Dashboards

Vertical Bar Charts

A vertical bar chart is a chart where categories are displayed along the y-axis, and corresponding values are represented by horizontal bars extending across the x-axis. This format is particularly useful when dealing with long category labels, as it provides better readability compared to vertical bar charts. allowing users to quickly interpret trends and differences across categories. Create a Chart to add a new chart: 1. Within the table, click on the "+" sign above the search bar. 2. From the drop-down menu, select Chart view. 3. A box will appear to enter a name for the view—choose a descriptive name that reflects its content. 4. Select who can edit: - Collaborative for team access and editing. - Personal for individual use. note: you can't add it in dashboards 5. Click "Add". 6. Click Chart type . 7. from the list Choose Horizontal Bar Chart Chart. Building a Horizontal Bar Chart To create a horizontal bar chart, users must configure the following components: Configuring a Horizontal Bar Chart: Example - Monthly Budget Analysis To illustrate how to create a horizontal bar chart, let's build one that captures our monthly budget. - For the x-axis, we will select Transaction Date and adjust the granularity to monthly to track income trends over time. - For the y-axis, we will choose Actual Income with the Sum measure to calculate total earnings per month. - To add more context, we will apply a breakdown by Income Type, allowing us to visualize income sources within each month. 1. Define the X-Axis (Categories) - from the drop-down list choose a Column to Represents the grouping of data points. - In this example, we use Transaction Date, adjusting the granularity to monthly for time-based analysis. 2. Define the Y-Axis (Values) - from the drop-down list choose a Column to Represents the numerical values being measured. - We select Actual Income, applying the Sum measure to calculate total earnings. 3. Apply a Breakdown (Optional) - from the drop-down list choose a Column to Segments the data within each bar for deeper insights. - In this case, breaking down by Income Type provides a clearer view of different income sources each month. - Sorting is disabled when a breakdown is applied. This setup ensures a structured and meaningful representation of income trends, making it easier to track and analyze financial performance over time. Comparing Multiple Values (Y-Axis): To compare Actual Income with Estimated Income, follow these steps: 1. Remove the breakdown (if previously applied) to allow a side-by-side comparison. 2. From the y-axis dropdown list, choose "Estimated Income" as the second measure. 3. Apply the "Sum" measure to ensure the total estimated income is calculated for each month. Now, your monthly-based horizontal bar chart will display both Actual Income and Estimated Income, making it easy to spot differences, analyze trends, and assess financial performance at a glance. Available Measures Based on Column Types When selecting a y-axis column, different measurement options become available: For Numeric Columns - Count – Counts the number of entries in the selected column. - Sum – Adds up all numerical values. - Avg – Calculates the average of the values. - Min/Max – Retrieves the smallest or largest value in the dataset. For Non-Numeric Columns - Count ONLY – Non-numeric columns can only be counted. - Number formatting always follows the column setup within the table. Customization & Features The platform offers various customization options to enhance horizontal bar charts: Sorting & Highlighting - Sort Values: - Sorts values in ascending or descending order based on the y-axis measurement. - Sorting is disabled when a breakdown is applied. - Highlight Values: - Enables highlighting of the maximum and minimum values in the dataset. Design Customization - Column Background: - Users can add a background color for each bar segment. - Show Legend: - Displays a legend for better readability, especially useful when a breakdown is applied. - Normalization: - Ensures values are scaled proportionally for accurate comparisons. - Color Customization: - Users can change the color palette or customize bar colors individually to match specific preferences. Filter a Horizontal Bar Charts: Within the view, click on the funnel icon in the view bar. 1. A box will appear; click on "Add filter." 2. Three fields will be displayed: - Choose a Column - Choose a Condition - Choose a Value to Filter by The filter will be applied directly to the view, updating the displayed data based on the selected criteria. Sharing a Score Card to Share Chart internally with users that have access to the Charts table: 1. Click Share Chart icon at the top corner of the view. 2. Copy the link. 3. Share it. note: Only people with access permission to this view can see it using this link. You can use. to learn more about access click here. Field Availability & Limitations Unavailable Fields for Both X-Axis & Y-Axis - Long text - File - Multiple select - Collaborator - Link to table - Lookup - Formula containing lookup output - AI - Formula containing AI output Additional X-Axis Restrictions - Number - Rating - Count By integrating these features, horizontal bar charts provide a structured and customizable way to visualize data, enabling users to compare values, track trends, and make data-driven decisions efficiently.

