Creating Visuals

A visual is a graphical representation of your data. You can add a wide variety of visuals to an analysis, using different types of charts and custom elements.

To create the visual, you can select the data fields and use AutoGraph to automatically determine the most appropriate visual type. Or you can select a specific visual type and choose fields to populate it.

You usually need a combination of dimension and measure fields to create a visual, for example the number of impressions (a measure) by week (a dimension).

Dimension or category fields
Descriptive text field icon Descriptive fields with alphanumeric strings that you can use to label and categorize data, such as printer names, printer types, and job states.
Date field icon Date fields with dates and time intervals. You can use date fields to organize your data into hierarchies according to year, quarter, and month or into units of time such as hours or minutes.
Measure fields
Numeric fields with quantified data that you can aggregate or calculate, such as number of impressions, number of copies, and event duration.

You cannot use the same field for more than one dimension field well in a visual.

Note: This function is only available with the Self-Service feature. If you want to purchase this feature, contact your Ricoh representative.
To create a visual:
  1. Click Dashboards tab, the Dashboards tab.
  2. Click Dashboard Designer, in the bottom-left corner.
    Dashboards tab
  3. On the Analyses dialog, click New analysis or click Options button, the Options button, next to an existing analysis and select Edit.
    Analyses dialog
  4. On the analysis page, click , the Add visual button, on the toolbar.
    Analysis page - Create a visual
  5. Use one of these methods to create the visual:
    • Use the AutoGraph function:
      1. In the list of visual types, click the AutoGraph icon.AutoGraph icon
      2. Add data to the visual by dragging fields from the Data panel to the Add a dimension or measure field well in the Visuals panel.

        The AutoGraph function automatically creates a type of visual based on the selected data and makes adjustments as you add more fields.

        If you have a long list of fields in the Data panel, you can use the search function to find a specific field. Enter a search term in the search box at the top of the panel. Search is case-insensitive and wildcards are not supported.

    • Select a visual type, and then choose the fields that you want to include:
      1. In the list of visual types, click the icon for the visual type that you want to create.
      2. Add data to the visual by dragging fields from the Data panel to the appropriate field wells in the Visuals panel. Or just select fields in the Data panel if you want RICOH Supervisor to automatically place them in appropriate field wells.

        Use dimension or measure fields according to the color of the target field well. Orange field wells expect a measure field and blue field wells expect a dimension field. If you use a dimension field to populate a Value field well, the Count aggregate function is automatically applied to it to create a numeric value.

      Analysis page - Edit a visual

      In some types of visuals, you can also drag fields directly to the drop targets displayed in the visuals. Green drop targets expect a measure field and blue drop targets expect a dimension field.

      Analysis page - Use drop targets in a visual
  6. Configure sorting, aggregation, granularity, and formatting settings for the fields that you added to the visual by clicking Options button, the Options button, next to a field in the Visuals panel.

    In visuals that display field labels, you can also configure field settings directly from the visual. Click Options button, the Options button, next to a field label.

  7. Customize the appearance of the visual in the Properties panel on the right.

You can add more visuals to the analysis by using the Add visual option from the toolbar. You can then resize the visuals and drag them to rearrange them.

RICOH Supervisor supports up to 30 visuals in a single sheet and up to 20 sheets per analysis.

In this section:

