with high and low sales, allowing for targeted marketing and resource allocation.

Customer Segmentation: Pie charts can illustrate the distribution of customers across different segments, aiding in personalized marketing strategies.

Conversion Rates: Funnel charts can depict the conversion rate of leads through the sales funnel, pinpointing areas for improvement.

Sales Representative Performance: Radar charts can help assess the performance of sales representatives based on various criteria, enabling recognition and coaching.

Cost Analysis: Waterfall charts can break down costs and profits, identifying areas where cost reduction or revenue optimization is possible.

Discount Impact: Bubble charts can help understand the relationship between discounts and sales, guiding pricing and discount strategies.

Channel Performance: Donut charts can demonstrate the effectiveness of different sales channels, such as online sales versus in-store sales.

Customer Behaviour: Scatter plots can show how the number of customers relates to sales, enabling businesses to predict future sales based on customer acquisition.

Product Portfolio Management: Treemaps can visualise the contribution of each product to the overall revenue, guiding product portfolio decisions.

Sales Funnel Analysis: Funnel charts can help identify where leads are dropping off in the sales process, allowing for targeted improvements in conversion rates.

Conclusion

In summary, Power BI charts are the vibrant and informative windows through which data comes to life. These charts are not just data visualisations; they're vital tools for gaining insights, making data-driven decisions, and telling compelling stories. To explore the wide range of chart types available in Power BI, from simple line charts tracking trends over time to complex radar charts evaluating multivariate data. Power BI charts empower businesses to navigate their data landscapes with clarity, revealing hidden patterns, guiding actions, and driving success. In order to see how they might assist organizations in seizing opportunities, reducing risks, and realizing the full potential of their data, they bridge the gap between raw data and actionable intelligence. In the age of data-driven decision-making, Power BI charts are the compass that steers enterprises toward a more informed, productive, and prosperous future."