> ## Documentation Index > Fetch the complete documentation index at: https://docs.usedatabrain.com/llms.txt > Use this file to discover all available pages before exploring further. # Building Charts in Databrain > A guide to creating the right visualization for your data. **A guide to creating the right visualization for your data** Welcome! This guide helps you build charts in Databrain quickly and confidently. Whether you're tracking a single number, comparing categories, or building interactive dashboards, you'll find the right approach here with step-by-step instructions, real examples, and visuals for each scenario. ### **How charts work** Every chart in Databrain is built from two ingredients: * **Dimensions**: what you group by (dates, regions, categories) * **Measures**: the numbers you calculate (Count, Sum, Average) To build any chart: 1. Start with the problem statement\ A good Databrain chart is not chosen by chart name first. Start with the sentence you are trying to answer: Are we on track? What\ changed? Where is the issue? Which segment is different? Which records need action? Once that sentence is clear, the chart type\ usually becomes obvious. 2. Build the metric shape\ Every chart starts with dimensions and measures. Dimensions answer "by what" - by month, region, segment, status, product,\ customer, country. Measures answer "how much" - revenue, count, average duration, conversion rate, spend, margin, or score. 3. Turn the metric into an experience\ The chart is only the first layer. In Databrain, the same metric can become much more useful with Group By, drill down, switch axes,\ chart click action, dashboard filters, metric filters, app filters, forecasting, downloads, and AI Summary. That feature stack is what turns a static visual into a guided analytics workflow. ### **Quick chart picker** | If you require | Use these Databrain charts | Why | | ----------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------- | | **One important number** | [Single Value](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-setup/single-value), Gauge V2, Progress Bar V2, Linear Gauge V2 | Use for KPI status, target progress, quota, SLA, utilization, health score, or progress | | **Compare categories** | Bar (Stack, Horizontal Stack), [Hybrid Bar](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-setup/hybrid-bar) | Use dimensions such as region, product, status, customer tier, or sales rep. | | **Trend over time** | Line, Area, Stacked Area | Use a date dimension and one or more measures. Add forecasting when the question is forward-looking. | | **Part of a total** | Pie, Doughnut, Rose, Stacked Area, [Hierarchical Map](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-setup/tree-map) | Use only when the number of categories is small enough for users to read. | | **Detailed records** | [Table, Horizontal Stack Table](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-setup/table-advanced) | Use when exact rows, values, statuses, links, or downloads matter more than shape. | | **Cross-tab analysis** | [Pivot Tables:](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-setup/pivot-table) Pivot Table 2, Pivot Table 3 | Use rows, columns, and measures to summarize data across two or more dimensions | | **Stages and movement** | [Funnel V2, Waterfall V2, Sankey](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-setup/funnel-sankey-waterfall) | Use for conversion stages, cumulative change, source-to-target flows, and process drop-offs. | | **Distribution and outliers** | Histogram, Boxplot, Scatter, Bubble V1 | Use for spread, skew, clusters, unusual points, and relationship between numeric variables. | | **Relationships** | [Network](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-setup/network), Sankey | Use source, target, and value columns to show links, affinity, dependencies, or flows | | **Geography** | [World Map, Indian States, USA Map, USA Map with](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-setup/maps) [Scatter, USA Map with Bar](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-setup/maps) | Use when region names match the chosen map geography. | | **Task timelines** | [Gantt](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-setup/gantt) | Use start date, end date, task label, and optional status or owner fields. | ### **Standard Databrain build pattern** 1. Create or edit a metric from the dashboard. 2. Add dimensions and measures, or use Custom SQL/Python when the data shape needs preparation. 3. Click the Charts icon and choose the chart type that matches the business question. 4. Open Settings and use appearance and actions to assign axes or roles. 5. Use Appearance to set colors, labels, legends, number format, prefix/suffix, thresholds, and chart-specific styling. 6. Use Actions to enable Group By, drill down, switch axes, click actions, forecasting, sorting, or secure underlying-data behavior where relevant. 7. Save to Dashboard and test the chart with filters, drill paths, and embed/app-filter behavior if it will be customer-facing ### **Requirement-to-chart playbook** | Requirement | Recommended chart | Data setup | Databrain features to enable | | ------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------- | | Executive KPI tile | Single Value | One aggregate measure such as SUM(revenue), COUNT(order\_id), AVG(score). | Metric expression, comparison value, conditional formatting. | | Progress toward a Target | Gauge V2, Linear Gauge V2, Progress Bar V2 | One measure plus optional min, max, or target columns. | Threshold colors, prefix/suffix formatting, target markers. | | Compare performance by category | Bar | Dimension = category Measure = revenue, count, margin, or score | Sort, chart labels, switch Y axis, dashboard filter. | | Many category names or long labels | Horizontal Stack | Use the category as the vertical label and the measure on the horizontal axis. | Right-size labels, sort descending, show top categories. | | Each bar split by status/channel/segment | Bar Stack or Horizontal Bar Stack | Dimension: month/region/category Measure: count or sum. Group By: status/channel/segment | Group By, dynamic options, legend, dashboard filter. | | Month-over-Month trend | Line, [Time Series](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-setup/time-series), Area | Date dimension plus one or more measures. | Time grain, dynamic group by, switch Y axis | | Compare actuals and forecast or two units | Combo or Horizontal Combo | One dimension plus at least two measures, usually bar plus line. | Multi-scale combo for measures with different units. | | Understand movement from starting value to ending value | Waterfall V2 | Category dimension plus measure representing increase, decrease, or total. | Use for revenue bridge, spend variance, margin movement. | | Source-to-Target movement | Sankey | Source dimension, target dimension, value measure. | Use for channel journeys, process handoffs, budget movement. | | Conversion from lead to customer | Funnel V2 | Stage dimension plus measure for count/value at each stage. | Use clear stage order, show conversion/drop-off. | | Relationships or Affinity | Network | Source, target, and value/strength columns. | Use for entity relationships, co-occurrence, dependencies, supplier-product networks. | | Hierarchy and contribution together | Hierarchical Map | Dimension hierarchy plus measure. | Use for category/subcategory/product contribution. | | Share of Total | Doughnut, Pie, Rose | Small number of categories plus one measure. | Avoid too many slices, use bar when exact comparison matters. | | Row-level Validation or audit view | Table | Dimensions and measures as visible columns. | Download, hide columns, conditional formatting, metric filters. | | Excel-like Summary | Pivot Table 2 or Pivot Table 3 | Rows, columns, and aggregate measures. | Use for finance, operations, account, and cohort summaries | | Spot Outliers | Boxplot, Scatter, Bubble V1, Histogram | Numeric fields for distribution, relationship, or size. | Use filters to isolate segment, table to inspect underlying rows. | | Geographic Performance | World Map, Indian States, USA Map, USA Map with Scatter, USA Map with Bar | Region/country/state dimension plus measure. | Region names must match the selected map geography. | | Project/Task Timelines | Gantt | Task label, start date, end date, optional owner/status, and measure if needed. | Use filters for owner, project, status, or priority. | ### **Analysis patterns** Use this section for any analysis requirement instead of a chart name. The goal is to translate the analysis intent into a Databrain build pattern while keeping the positioning clear: Databrain can visualize, filter, drill, summarize, and operationalize the analysis. | Analysis need | Databrain story | Product-safe implementation guidance | Suggested features | | --------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Outlier detection | Use Time Series, Line, [Trend Analyzer](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-setup/trend-analyzer), Boxplot, Histogram, Scatter, Bubble V1, and Table. The story is: show the trend or distribution, make the unusual point easy to see, then let the user filter, drill, or open the records behind it. | Native pattern: Visual outlier review, AI Summary, filters, and underlying-data inspection | Time Series, [Boxplot](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-setup/boxplot), [Histogram](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-setup/histogram), Scatter, Bubble, Chart Actions, Metric AI Summary, Drill Down | | Clustering and Segmentation | Use Group By feature for Bar Stack, Horizontal Stack, Scatter, Bubble V1, and dashboard filters. The story is: split the chart by customer segment, cohort, product family, region, risk band, or generated cluster label. | Native pattern: dimensions, Group By, dynamic options, filters | [Group By](https://docs.usedatabrain.com/guides/metric/group-by) | | What-if / Scenario Analysis | Use Single Value, Combo, Line, Gauge/Progress, and Table. The story is: compare baseline vs selected scenario and show the impact on headline KPI, trend, and detailed drivers. | Native pattern: filters, Dynamic Property, and scenario columns/measures | [Dynamic Property](https://docs.usedatabrain.com/guides/metric/dynamic-property#dynamic-property) | | Affinity / Graph Analysis | Use Network and Sankey. The story is: show which entities are connected, how strong the relationship is, and where flow, dependency, or co-occurrence is concentrated. | Native pattern: source, target, and value visualization. | [Network](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-setup/network#network-chart), [Sankey](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-setup/funnel-sankey-waterfall#sankey-setup) | | Geospatial Analysis | Use World Map, Indian States, USA Map, USA Map with Scatter, USA Map with Bar The story is: show where performance, risk, demand, supply, or exceptions are concentrated geographically. | Native pattern: geography dimension plus measure. Keep country/state/region names aligned with the selected map geography and use dashboard filters for territory, segment, or time range | [Map Charts](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-setup/maps#map-charts), [Dashboard](https://docs.usedatabrain.com/guides/filters/dashboard-filter#dashboard-filter) [Filter](https://docs.usedatabrain.com/guides/filters/dashboard-filter#dashboard-filter), [Metric Filter](https://docs.usedatabrain.com/guides/filters/metric-filter) | | Augmented Analysis | Use AI Summary, Metric Summary, forecasting, drill