Insight Types

Insights in Incorta Analytics are divided into three categories:

  • Tables
  • Charts
  • Gauges

Part of designing an effective Insight is selecting the appropriate visualization type. In this Appendix, you will find a description of each of these types. The choice of a visualization type is not set in stone; after defining an Insight in the Analyzer, you can still change the visualization type to whatever you find as the best fit. You can even change a visualization type to a completely different one, e.g. you can transform a table into a column chart.

Table Types

  • Pivot Table. Use a pivot table to plot two dimensions against each other. The attributes entered in the “grouping dimension” field define the rows in the pivot table. Those entered in the “coloring dimension” field define the columns in the pivot table. Finally, the attributes entered in the “measure” field define the cells of the pivot table. The “grouping dimension” and the “coloring dimension” both are required to build a pivot table.
  • Table. This is the simplest mode of a table. All attributes and measures have to be entered in the “measure” field. You can enter columns from different tables, if they are joined together. If a column shows as Null, this can indicate a missing join, or joins in the wrong direction.
  • Aggregated. The user can group-by the data by certain dimensions. The group-by dimensions have to be dragged to the “grouping dimension” field, while the rest of the attributes should be dragged to the “measure” field. By default, Incorta will aggregate the data, grouping by the “grouping dimensions.” User can select not to Aggregate, by turning off the Aggregated button from the Settings drop-down menu in the upper right-hand corner of the screen.
  • Aggregated - Total. This table type has a row added at the bottom where the sum of all the rows would be calculated.
  • Aggregated - Subtotal. This table type has the totals calculated and displayed for each row.
  • Aggregated - Subtotal - Total. In addition to the Aggregated - Subtotal table, this table type has a row added at the bottom where the sum of all the rows would be calculated. The values in this row would be the same as those in the total row, if the Aggregated - Total were chosen.

Visualization Types

  • Column (Vertical-Bar) Chart. Plot grouping dimensions on the (horizontal) x-axis,and measures on the (vertical) y-axis. The first added attribute to the “grouping dimension”field is used for data slicing. Additional attributes to this field enables the user to select one group, filter the data on that value, and drill down to the next dimension. Additional measures are represented by different colors.
  • Bar Chart. This chart is similar to the column chart representing the data in horizontal bars rather than vertical columns. Using this chart, you can plot grouping dimensions on the (vertical) y-axis versus measures on the (horizontal) x-axis. Additional measures are represented by different colors.
  • Stacked-Column Chart. Use this chart to display multiple categories in each column. The colored bands represent slicing of the total by the coloring dimension. Attributes in the grouping dimension field define the x-axis of the chart. The bar represents the measure in the chart. The bar can be sliced according to the attributes in the “coloring dimension.” If you add two attributes to the “grouping dimension” field, you can filter by one year, drill down to quarters in that year, and keep data sliced using the coloring dimension. If you add two attributes in the coloring dimension field (e.g. Product Category and Product), you can filter on one Product Category, drill down to the Products in that category, and see data for all the years. However, you cannot add two attributes to the grouping dimension field and two attributes to the coloring dimension field for this kind of chart. Use this type of chart to stack multiple measures by adding two or more measures to the measure field and no attributes to the coloring dimension field. You cannot add multiple measures and a coloring dimension in this type of chart.
  • Stacked-Bar Chart. This chart is similar to the Stacked-Column chart representing data in horizontal bars rather than vertical columns.
  • Percentage Column Chart. Use this chart type to represent data in columns sliced by the coloring dimension and represented as a percentage of a total. This chart is similar to the Stacked-Column Chart in terms of adding dimensions and measures. However, it is not used to analyze measure values. It represents the relative percentage of each coloring (or slicing) dimension compared to the whole measure value for that grouping dimension value.
  • Percentage Bar Chart. As in the Percentage Column Chart, use this chart type to represent data in bars sliced by the coloring dimension and represented as a percentage of a total.
  • Combo Dual Axis Chart. Use this chart when you want to plot two different measures on the same y-axis. The two measures will have the same scale. You only need to add a grouping dimension, and two measures to obtain this chart. Additional grouping dimensions will be used for drill-down. This type of chart is used when both analyzed measures have similar ranges.
  • Dual Axis Chart. Use this chart type to plot two different measures on two separate y-axes, which can have different scales. This type requires at least one grouping dimension only, however, more grouping dimensions can be added to drill down.
  • Dual Axis Chart. Use thisnchart type to plot two different measures on two separate x-axes, which can have different scales. This type requires at least one grouping dimension only, however, more grouping dimensions can be added to drill down.
  • Area Chart. In this type of chart, the areas under the lines for multiple data series are overlayed on each other. This chart requires a grouping dimension and a measure. A coloring dimension can be added to slice the area for each dimension value by another dimension. Similar to the Stacked-Column Chart, you can choose to stack two measures, but then you cannot add a coloring dimension in that case.
  • Stacked-Area Chart. This type of chart is also called a Subdivided Surface Chart or a “Band Chart.” If possible, use the Sort By function in your filters to plot the smoothest trend at the bottom of your chart. Only the data series plotted at the bottom of the chart starts at zero on the y-axis, each following series is plotted relative to the series below it. This chart type behaves similar to the Stacked-Column Chart except that the data is shown as colored areas instead of separate bars.
  • Percentage Area Chart. This chart shows the area under the line as a percentage of the total. It behaves similar to the 100-Percent-Stacked Column Chart, except that the data is shown as colored areas, instead of separate vertical bars.
  • Line Chart. This graph connects data points in the series with a line, but does not indicate exact values between data points. Additional measures will be represented by separate colored lines.
  • Stacked-Line Chart Only. the data series plotted at the bottom of the chart starts at zero on the y-axis, each following series is plotted relative to the series below it. This chart behaves similar to the stacked column chart, except that the graphs are drawn with lines instead of vertical bars.
  • Percentage Line Chart. This graph shows each data point in the series as a percentage or part of 100% or of another specified threshold. This chart is similar to the 100-percent-stacked-column chart, except that the data is plotted as lines instead of vertical bars.
  • Spider Chart. A spider chart can be used to represent actual vs target values. A radar chart can be used to represent multiple measures against 3 or more grouping dimension values.
  • Pyramid Chart. A pyramid chart can be used to represent categories based on their hierarchy, importance, or size. A pyramid chart requires one grouping dimension and one measure. It is the same as a funnel chart, but inverted.
  • Treemap Chart. Treemap charts can be used to represent hierarchical structures, using a specific column for coloring. The size of the rectangle represents the value of the grouping dimension. Treemaps can also show the 2nd level of the grouping dimensions. Any hierarchical type data can be shown with a glimpse into the next level. They are useful for showing two levels of values at the same time. Treemaps only show 1 measure but 2 levels.
  • Heatmap Chart. Heatmap charts can be used to represent values of each slot using varying darkness. That is, the darker the slot, the higher the value it represents.
  • Pie Chart. Use a pie chart to display distinct categories of data. It can be used to slice one measure by one grouping dimension. Additional grouping dimensions can be added to allow for drill down from one dimension to the next.
  • Pie Donut Chart. Use a pie chart to display distinct categories of data. It can be used to slice one measure by one grouping dimension. Additional grouping dimensions can be added to allow for drill down from one dimension to the next.
  • Donut Chart. The donut chart is used in the same way as the pie chart, representing data sets in a donut rather than a pie.
  • Time Series. Use this chart type to represent a time series uisng splines. This chart requires a minimum of one grouping dimension and a measure. The graph has zooming capabilities that enables the user to zoom in different periods. Additional grouping dimensions can be added for drill-down. Additional measures are represented by separate colored splines.
  • Line Time Series. Use this chart type to represent a time series using lines. This chart requires a minimum of one grouping dimension and a measure. The graph has zooming capabilities that enables the user to zoom in different periods. Additional grouping dimensions can be added for drill-down. Additional measures are represented by separate colored lines.
  • Funnel Chart. A funnel chart displays values as progressively decreasing proportions. The size of the area is determined by the series value as a percentage of the total of all values.
  • Scatter Chart. The Scatter Chart is an X-Y plot in which each entity represented is assigned a symbol called a point shape. Both the x and y dimensions are quantitative; that is, they have magnitude. If there is an independent variable, place it on the x-axis. The grouping dimension is descriptive or categorical. The purpose of a scatterplot is to discover or illustrate correlations between the variables.
  • Bubble Chart. Use this chart type for a bubble representation of a grouping dimension (e.g. Product Subcategory) varying in size according to a numeric measure placed third in the measure field. In this chart, you must have three numeric elements in the measure field in a specific order (e.g. Revenue, Cost, Profit) . The first measure indicates the x-axis value, while the second measure indicates the y-axis value. Finally, the size of each bubble represents the magnitude of the third measure.
  • Bubble. This chart type uses bubbles to represent a grouping dimension (e.g. Country) in varying sizes according to the element numerical value in the measure field (e.g. revenue) The grouping dimension labels each bubble.

