# Understanding Tellius charts

To help you make the most of this feature, let's dive into a quick overview of each chart type used in Tellius. Whether you’re tracking trends with a line chart, comparing categories with a bar graph, or uncovering relationships with a scatter plot, each chart type brings its unique strengths to the table.

<figure><img src="https://content.gitbook.com/content/8GaK1h3pmgbR63x0ftET/blobs/faZ6KoP7QXLFOtHvzNr6/image.png" alt=""><figcaption><p>List of charts supported in Tellius</p></figcaption></figure>

### Bar Chart

Relevant for comparison queries. Bar charts are excellent for visualizing differences between groups or categories.

Example: <mark style="color:orange;">“</mark>*<mark style="color:orange;">Show profit by department</mark>*<mark style="color:orange;">”</mark>

### Line Chart

Ideal for analyzing changes and trends over time. It connects individual data points, making it easy to track rises and falls in data over intervals.

Example: <mark style="color:orange;">"</mark>*<mark style="color:orange;">Show monthly revenue trend for the past year</mark>*<mark style="color:orange;">"</mark>

### Scatter Plot

Useful for analyzing the relationship between variables, showing how one variable is affected by another.

Example:&#x20;

### KPI (Key Performance Indicator)

Relevant for tracking progress against goals. KPIs are straightforward and focus on critical data points.

Example: <mark style="color:orange;">“</mark>*<mark style="color:orange;">Show me gross profit margin for this quarter</mark>*<mark style="color:orange;">”</mark>

### Combo (Bar and Line)

Combines the clarity of bar charts with the trend-tracking ability of line charts. This chart allows for dual insights in a single view.

Example: <mark style="color:orange;">“</mark>*<mark style="color:orange;">Show me monthly sales and profit for last year</mark>*<mark style="color:orange;">”</mark>

### Pie Chart

Effective for showing proportions and compositions. It visually represents parts of a whole data.

Example: *<mark style="color:orange;">“Show me percentage of employees by department”</mark>*

### Table

Relevant for queries needing detail and precision. Tables are ideal when every data point matters.

Example: *<mark style="color:orange;">“List all IT projects with their budget, status, and team size”</mark>*

### Detail Table

Similar to a regular table but provides more granular details. It's helpful when comprehensive data representation is needed.

Example: *<mark style="color:orange;">“Sales report including customer, market, region, quantity, and country”</mark>*

### Pivot Table

Best for summarization and categorization. It allows for quick reorganization and grouping of data.

Example: *<mark style="color:orange;">“Summary of monthly sales by region and category”</mark>*

{% hint style="info" %}
**Tables vs Detailed tables vs Pivot tables**<br>

* Regular tables are straightforward and precise for listing detailed information.
* Detailed tables offer a deeper level of granularity, making them ideal for complex datasets.
* Pivot tables are best for summarizing and categorizing data, allowing quick reorganization and grouping.
  {% endhint %}

### Histogram

Useful for data distribution. It groups data into ranges, showing the frequency of values within these ranges.

Example: *<mark style="color:orange;">“Frequency distribution of daily sales last month”</mark>*

### Heatmap

Useful for visualizing complex data sets. Heatmaps use color intensity to convey data density, making it easy to spot high and low points.

Example: *<mark style="color:orange;">“Show me employee performance ratings by department and experience level”</mark>*

### Treemap

Treemap chart provides elaborate, area-based visualization for hierarchical or nested data. The large rectangles (representing tree branches) and the small rectangles (representing each node in that branch) are sized by the measure values. Treemap allows you to plot hundreds of data points that can help with quick comparisons.

Example: *<mark style="color:orange;">“Show me revenue by product categories and subcategories”</mark>*

### Sankey Diagram

Effective for showing flows and transfers between different stages or categories. It highlights the magnitude of these movements.

Example: *<mark style="color:orange;">“Show me customer journey from initial channels to final purchase for the last six months”</mark>*

### Bubble Chart

Relevant for multi-variable queries. Bubble charts can display three dimensions of data. It adds a size dimension to the traditional scatter plot, offering more context.

Example: *<mark style="color:orange;">“Compare companies by revenue, market share, and profit margin”</mark>*

### Boundary Map

Suitable for geographic boundary visualization. It's used for plotting data over specific geographic areas.