down, and filters alongside the chart. The story is: help the viewer understand what changed, why it matters, and where to investigate next. | Native pattern: explain, summarize, forecast, and guide exploration from the metric view | [AI Summary](https://docs.usedatabrain.com/guides/metric/ai-summary), [Metric](https://docs.usedatabrain.com/guides/metric/metric-summary#metric-summary) [Summary](https://docs.usedatabrain.com/guides/metric/metric-summary#metric-summary), [Chart Actions](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-actions#chart-actions), [Forecasting](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-actions#9-forecasting), [Drill Down](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-actions/drill-down#drill-down) | ### **Interaction features that make charts useful** | Feature | Use it when | | -------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Group By | When one column contains the breakdown values, such as status or channel, Group By turns those values into chart series. Use it with stacked bars and lines. | | Drill Down | Use when the dataset has hierarchy: Region > Country > City, Year > Quarter > Month, Category > Product. Databrain applies the clicked value as a filter and re-groups by the next dimension | | Cross-dashboard Drill Down | Use when a click in one metric should update the rest of the dashboard context. | | Switch X Axis / Switch Y Axis | Use when end users should compare the same metric by different dimensions or measures without duplicating charts. | | End user measures and dimensions | Use for self-service exploration where the viewer can change dimensions and measures on a metric card | | Chart Click Action / Card Click Action | Use when a data point or card should take the user to a detail page, related metric, dashboard, or configured URL | | Dashboard filters | Use when one control should update multiple charts on the dashboard. | | Metric filters | Use when a filter is specific to one chart and should not affect the full dashboard. | | App filters | Use in embedded dashboards when the host app or guest token should pre-scope data for tenant, user, date, region, or role | | Forecasting | Use on trend-oriented charts when the client wants future periods, expected direction, or forecast comparison. | | AI Summary | Use when the viewer needs a quick natural-language explanation of a metric in full-screen mode. | | Downloads and Underlying Data | Use when customers need to export chart data, inspect records, or validate the calculation. | ### **Chart catalog** #### **KPI Cards** | Chart | What it is used for | Setup and feature tip | | ------------------------------------ | ------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------- | | Single Value | Shows one headline KPI such as total revenue, churn rate, or open tickets. | One measure or a dimension that resolves to one value. Add metric expression, comparison, and conditional formatting. | | Gauge V2 | Shows score, utilization, SLA, capacity, or risk against a range. | One measure, optional dimensions, min/max, thresholds. Prefer V2 for new dashboards. | | Linear Gauge V2 | Shows progress on a horizontal scale with threshold bands. | One measure plus optional min/max or range configuration. | | Progress Bar V2 | Shows completion percentage, usage vs limit, quota progress, or onboarding progress. | One measure and optional max/min. Use when a simple horizontal progress story is clearer than a radial gauge. | | Gauge, Linear Gauge, Progress Bar V1 | Legacy variants that may appear in older workspaces or existing dashboards. | Use V2 variants for new chart work when available. | #### **Tables** | Chart | What it is used for | Setup and feature tip | | ---------------------- | --------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------- | | Table | Shows exact rows and values for audit, operations, account lists, and validation. | Dimensions and measures as columns. Add downloads, hidden columns, formatting, and filters. | | Trend Analyzer | Shows trend-focused metric analysis over time. | Use for time-oriented datasets where the customer needs direction, change, or pattern review. | | Pivot Table | Legacy pivot-style summary. | Use a pivot variant when rows, columns, and aggregate measures are needed. | | Pivot Table 2 | Cross-tab summary for business users who expect Excel-like slices. | Requires aggregate measures and one or more dimensions. | | Pivot Table 3 | More configurable pivot for row/column style summaries. | Use for finance, cohort, account, product, or operational matrix views. | | Horizontal Stack Table | Table plus compact in-row bar comparison. | Use when the exact value and visual magnitude should appear together. | #### **Line and Time Series** | Chart | What it is used for | Setup and feature tip | | ----------- | ------------------------------------------------------------------ | ---------------------------------------------------------------------------------------------------- | | Line | Shows trend over ordered categories or dates. | Dimension plus one or more measures. Good for revenue, users, tickets, defects, conversion trend. | | Time Series | Shows measures over a date/time dimension with time grain control. | Requires a date dimension and measures. Supports daily, weekly, monthly, quarterly, yearly grouping. | #### **Bar** | Chart | What it is used for | Setup and feature tip | | -------------------- | ------------------------------------------------------- | ------------------------------------------------------------------------------------------------------ | | Bar | Compares categories vertically. | Dimension plus measure. Good first choice for ranked category comparison. | | Bar Stack | Compares total and composition in one vertical bar. | Dimension plus measure, with Group By or multiple