Score Cards

Score Cards A scorecard is a valuable chart for measuring and tracking performance against specific goals, whether in business, project management, or personal development. It provides a clear framework for assessing progress by using key performance indicators (KPIs) or predefined criteria. By offering a visual and structured way to evaluate success, a scorecard enables informed decision-making, continuous improvement, and goal achievement. Create a Chart Create a new chart Steps 1. Within the table, click on the "+" sign above the search bar. 2. From the drop-down menu, select Chart view. 3. A box will appear to enter a name for the view—choose a descriptive name that reflects its content. 4. Select who can edit: - Collaborative for team access and editing. - Personal for individual use. note: you can't add it in dashboards 5. Click "Add". 6. Click Chart type . 7. from the list Choose Score Card Chart. Build a Score Card Chart How to Build a Score Card Chart 1. Choose X-Axis: Select a column from the drop-down list to define the measured variable for the chart. 2. Choose a Measure: Once a column is selected, choose the appropriate measure to apply. Dynamic Measures: The available measures will be automatically populated based on the selected column type, ensuring relevant calculations and insights. 3. Add Sub-Header (optional): write a description for KPI, as it helps break up content, making it easier to read and understand. Score Cards Setup: | Color | Purpose | | -------------- | ---------------------------------------------------------------------------------------------------------------------------------- | | 🔴 X-Axis | a drop-down list consist of columns of the table. | | 🟢 Measures | available measures will be automatically populated based on the selected column type, ensuring relevant calculations and insights. | | 🔵 Sub-headers | helps break up content, making it easier to read and understand. | | 🟠 Currency | Currencies and Number format always follow the column setup within the table. | Available Measures Based on Column Types: - Numbers: - Count – Counts the number of entries in the selected column. - Sum – Adds up all numerical values. - Avg – Calculates the average of the values. - Min/Max – Retrieves the minimum or maximum value in the dataset. - Other Column Types: - Count ONLY – Non-numeric columns can only be counted. | Numbers formats always follow the column setup within the table. | | ---------------------------------------------------------------- | Examples: - If you want to calculate the total number of projects, you can select the project id column and apply the Count measure. - If you need to analyze a project budget, you can choose the budget column and apply Sum, Average, Min, or Max as needed. How to Filter a Score Card Within the view, click on the funnel icon in the view bar. 1. A box will appear; click on "Add filter." 2. Three fields will be displayed: - Choose a Column - Choose a Condition - Choose a Value to Filter by The filter will be applied directly to the view, updating the displayed data based on the selected criteria. Example: you can filter ONLY Completed Projects. but don't forget to add sub-header to explain the filtered data. Fields Availability If certain fields don’t appear in the list when creating charts, it's because some field types are not supported for visualization on both the x-axis and y-axis. These include: - Long text: Typically not suitable for numerical or categorical representation in charts. - File: Contains attachments or documents, which cannot be plotted on a chart. - Multiple select: Stores multiple values, making it difficult to plot in a single axis format. - Collaborator: Represents users rather than measurable data. - Link to table: References another table instead of containing direct numerical or categorical data. - Lookup: Pulls values from another table but isn’t always structured for charting. - Formula containing lookup output: Derived data that depends on lookups, which may not be supported in chart rendering. - AI: AI-generated outputs may be complex and not directly usable in charts. - Formula containing AI output: Similar to AI fields, these often contain generated text or complex logic not suited for visualization. These limitations exist to ensure that only structured, quantifiable data is used for meaningful chart representation.

