Charts are the primary visualization components used in CORE Insights Dashboard Builder. They allow companies to analyze CORE data by transforming datasets into visual representations such as graphs, tables, maps, and key performance indicators (KPIs).
Charts are created using the Chart Builder, where you select a dataset and define how data should be grouped and measured. Each chart is connected to a single dataset, although dashboards can contain multiple charts built from different datasets to present a broader view of company data.
Charts update dynamically as fields and settings are adjusted, enabling users to explore and refine insights before saving them to a dashboard.
How Charts Work
When creating a chart, the first step is selecting a dataset. The dataset determines which fields are available for visualization.
Dataset fields are divided into two types:
- Category fields represent dimensions used to group or segment data. These fields are typically text or date-based values, such as client, activity item, or accounting date. Category fields define how data is sliced and compared within the chart and may also include user-defined bucketed fields.
- Value fields represent measurable data and are always numeric. These fields are used to calculate totals or measurements such as hours, bill amounts, or costs. When added to a chart, value fields are aggregated automatically to summarize results.
Charts are built by dragging category and value fields into the configuration shelves. Depending on the chart type, at least one category and one value field can be required.
Chart Types
CORE Insights supports multiple chart types designed for different reporting needs. Each chart type provides slightly different configuration options and determines how data can be grouped and displayed within the Chart Builder.
- XY Charts are commonly used for trend and comparison analysis and include bar charts, line charts, symbol charts, and min-max charts. These charts require at least one category field and one value field. Data values are aggregated and displayed according to the selected category. Multi-series variations allow an additional dimension to be added, enabling comparisons across another field such as year or project manager.
- Percent-of-Total Charts visualize proportional relationships within data. Pie charts, funnel charts, and word clouds display how individual segments contribute to an overall total. These charts typically require one category field and one value field.
- KPI and Indicator Charts display single key metrics and are useful for highlighting performance indicators. Supported KPI visualizations include indicators, dial gauges, and bullet bar gauges. These charts require only one value field.
- Table Charts visualizations display data in tabular form and are useful for detailed analysis. Standard tables allow multiple category and value fields to be displayed together. Grouped tables summarize values by selected categories, while expandable tables provide hierarchical views with summarized totals. Crosstab tables allow users to pivot data across an additional dimension for comparative reporting.
- Map Charts visualize geographical data and include dot maps, bubble maps, and choropleth maps. These charts require datasets that contain defined geolocation fields.
- Advanced Charts visualizations include heat maps and box-and-whisker charts. Heat maps display relationships across multiple dimensions using color intensity, while box-and-whisker charts illustrate data distribution across categories.
Chart Configuration
After fields are added, chart settings can be adjusted using configuration panels available within the Chart Builder. General settings control chart behavior, including tooltips and the maximum data points displayed. Style options allow customization of colors, axes formatting, and visual presentation. Additional configuration options appear depending on the selected chart type. For example, sorting options are available only for charts that support ordering, and layered charts provide additional configuration for multi-series visualizations.
Filters can be applied directly to a chart to limit displayed data without affecting other dashboard components.
Derived Fields
Chart Builder allows you to create additional calculated or derived fields without modifying the original dataset.
Calculated fields allow you to create new values using formulas based on existing dataset columns. Calculated fields are commonly used to create custom metrics that are not available directly in the dataset.
Bucketed columns can be used to group data into ranges or categories, such as grouping countries into regions. Transformations allow calculated fields to be created using formulas based on existing dataset values.
These derived fields enable more flexible analysis directly within the chart.
Filters
Filters can be applied to a chart using the Filters panel or the filter icon within the Chart Builder. Chart-level filters limit the data displayed in the selected visualization while leaving other dashboard charts unchanged.
Charts rely on datasets to supply fields and calculations. Check Understanding Datasets in CORE Insights help article to learn how datasets work.