Example: *<mark style="color:orange;">“Geographical distribution of all company branches”</mark>*

### Location Map

Location maps provide geographical context to data. Ideal for displaying data points geographically. It helps in understanding spatial patterns or distributions.

Example: *<mark style="color:orange;">“Location of all customers in India”</mark>*

{% hint style="success" %} <mark style="color:green;">**Boundary maps vs Location maps**</mark>

Boundary maps are used to outline and highlight areas or regions, such as countries, states, districts, or sales territories, emphasizing their geographic limits and extents. In contrast, location maps primarily focus on displaying specific points or locations geographically, often used to pinpoint places like store locations, customer addresses, or regional offices.
{% endhint %}

### Waterfall Chart

Ideal for showing step-by-step changes. They help in understanding how each positive or negative value affects the total value over a sequence of steps.

Example: *<mark style="color:orange;">“Show me the breakdown of last year's profit, starting from total revenue and subtracting each expense sequentially”</mark>*

### KPI Target

Highlights performance against a predefined target. It's used for goal tracking and performance measurement.

Example: *<mark style="color:orange;">“Comparing actual sales against sales targets”</mark>*

{% hint style="success" %} <mark style="color:green;">**KPI charts vs KPI target charts**</mark>

KPI charts focus on visualizing key performance indicators, displaying current values of crucial metrics like sales figures, customer satisfaction, or production volumes. KPI Target charts, on the other hand, not only show the current value of a KPI but also compare it against a predefined target or goal, highlighting how the current performance measures up to the set objectives.
{% endhint %}

### Confidence Range

Useful for representing uncertainty in data. It shows potential variability and is often used in predictive models/queries.

Example: *<mark style="color:orange;">“Projected sales growth for the next quarter with confidence intervals”</mark>*

### Bar Conversion

Ideal for showing conversion rates or stages in a process. It helps in understanding progression through different stages.

Example: *<mark style="color:orange;">“Analyzing conversion rates at different stages of a sales funnel”</mark>*&#x20;

### Funnel Chart

Funnel charts are great for depicting stages in a process. Displays the reduction in data through different stages. It’s often used in sales and marketing to track the stages of the customer journey.

Example: *<mark style="color:orange;">“Show me customer journey from awareness to purchase for productAB”</mark>*

{% hint style="info" %} <mark style="color:green;">**Bar conversion charts vs Funnel charts**</mark>

Bar conversion charts are used to display conversion rates at different stages of a process, effectively showing how a value or quantity changes from one stage to the next. In contrast, funnel charts are specifically designed to represent the stages in a sales or marketing funnel, visually depicting the reduction in numbers as potential leads or customers progress through each stage towards a final action or sale.
{% endhint %}

### Growth Chart

Growth charts clearly show upward or downward trends, tracking increases or decreases over time. It's suitable for representing growth metrics.

Example:&#x20;

### Year over Year (YoY) Chart

A YoY (Year over Year) chart compares metrics from one period to the same period in previous years to illustrate trends or changes over time.

Example: *<mark style="color:orange;">“Show me sales of June this year vs June last year”</mark>*

### Cohort Charts

A cohort chart tracks and compares the behavior or performance of groups of users (cohorts) who share a common characteristic or experience within a defined time frame.

Example: *<mark style="color:orange;">“Show me retention rates of employees hired in different years”</mark>*

{% hint style="info" %} <mark style="color:green;">**YoY charts vs Cohort charts**</mark>

Year over Year (YoY) charts are used to compare data metrics across the same periods in consecutive years, highlighting trends and changes over time, such as annual growth or decline. Cohort charts, however, group users or items into cohorts based on shared characteristics or experiences during a specific period, and track their behavior or performance over time, revealing patterns within each cohort group.
{% endhint %}

### Rich KPI Chart

The Rich KPI chart is a powerful, compact visualization designed to track the trend of KPI metric over time using a mini area chart (sparkline). Given a measure and a date dimension, it highlights period-over-period change (YoY, MoM, etc.) using color-coded deltas.&#x20;

Example: *<mark style="color:orange;">Highlight sales by month per region or category and compare YoY or MoM changes</mark>*

<figure><img src="https://content.gitbook.com/content/8GaK1h3pmgbR63x0ftET/blobs/HSfQTXt5gRLIfqAQVpb3/image.png" alt="" width="375"><figcaption><p>Rich KPI chart</p></figcaption></figure>