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updatedAt: 2026-02-24T11:33:05.000Z
agentTools:
  projectIndex: https://help.zluri.com/llms.txt
---

# Chart Types in Zluri

When creating a widget in Zluri, users select a **dataset** and apply a **chart type** to define how the data will be visually represented. This guide outlines the available chart types, recommended use cases, and selection tips.

## How Charts Work

Each widget is a combination of:

* **Dataset** – The underlying data (e.g., users, applications, spend)
* **Chart Type** – The visualization method (e.g., bar, KPI, table)
* **Configuration** – Field selection, filters, formatting, etc.

The fields available in the dataset influence which chart types are supported.

## Supported Chart Types

### 1. Line Chart

Plots data points over time to visualize trends.

* **Use Cases**:
  * Application spend trends
  * Login activity over weeks or months
  * License growth tracking

* **Tags**: `Trendline`, `Time Series`, `Line Plot`, `Platform Analytics`

### 2. Bar Chart

**(Vertical, Horizontal, Stacked)**

Compares values across categories.

* **Use Cases**:
  * Spend by app
  * Access requests by department
  * App usage by location

* **Tags**: `Stacked`, `Predictive`, `Discrete`, `Trend analysis`

### 3. Table Chart

Displays raw, detailed data in rows and columns.

* **Use Cases**:
  * App-wise license and usage breakdown
  * User access listings
  * Contract metadata summaries

* **Tags**: `Sequential`, `Aggregated Data`, `Variations`, `Multi-field`

### 4. Big Number (KPI)

Highlights a single metric—total, average, or percentage.

* **Use Cases**:
  * Total SaaS spend
  * Number of active users
  * % license utilization

* **Tags**: `KPI`, `Summarization`, `Aggregated Metric`, `Single Value`

### 5. Pie Chart

Visualizes part-to-whole relationships using circular segments.

* **Use Cases**:
  * Spend distribution by vendor
  * Users by department
  * App usage by geography

* **Tags**: `Category`, `Segment`, `Region`, `Label`, `Status`

### 6. Histogram

Displays frequency distribution by grouping numeric values into bins.

* **Use Cases**:
  * Access duration analysis
  * User distribution by activity
  * Cost segmentation

* **Tags**: `Data Quality`, `Numeric Range`, `Clustering`, `Patterns`

### 7. Area Chart

Highlights cumulative trends with shaded areas under lines.

* **Use Cases**:
  * Cumulative license assignment
  * Monthly spend growth
  * Access growth by department

* **Tags**: `Cumulative`, `Time-based`, `Performance`, `Geographical`

## Choosing the Right Chart

| Goal                     | Recommended Chart Type |
| ------------------------ | ---------------------- |
| Show trends over time    | Line Chart, Area Chart |
| Compare categories       | Bar Chart, Pie Chart   |
| Highlight a key metric   | Big Number             |
| Display detailed records | Table                  |
| Visualize distribution   | Histogram              |

<Image align="center" src="https://files.readme.io/7c91620bb8d9ce4ece02044e999a8bfcea0fd3ce2a08908b1519955e74c1ccda-BI20.webp" />

<br />

## Chart Type Quick Reference

| Chart Type  | Best For                     | Example Use Case                |
| ----------- | ---------------------------- | ------------------------------- |
| Line Chart  | Time-based trends            | App spend trend per month       |
| Bar Chart   | Category comparisons         | Apps with highest user count    |
| Stacked Bar | Multi-dimensional breakdowns | Access levels by department     |
| Pie Chart   | Part-to-whole comparisons    | Spend by department             |
| Big Number  | Key metrics/KPIs             | Total SaaS spend                |
| Table       | Detailed reporting           | License count vs. usage         |
| Area Chart  | Cumulative analysis          | Cumulative licenses issued      |
| Histogram   | Distribution and outliers    | User count by login frequency\[ |

<Image align="center" src="https://files.readme.io/ed27492d1c36b123d35ce1d9695a5e084cd6269debf8872ae59b89ccffc27513-Screenshot_2025-07-30_at_2.53.07_PM.png" />

## Pro Tips

* Use **Flat datasets** for high-level KPIs and summaries.
* Use **Expanded datasets** for detailed, user-level views.
* Apply **DISTINCT** or groupings when using Pie, Bar, or Line charts on expanded datasets.
* When unsure, use a **Table Chart** to preview the dataset layout.