• 3 min read

Sample real estate dashboard

This page shows how to build a complete dashboard using a single data source. It demonstrates all available chart types and helps you understand how filters and charts work together.

A computer monitor displaying various charts and graphs with tabs for country, property type, and stage selection, surrounded by plants and decor.

Table of Content

  1. What this dashboard demonstrates

  2. Data source

  3. Filters

  4. Chart overview

  5. Layout considerations

  6. Maintaining the dashboard

What this dashboard demonstrates

This dashboard combines multiple chart types in one place. It shows how different perspectives on the same data can support a clear and consistent story.

You will learn how to:

  • connect one data source to multiple charts

  • use filters that work across all components

  • combine different chart types without creating conflicts

  • structure content in a way that remains easy to maintain

Sample Dashboard

Country(choose up to 10)
Property Type(choose up to 10)
Segment
Pie Chart: Distribution of property types
Bar Chart: Property Type
Floating Bar Chart: Price Range
Line Chart: Trend over time
Line Chart: Trend over time (multiple metrics)
Composed Chart: Compare volume vs. value
Table: Detailed view
#CityProperty TypeListingsTransactionsRevenue
1HamburgApartment1204522500000
2BerlinHouse803018000000
3MunichVilla602225000000
4ParisApartment1405030000000
5LyonHouse903514000000
6MadridApartment1104016000000
7BarcelonaVilla702527000000
8HamburgHouse1003817500000
9ParisVilla652029000000
10MadridHouse853219000000

Data source

All charts on this page use the same dataset. This ensures consistency and allows filters to apply across the entire dashboard.

The dataset includes:

  • locations such as country and city

  • property types and segments

  • metrics such as listings, transactions, and revenue

  • a time dimension for trend analysis

Make sure the data is clean and complete. Inconsistent or missing values can affect multiple charts at once.

Filters

This dashboard uses three filters to control the data:

  • Country (multi select)

  • Property type (multi select)

  • Segment (single select)

These filters are shared across all charts. Avoid adding filters that only affect a single chart, as this can lead to empty states and a confusing user experience.

Chart overview

Each chart highlights a different aspect of the data:

  • Pie chart shows the distribution of property types

  • Bar chart compares transactions across cities

  • Floating bar chart visualizes the range between listings and transactions

  • Line chart displays trends over time

  • Composed chart combines volume and revenue in one view

  • Table provides a detailed breakdown

Together, these charts create a balanced overview without overwhelming the user.

Layout considerations

Arrange charts in a way that supports readability and comparison.

  • Use an even number of charts where possible

  • Place related charts next to each other

  • Use full-width components like tables to provide detail at the end

  • Start with high-level insights and move toward more detailed views

Maintaining the dashboard

Since all charts rely on the same data source, updates should be made carefully.

  • Keep naming consistent across dimensions and values

  • Avoid adding unnecessary complexity

  • Check how changes affect all charts and filters

  • Update the data regularly to keep the dashboard relevant

A well-structured dataset ensures that the dashboard remains stable and easy to extend.