  1. Using AutoGraph
    The AutoGraph function creates a visual automatically, using the most appropriate visual type for the data fields you select.
  2. Using Bar Charts
    The bar chart is commonly used to compare multiple items. Bar charts display categories or items along one of the axes and their values on the other axis. You can also group the values by another category and choose a stacked layout.
  3. Using Box Plots
    The box plot, or box and whisker plot, displays data pooled from multiple sources into one visual, helping you make data-driven decisions. You can use box blots to visualize how data is distributed across an axis or over time. For example, a box plot can show the number of printer errors encountered over a 7-day time period.
  4. Using Combo Charts
    Using a combo chart, you can create one visualization that shows two different types of data, such as trends and categories. Combo charts combine a line chart with a bar chart. Bar charts are useful for comparing categories. Both bar charts and line charts are useful for displaying changes over time, although bar charts are more useful when there is a greater difference between changes.
  5. Using Custom Visual Content
    You can embed custom content, such as images, online forms, webpages, and online videos, in an analysis. For example, you can embed the image of your company logo, an online video from a conference, or an online form asking the users of the dashboard if the dashboard is helpful.
  6. Using Donut Charts
    Use donut charts to compare values for items in a dimension. The best use for this type of chart is to show a percentage of a total amount.
  7. Using Funnel Charts
    Use a funnel chart to visualize data that moves across multiple stages in a linear process. The first stage, known as the head, is the largest block and is followed by the smaller stages, known as the neck, in a funnel shape. The size of a block is a percentage of the total, and is proportional to the value it represents.
  8. Using Gauge Charts
    Use gauge charts to compare values for items in a measure. You can compare them to another measure or to a custom amount. For example, gauge charts are useful when you want to visualize data that represents liquid levels, such as ink usage.
  9. Using Heat Maps
    Use heat maps to show a measure for the intersection of two dimensions, with color-coding to easily differentiate where values fall in the range. Heat maps can also be used to show the count of values for the intersection of the two dimensions.
  10. Using Highcharts
    Use Highcharts visuals to create custom chart types and visuals that use the Highcharts Core library. To configure a Highcharts visual, you add a Highcharts JSON schema to the visual. The Chart code editor provides contextual assistance and real-time validation to ensure that the input JSON schemas are configured properly. For security reasons, the visual editor does not accept CSS, JavaScript, or HTML code input.
  11. Using Histograms
    Use a histogram chart to display the distribution of continuous numerical values in your data.
  12. Using Image Components
    You can upload a static image to an analysis.
  13. Using Key Performance Indicators
    Use a key performance indicator (KPI) to visualize a comparison between a key value and its target value. A KPI displays a value comparison, the two values being compared, and a visual that provides context to the data that is displayed. You can choose from a set of predefined layouts.
  14. Using Layer Maps
    Use layer maps to visualize data with custom geographic boundaries. To create layer maps, you upload GeoJSON files that shape layers over a base map and join with data to visualize associated metrics and dimensions. You can customize the color, border, and opacity of the shape layers.
  15. Using Line Charts
    Line charts help you compare data over time or compare changes over the same time period for more than one group or category.
  16. Using Map Charts
    Map charts let you compare values and display categories across geographical regions. You can create map charts only if your dataset contains location data that corresponds to latitudinal and longitudinal values. Location data can include the actual values for latitude and longitude. It can also include geographic components such as country, state or region, county or district, city, and ZIP code or postal code.
  17. Using Pie Charts
    Pie charts are used to display proportional data and percentages.
  18. Using Pivot Tables
    A pivot table is useful for summarizing and analyzing large amounts of data. It shows measure values for the intersection of two dimensions.
  19. Using Radar Charts
    In a radar chart, one or more groups of values are plotted over multiple common variables. Each variable has its own axis, and each axis is arranged radially around a central point. The data points from a single observation are plotted on each axis and connected to each other to form a polygon. Multiple observations can be plotted in a single radar chart to display multiple polygons, which makes it easier to spot outlying values for multiple observations quickly.
  20. Using Sankey Diagrams
    Use Sankey diagrams to show flows from one category to another, or paths from one stage to the next.
  21. Using Scatter Plots
    You can use scatter plots to visualize two or three measures across two dimensions.
  22. Using Tables
    A table is a grid that contains related data in a logical series of rows and columns.
  23. Using Text Boxes
    Use text boxes to add context to sheets in an analysis. For example, text boxes can include instructions, descriptions, or hyperlinks to external websites.
  24. Using Tree Maps
    Tree maps display hierarchical data in the form of nested rectangles. For example, you can use a tree map instead of a bar chart to compare a large number of categories and subcategories.
  25. Using Waterfall Charts
    A waterfall chart is useful for understanding how an initial value is affected by a series of additions and subtractions. Each positive or negative change that the initial value goes through is represented as a bar. The last bar represents the final total.
  26. Using Word Clouds
    Use word clouds as an engaging way to display how often a word is used in relation to other words in a dataset. For example, you can show word or phrase frequency and identify trending items or actions.
Parent topic: Creating and Managing Visuals