Gauge Chart

A Gauge Chart is a variation of a pie chart designed to represent data in a semi-circular format with segments indicating different ranges of values. Unlike traditional gauge charts with a needle, this gauge-style pie chart uses proportional segments to visualize data distribution within a defined range. It is particularly effective for visualizing performance indicators, comparisons between different categories. Creating a Gauge Chart To add a new chart: 1. Within the table, click on the "+" sign above the search bar. 2. From the drop-down menu, select Chart view. 3. A box will appear to enter a name for the view—choose a descriptive name that reflects its content. 4. Select who can edit: - Collaborative for team access and editing. - Personal for individual use. Note: You can't add it in dashboards. 5. Click "Add". 6. Click Chart type. 7. From the list, choose Gauge Chart. Building a Gauge Chart To create a Gauge chart, users must configure the following components: Configuring a Gauge Chart: Example - Risk Impact Analysis To illustrate how to create a Gauge chart, let's build one that categorizes risks based on their impact level. - For the x-axis (category): we will select "Impact" to show the distribution of risk levels. - For the y-axis (values): we will choose "Titles" with the Count measure to calculate the total number of risks per impact level. 1. Define the x-axis (Category/Slice) From the drop-down list, choose a column to represent different sections of the Gauge. In this example, we use "Impact" to categorize risks into different impact levels (e.g., Low, Medium, High). 2. Define the Values (Amounts) From the drop-down list, choose a column to represent numerical values. We select "Title", applying the Count measure to calculate the total number of risks within each impact level. This setup ensures a structured and meaningful representation of risk distribution, making it easier to assess and mitigate high-impact risks. Available Measures Based on Column Types For Numeric Columns - Count – Counts the number of entries in the selected column. - Sum – Adds up all numerical values. - Avg – Calculates the average of the values. - Min/Max – Retrieves the smallest or largest value in the dataset. For Non-Numeric Columns - Count ONLY – Non-numeric columns can only be counted. Number formatting always follows the column setup within the table. Customization & Features Design Customization Corner Radius: - Users can modify the corner radius to create rounded slice edges for a smoother appearance. Gap: - Users can adjust the gap between slices to enhance visibility and separate sections more clearly. Show Legend: - Displays a legend for better readability, especially useful when a breakdown is applied. Inner Radius: - Users can modify the inner radius by adjusting the central empty space. Color Customization: - Users can change the color palette or customize slice colors individually to match specific preferences. Filtering a Gauge Chart Within the view, click on the funnel icon in the view bar. A box will appear; click on "Add filter." Three fields will be displayed: 1. Choose a Column 2. Choose a Condition 3. Choose a Value to Filter by The filter will be applied directly to the view, updating the displayed data based on the selected criteria. Sharing a Gauge Chart To share a chart internally with users who have access to the Charts table: 1. Click the Share Chart icon at the top corner of the view. 2. Copy the link. 3. Share it. Note: Only people with access permission to this view can see it using this link. Publishing a Gauge Chart (SOON) Once your chart is designed and tested, publishing it involves making it accessible to an audience. To Publish a Chart: 1. Click the Share Chart icon at the top corner of the view. 2. Go to the Publish tab. 3. Click Publish. 4. Copy the link. 5. Share it. Note: There are options to Restrict Access with Password, Change the Link, or Unpublish the Link. For more details, visit the public sharing article. Field Availability & Limitations Unavailable Fields for Both X-Axis & Y-Axis - Long text - File - Multiple select - Collaborator - Link to table - Lookup - Formula containing lookup output - AI - Formula containing AI output Additional X-Axis Restrictions - Number - Rating - Count By integrating these features, Gauge charts provide a structured and visually appealing way to represent categories, enabling users to analyze distributions and make data-driven decisions efficiently.