measures for segments. | | Hybrid Bar | Mixes stacked and non-stacked bars in the same view. | Use when part of the comparison needs stacking and another part should remain standalone. | | Horizontal Bar | Compares many or long category labels. | Same as bar, but easier to read for long labels. | | Horizontal Bar Stack | Compares composition across many long-label categories. | Use for status by team, training by management level, cases by reason, or customer segment by product. | | Gantt | Shows task, project, or process timelines. | Needs task labels plus start/end date fields; useful for milestone tracking. | #### [**Combo**](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-setup/combo-chart) | Chart | What it is used for | Setup and feature tip | | ------------------------------- | --------------------------------------------------------------- | ---------------------------------------------------------------------- | | Combo (Multi-Scales) | Combines bars and lines when measures use different units. | Use for revenue and margin percent, volume and price, actual and rate. | | Horizontal Combo (Multi-Scales) | Horizontal variant for long categories with two measure scales. | Use when category labels need horizontal space. | | Combo (Single-Scale) | Combines visual forms when measures share one scale. | Use when bars and line belong to the same unit or comparable range. | | Horizontal Combo (Single-Scale) | Compares actual vs target on one horizontal scale. | Use for target tracking by category. | #### **Area** | Chart | What it is used for | Setup and feature tip | | ------------ | ----------------------------------- | ------------------------------------------------------------------------------ | | Area | Emphasizes magnitude over time. | Use when the filled shape helps communicate volume, backlog, demand, or usage. | | Stacked Area | Shows composition change over time. | Use for segment mix, channel mix, product contribution, or usage by plan. | #### **Pie** | Chart | What it is used for | Setup and feature tip | | -------- | ------------------------------------------------------------------ | -------------------------------------------------------------------- | | Doughnut | Shows share of total with a clean center space. | Use for a small number of categories. | | Pie | Shows simple part-to-whole distribution. | Use sparingly, choose bar if exact comparison is important. | | Rose | Shows part-to-whole with stronger visual emphasis on segment size. | Use when the category count is small and relative magnitude matters. | #### **Distribution** | Chart | What it is used for | Setup and feature tip | | ------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------- | ------------------------------------------------------------------------------------------------- | | Histogram | Shows how many records fall into numeric ranges. | Numeric dimension plus measure/count. Use for age bands, spend buckets, order value distribution. | | BoxPlot | Shows median, quartiles, spread, and outliers. | Needs enough numeric columns/values. Use for outlier and distribution checks. | | Scatter | Shows relationship between two numeric variables. | X and Y axes as dimensions/measures. Use for correlation and outlier discovery. | | Bubble | Scatter with a constant bubble-size multiplier. | Use when all points can share the same visual size scale. | | [Bubble V2](https://docs.usedatabrain.com/guides/visualizations-actions-and-appearance/chart-setup/bubble-chart-v2) | Scatter where bubble size is driven by a measure. | Use when X, Y, and size together explain segment value, risk, volume, or priority. | #### **Funnel and Flow** | Chart | What it is used for | Setup and feature tip | | ------------ | ------------------------------------------------------- | -------------------------------------------------------------------------------------------- | | Funnel | Legacy funnel for stage drop-off. | Use Funnel V2 for new work when available. | | Funnel V2 | Shows conversion stages and drop-off. | Stage dimension plus measure. Good for sales, onboarding, claims, approval workflows. | | Waterfall | Legacy waterfall for cumulative change. | Use Waterfall V2 for new work when available. | | Waterfall V2 | Explains increases/decreases from start to final value. | Use for variance bridge, P\&L movement, budget vs actual. | | Sankey | Shows flow from source to target. | Needs source, target, and value. Use for journey, allocation, handoff, or movement analysis. | | Network | Shows graph-style nodes and links. | Needs source, target, value. Use for relationships, affinity, dependencies, co-occurrence. | #### **Hierarchical** | Chart | What it is used for | Setup and feature tip | | -------- | ---------------------------------------------------- | -------------------------------------------------------------------------- | | Tree Map | Shows hierarchy and contribution in a compact space. | Dimension plus measure. Use for category/subcategory/product contribution. | #### **Maps** | Chart | What it is used for | Setup and feature tip | | ------------------- | ------------------------------------------------------ | ---------------------------------------------------------------------- | | Indian States | Shows values by Indian states or territories. | Region dimensions must match Indian map names; measure colors regions. | | US Map | Shows values by US states. | Use state names matching the map geography. | | US Map with Scatter | Adds point/scatter overlay to the US map. | Use for event density, store locations, incidents, or demand points. | | US Map with Bar | Adds bar comparison beside or over the US map context. | Use when geography and ranked values should be read together. | | World Map | Shows values by country. | Country names must match expected world map names. |