  • Map Chart. When you design a geographical chart in Incorta Analytics, the drill-down path should be Country, State/Province (use a column that contains the ISO state code), and a full address (street address, city, state). Google Maps does not allow two map charts in the same dashboard. To use a map chart, ensure the following:

    • The Google API key must be provided in the Admin UI > Tenants > Tenant Name > Miscellaneous. Ask the system administrator to do this.
    • For the Lat/Long data, the Lat/long column data must be in the (lat,long) format, e.g. 47.23, -140.22 — This is one data point.
    • The data must reflect real locations.

    • Supported formats for countries are:

      • Full name
      • 3 character code of the country (iso-a3)
      • 2 character code of the country

    • Supported formats for US states are:

      • Full name
      • 2 character code

    • Supported formats for US counties and cities are:

      • Full name
      • 2 character code
      • Full name with word ‘County’ (ex: San Mateo County)
      • Full name, 2 character state name (ex: Alameda, CA)
  • Map Bubble. This chart type maps the grouping dimension values (e.g. Country) as bubbles in varying sizes according to the element numerical value in the measure field (e.g. revenue).
  • TagCloud. This chart type displays the grouping dimension values (e.g. Country) as tags in varying sizes according to the element numerical value in the measure field (e.g. revenue).
  • Area Range Chart. Use this chart type to plot a grouping dimension (e.g. Country) versus two measures (e.g. Revenue and Cost) using two different lines. The area enclosed between thetwo lines is shaded.
  • Combination Chart. Use this chart type to combine a pie chart with a column chart in the same Insight.

Types of Gauges

  • Angular Gauge. An Angular Gauge shows a single value in relation to a range of values. You can set stops, or ranges on the gauge to be displayed in certain colors, independent of the value.
  • Solid Gauge. A Solid Gauge uses a single block of color to show a single value in relation to a range. You can set stops, or thresholds, above or below which a certain color is used. The color of the fill corresponds to the range in which the data value falls.
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