Horizontal Bar Charts

Horizontal Bar Chart A horizontal bar chart is a chart where categories are displayed along the y-axis, and corresponding values are represented by horizontal bars extending across the x-axis. This format is particularly useful when dealing with long category labels, as it provides better readability compared to vertical bar charts. allowing users to quickly interpret trends and differences across categories. How to Create a Chart 1. Within the table, click on the "+" sign above the search bar. 2. From the drop-down menu, select Chart view. 3. A box will appear to enter a name for the view—choose a descriptive name that reflects its content. 4. Select who can edit: - Collaborative for team access and editing. - Personal for individual use. note: you can't add it in dashboards 5. Click "Add". 6. Click Chart type . 7. from the list Choose Horizontal Bar Chart Chart. Building a Horizontal Bar Chart To create a horizontal bar chart, users must configure the following components: Configuring a Horizontal Bar Chart: Example - Monthly Budget Analysis To illustrate how to create a horizontal bar chart, let's build one that captures our monthly budget. - For the x-axis, we will select Transaction Date and adjust the granularity to monthly to track income trends over time. - For the y-axis, we will choose Actual Income with the Sum measure to calculate total earnings per month. - To add more context, we will apply a breakdown by Income Type, allowing us to visualize income sources within each month. 1. Define the X-Axis (Categories) - from the drop-down list choose a Column to Represents the grouping of data points. - In this example, we use Transaction Date, adjusting the granularity to monthly for time-based analysis. 2. Define the Y-Axis (Values) - from the drop-down list choose a Column to Represents the numerical values being measured. - We select Actual Income, applying the Sum measure to calculate total earnings. 3. Apply a Breakdown (Optional) - from the drop-down list choose a Column to Segments the data within each bar for deeper insights. - In this case, breaking down by Income Type provides a clearer view of different income sources each month. - Sorting is disabled when a breakdown is applied. This setup ensures a structured and meaningful representation of income trends, making it easier to track and analyze financial performance over time. Comparing Multiple Values (Y-Axis): To compare Actual Income with Estimated Income, follow these steps: 1. Remove the breakdown (if previously applied) to allow a side-by-side comparison. 2. From the y-axis dropdown list, choose "Estimated Income" as the second measure. 3. Apply the "Sum" measure to ensure the total estimated income is calculated for each month. Now, your monthly-based horizontal bar chart will display both Actual Income and Estimated Income, making it easy to spot differences, analyze trends, and assess financial performance at a glance. Available Measures Based on Column Types When selecting a y-axis column, different measurement options become available: For Numeric Columns - Count – Counts the number of entries in the selected column. - Sum – Adds up all numerical values. - Avg – Calculates the average of the values. - Min/Max – Retrieves the smallest or largest value in the dataset. For Non-Numeric Columns - Count ONLY – Non-numeric columns can only be counted. - Number formatting always follows the column setup within the table. Customization & Features The platform offers various customization options to enhance horizontal bar charts: Sorting & Highlighting - Sort Values: - Sorts values in ascending or descending order based on the y-axis measurement. - Sorting is disabled when a breakdown is applied. - Highlight Values: - Enables highlighting of the maximum and minimum values in the dataset. Design Customization - Column Background: - Users can add a background color for each bar segment. - Show Legend: - Displays a legend for better readability, especially useful when a breakdown is applied. - Normalization: - Ensures values are scaled proportionally for accurate comparisons. - Color Customization: - Users can change the color palette or customize bar colors individually to match specific preferences. Filter a Horizontal Bar Charts: Within the view, click on the funnel icon in the view bar. 1. A box will appear; click on "Add filter." 2. Three fields will be displayed: - Choose a Column - Choose a Condition - Choose a Value to Filter by The filter will be applied directly to the view, updating the displayed data based on the selected criteria. Field Availability & Limitations Unavailable Fields for Both X-Axis & Y-Axis - Long text - File - Multiple select - Collaborator - Link to table - Lookup - Formula containing lookup output - AI - Formula containing AI output Additional X-Axis Restrictions - Number - Rating - Count By integrating these features, horizontal bar charts provide a structured and customizable way to visualize data, enabling users to compare values, track trends, and make data-driven decisions efficiently.

Donut Chart

A Donut chart is a variation of a pie chart where categories are represented as slices of a ring, with a hollow center, and corresponding values determine the proportional size of each slice. This format is particularly useful when displaying parts of a whole, providing a clear and visual representation of distributions. It allows users to quickly understand proportions and compare segments efficiently. Creating a Donut Chart To add a new chart: 1. Within the table, click on the "+" sign above the search bar. 2. From the drop-down menu, select Chart view. 3. A box will appear to enter a name for the view—choose a descriptive name that reflects its content. 4. Select who can edit: - Collaborative for team access and editing. - Personal for individual use. Note: You can't add it in dashboards. 5. Click "Add". 6. Click Chart type. 7. From the list, choose Donut Chart. Building a Donut Chart To create a Donut chart, users must configure the following components: Configuring a Donut Chart: Example - Risk Impact Analysis To illustrate how to create a Donut chart, let's build one that categorizes risks based on their impact level. - For the x-axis (category): we will select "Impact" to show the distribution of risk levels. - For the y-axis (values): we will choose "Titles" with the Count measure to calculate the total number of risks per impact level. 1. Define the x-axis (Category/Slice) From the drop-down list, choose a column to represent different sections of the Donut. In this example, we use "Impact" to categorize risks into different impact levels (e.g., Low, Medium, High). 2. Define the Values (Amounts) From the drop-down list, choose a column to represent numerical values. We select "Title", applying the Count measure to calculate the total number of risks within each impact level. This setup ensures a structured and meaningful representation of risk distribution, making it easier to assess and mitigate high-impact risks. Available Measures Based on Column Types For Numeric Columns - Count – Counts the number of entries in the selected column. - Sum – Adds up all numerical values. - Avg – Calculates the average of the values. - Min/Max – Retrieves the smallest or largest value in the dataset. For Non-Numeric Columns - Count ONLY – Non-numeric columns can only be counted. Number formatting always follows the column setup within the table Design Customization Donut properties Corner Radius: - Users can modify the corner radius to create rounded slice edges for a smoother appearance. Gap: - Users can adjust the gap between slices to enhance visibility and separate sections more clearly. Show Legend: - Displays a legend for better readability, especially useful when a breakdown is applied. Inner Radius: - Users can modify the inner radius by adjusting the central empty space. Color Customization: - Users can change the color palette or customize slice colors individually to match specific preferences. Filtering a Donut Chart Within the view, click on the funnel icon in the view bar. A box will appear; click on "Add filter." Three fields will be displayed: 1. Choose a Column 2. Choose a Condition 3. Choose a Value to Filter by The filter will be applied directly to the view, updating the displayed data based on the selected criteria. Field Availability & Limitations Unavailable Fields for Both X-Axis & Y-Axis - Long text - File - Multiple select - Collaborator - Link to table - Lookup - Formula containing lookup output - AI - Formula containing AI output Additional X-Axis Restrictions - Number - Rating - Count By integrating these features, Donut charts provide a structured and visually appealing way to represent categories, enabling users to analyze distributions and make data-driven decisions efficiently.

