Creating the Dashboard


A dashboard is a visual representation of data that provides a consolidated and interactive view of key performance indicators (KPIs), metrics, and other relevant information. It is designed to offer a comprehensive overview of an organization’s or an individual’s data in a single, easily accessible interface.

Dashboards can be customized to display metrics such as website traffic, sales figures, or social media engagement. They can also be designed to provide real-time updates or be updated regularly, such as daily or weekly.

To create a dashboard in Lumenore:  

Step 1: Access “Create Dashboard” either from the homepage or the Self-Service page and choose “Create Dashboard”.

“Lumenore’s Self Service BI empowers users to create rapid reports, extending beyond the confines of static, pre-defined data snapshots typically offered by traditional reporting. This facilitates an enriched and interactive experience for end-users.”

Step 2: Enter the dashboard name and choose the schema based on your requirements.

Step 3: At any time, the user can manage, change, and refresh the schema by clicking on icons located at the top left.

Step 4: Upon clicking the three dots adjacent to attributes, three options will be displayed:

  • Group Tables: To create a group of attributes presented in one schema.
  • Calculate Attribute: To create a customized attribute according to the requirement.
  • Add Hierarchy: To arrange the data elements in the drill-down levels.

Note: An attribute denotes a characteristic or feature associated with a data point or object. Attributes can be either categorical or numerical, offering insights into the properties or qualities of an object. For instance, in a dataset of students, attributes might encompass age, gender, height, weight, and academic performance.

Upon clicking the three dots adjacent to measures, three options will be displayed:

  • Group Tables: To create a group of attributes presented in one schema.
  • Calculate Attribute: To create a customized attribute according to the requirement.
  • Create/manage what-if parameters: To explore the potential outcomes or consequences of changes in one or more input variables. It defines the relationship between two or more two variables; there can be dependent and independent variables.

Note: A measure pertains to a calculated value or quantity derived from the data. Measures serve the purpose of quantifying or describing the attributes of data points. For instance, metrics like mean, median, and mode are measures of central tendency, offering insights into the average or typical value of a dataset.

Step 5: Choose at least one measure and one attribute, and a table view will be displayed.

Step 6: Users have the option to assign a title to the chart, specify the data limit for display, view and sort the data in ascending or descending order, save the chart, and explore additional functionalities such as Duplicate and Reset.

 Step 7: Navigate to “Chart Type”, and choose the appropriate chart based on your needs.

Step 8: For chart customization, click on “Advance”. The chart properties will then be displayed.

  • Series: Users can personalize the attributes of the chosen series. This encompasses customization options such as series color, chart type, formatting type (US/India), precision, abbreviation preferences (None/Auto), formatter text options ($/%/₹), and formatter text position (Right/Left). Additionally, users have the capability to implement conditional formatting by selecting “Add New Rule” (refer to the documentation to learn more about Conditional Formatting in Grid).

  • General: Users can tailor various aspects of the chart, including the background, label color, label title, plot border color, background color, data labels, font size, and color.

  • Legends: Users have the option to personalize the legend’s position, background color, and alignment.

  • Spacing: Users can tailor plot border width, margin, and spacing to meet specific requirements.

  • Tooltip: Users can personalize the tooltip’s background color, font color, border radius, border width, and border color. Additionally, they have the option to toggle the visibility of the tooltip on or off.

  • Value scale (y-axis): Users can tailor the properties of the Y-axis.

  • Category Scale (X-axis): Users have the option to customize properties related to the X-axis.

  • Visual lines: Users now possess the capability to generate visual lines—whether dynamic or manually set target/benchmark lines—to compare the chart values against specific target or benchmark figures.

Step 9: Select “Apply” to implement the customizations made.

Step 10: Navigate to the dashboard creation screen and click on “Custom” to modify the chart layout. Instead of using default settings, a custom chart allows you to tailor the visual representation of data according to your needs. This can include adjusting colors, labels, axes, and other elements to better communicate the information you want to convey.

Upon selecting the “Custom” option, you will encounter a range of template choices. Simply click on any of the available templates. As an illustration, let’s choose template 4 for demonstration purposes.

Next, tap the “+” icon to include the following options:

  • Charts
  • Micro Chart
  • Text/Widget
  • Grid
  • Image

Step 11: Once you have generated multiple charts, proceed to the next step by clicking on “Next” in the bottom right corner to create the dashboard.

Step 12: Select dashboard layout according to your requirement. Then click “Apply”.

Step 13: Once the dashboard is created, you gain access to various functionalities to interact with your dashboard, such as canceling, filtering, customization, publishing, modifying layout, including a header, adding text, and inserting cards.