How To Create Dashboards

1. To Create New Dashboard 2. Click "Analytics" 3. Click "+ Add dashboard"  4. Choose a Name for your Dashboard  5. Click "Add"  6. To add Charts, Click "Edit Dashboard" 7. the dashboard is divided into square click where you want to insert charts  8. Click "Add Chart"  9. you will see a list with all Applications within your Workspace Choose the App you want to add your charts from  10. a list of Charts associated with Application will Appear Choose a Chart  11. Resize the Chart to your desired size  ## Groups 1. Group Helps you with Aggregating Multiple Charts to into a Single Background  2. After Creating a group grab and drop your desired charts into Group  3. Rename the Group heading to descriptive heading  4. you can add Text to describe your Dashboards & Charts\ After writing into your text box make sure to save your work by checking the right icon  5. Click "Apply changes" to save your work  Congratulation! you just built your first Dashboard

Pie Charts

A pie chart is a chart where categories are represented as slices of a circle, and corresponding values determine the proportional size of each slice. This format is particularly useful when displaying parts of a whole, providing a clear and visual representation of distributions. It allows users to quickly understand proportions and compare segments efficiently. Creating a Pie Chart To add a new chart: 1. Within the table, click on the "+" sign above the search bar. 2. From the drop-down menu, select Chart view. 3. A box will appear to enter a name for the view—choose a descriptive name that reflects its content. 4. Select who can edit: - Collaborative for team access and editing. - Personal for individual use. Note: You can't add it in dashboards. 5. Click "Add". 6. Click Chart type. 7. From the list, choose Pie Chart. Building a Pie Chart To create a pie chart, users must configure the following components: Configuring a Pie Chart: Example - Risk Impact Analysis To illustrate how to create a pie chart, let's build one that categorizes risks based on their impact level. - For the x-axis (category): we will select "Impact" to show the distribution of risk levels. - For the y-axis (values): we will choose "Titles" with the Count measure to calculate the total number of risks per impact level. 1. Define the x-axis (Category/Slice) From the drop-down list, choose a column to represent different sections of the pie. In this example, we use "Impact" to categorize risks into different impact levels (e.g., Low, Medium, High). 2. Define the Values (Amounts) From the drop-down list, choose a column to represent numerical values. We select "Title", applying the Count measure to calculate the total number of risks within each impact level. This setup ensures a structured and meaningful representation of risk distribution, making it easier to assess and mitigate high-impact risks. Available Measures Based on Column Types For Numeric Columns - Count – Counts the number of entries in the selected column. - Sum – Adds up all numerical values. - Avg – Calculates the average of the values. - Min/Max – Retrieves the smallest or largest value in the dataset. For Non-Numeric Columns - Count ONLY – Non-numeric columns can only be counted. Number formatting always follows the column setup within the table Design Customization Pie properties Show Legend: - Displays a legend for better readability, especially useful when a breakdown is applied. Corner Radius: - Users can modify the corner radius to create rounded slice edges for a smoother appearance. Gap: - Users can adjust the gap between slices to enhance visibility and separate sections more clearly. Color Customization: - Users can change the color palette or customize slice colors individually to match specific preferences. Filtering a Pie Chart Within the view, click on the funnel icon in the view bar. A box will appear; click on "Add filter." Three fields will be displayed: 1. Choose a Column 2. Choose a Condition 3. Choose a Value to Filter by The filter will be applied directly to the view, updating the displayed data based on the selected criteria. Field Availability & Limitations Unavailable Fields for Both X-Axis & Y-Axis - Long text - File - Multiple select - Collaborator - Link to table - Lookup - Formula containing lookup output - AI - Formula containing AI output Additional X-Axis Restrictions - Number - Rating - Count By integrating these features, pie charts provide a structured and visually appealing way to represent categories, enabling users to analyze distributions and make data-driven decisions efficiently.

Nightingale Chart

A Nightingale Chart, also known as a polar area chart or rose chart, is a variation of a pie chart where data is represented in circular segments with varying radii. Unlike a traditional pie or donut chart, the segment size is determined by both the angle and radius, making it particularly effective for visualizing cyclical patterns and distributions over time. It allows users to highlight trends, compare proportions, and understand data variations intuitively. Creating a Nightingale Chart To add a new chart: 1. Within the table, click on the "+" sign above the search bar. 2. From the drop-down menu, select Chart view. 3. A box will appear to enter a name for the view—choose a descriptive name that reflects its content. 4. Select who can edit: - Collaborative for team access and editing. - Personal for individual use. Note: You can't add it in dashboards. 5. Click "Add". 6. Click Chart type. 7. From the list, choose Nightingale Chart. Building a Nightingale Chart To create a Nightingale chart, users must configure the following components: Configuring a Nightingale Chart: Example - Risk Impact Analysis To illustrate how to create a Nightingale chart, let's build one that categorizes risks based on their impact level. - For the x-axis (category): we will select "Impact" to show the distribution of risk levels. - For the y-axis (values): we will choose "Titles" with the Count measure to calculate the total number of risks per impact level. 1. Define the x-axis (Category/Slice) From the drop-down list, choose a column to represent different sections of the Nightingale. In this example, we use "Impact" to categorize risks into different impact levels (e.g., Low, Medium, High). 2. Define the Values (Amounts) From the drop-down list, choose a column to represent numerical values. We select "Title", applying the Count measure to calculate the total number of risks within each impact level. This setup ensures a structured and meaningful representation of risk distribution, making it easier to assess and mitigate high-impact risks. Available Measures Based on Column Types For Numeric Columns - Count – Counts the number of entries in the selected column. - Sum – Adds up all numerical values. - Avg – Calculates the average of the values. - Min/Max – Retrieves the smallest or largest value in the dataset. For Non-Numeric Columns - Count ONLY – Non-numeric columns can only be counted. Number formatting always follows the column setup within the table. Customization & Features Design Customization Corner Radius: - Users can modify the corner radius to create rounded slice edges for a smoother appearance. Gap: - Users can adjust the gap between slices to enhance visibility and separate sections more clearly. Show Legend: - Displays a legend for better readability, especially useful when a breakdown is applied. Inner Radius: - Users can modify the inner radius by adjusting the central empty space. Color Customization: - Users can change the color palette or customize slice colors individually to match specific preferences. Filtering a Nightingale Chart Within the view, click on the funnel icon in the view bar. A box will appear; click on "Add filter." Three fields will be displayed: 1. Choose a Column 2. Choose a Condition 3. Choose a Value to Filter by The filter will be applied directly to the view, updating the displayed data based on the selected criteria. Sharing a Nightingale Chart To share a chart internally with users who have access to the Charts table: 1. Click the Share Chart icon at the top corner of the view. 2. Copy the link. 3. Share it. Note: Only people with access permission to this view can see it using this link. Publishing a Nightingale Chart (SOON) Once your chart is designed and tested, publishing it involves making it accessible to an audience. To Publish a Chart: 1. Click the Share Chart icon at the top corner of the view. 2. Go to the Publish tab. 3. Click Publish. 4. Copy the link. 5. Share it. Note: There are options to Restrict Access with Password, Change the Link, or Unpublish the Link. For more details, visit the public sharing article. Field Availability & Limitations Unavailable Fields for Both X-Axis & Y-Axis - Long text - File - Multiple select - Collaborator - Link to table - Lookup - Formula containing lookup output - AI - Formula containing AI output Additional X-Axis Restrictions - Number - Rating - Count By integrating these features, Nightingale charts provide a structured and visually appealing way to represent categories, enabling users to analyze distributions and make data-driven decisions efficiently.