Sales Forecasting Dashboard
A multi-panel dashboard on three years of retail data: monthly revenue trends, product-category performance, regional heatmaps and a six-month machine-learning forecast with confidence intervals.
Data Visualization Platform
Dashboards and reports designed around decisions
Interactive dashboards, filters and scheduled reports built around the questions a team asks every week, not around the chart types a tool happens to offer.
Indicative starting price: $14,999 (USD). Final price depends on scope.
Technical notes
- Built on open-source tools such as Apache Superset or Plotly Dash, or custom, depending on how much control and maintenance your team wants.
- Connects to CSV, Excel and SQL sources; dashboards read prepared tables rather than raw files.
- Scheduled PDF reports and role-based access to sensitive views are available.
From question to chart
We start from the question a person is asking and pick the chart that answers it. This is the logic we apply.
| The question | Chart | Why |
|---|---|---|
| Is it going up or down? | Line, with the prior period as a second line | Shows direction and gives a baseline to judge it against. |
| Which is biggest? | Sorted horizontal bars | Length is the easiest quantity to compare; sorting removes the hunt. |
| Are we on target? | Single number with a target and variance | One glance; no chart needed. |
| Where is it happening? | Map or regional heat grid | Location is the question; used only when geography matters. |
| What is behind this number? | Drill-down table | Lets a reader verify the number instead of trusting it. |
Problems this solves
- Stakeholders ask for the same numbers repeatedly because there is nowhere to look them up.
- Existing dashboards are cluttered and nobody trusts them.
- Reports are assembled by hand and sent as attachments.
- Different people need different views of the same data.
What you receive
- Interactive dashboards with filters for the dimensions you actually use
- Scheduled PDF or email reports
- Role-based access to sensitive views
- Connections to CSV, Excel and SQL sources
- A short guide to how each metric is calculated
See a working example
Our public demo dashboard has working filters and charts. Every figure on it is sample data, and it says so on the page.
How the work runs
Each phase has an input from you and a written output from us. Training and ongoing changes are agreed separately.
| Phase | What happens | You provide | You receive |
|---|---|---|---|
| Step 1Questions and audience | Identify who uses the dashboard, which decisions it supports and which questions they ask every week. | A short list of questions and the people who ask them. | A one-page brief for each dashboard. |
| Step 2Design the views | Choose metrics, comparisons and drill-downs. Sketch each view before building. | Feedback on the sketches. | Approved wireframes. |
| Step 3Build | Connect the data sources and build dashboards, filters and scheduled reports. | Access to the data, or the clean tables from an analytics project. | Working dashboards on your data. |
| Step 4Test with real users | Check that numbers match trusted reports and that users can find answers unaided. | Two or three users for a short session each. | A list of fixes and a metric guide. |
| Step 5Release and train | Set permissions, schedule reports and walk users through the dashboards. | The list of who may see what. | Live dashboards and a short user guide. |
Related work
Anonymised client projects. Client names are withheld because of confidentiality; the project page explains each one.
Interactive Data Visualisation Tool Suite
A no-code, drag-and-drop dashboard builder that connects to CSV, Excel and SQL sources and generates charts, pivot tables and geo maps, with scheduled PDF reports and role-based access control.
From the blog
Practical articles from the engineers on this topic.
Why Your Business Needs a Data Visualisation Strategy in 2026
Most dashboards get built, admired once, and then ignored. A visualisation strategy is mostly about deciding which questions deserve a screen, defining each number once, and making the …
FAQ
Frequently asked questions
Do you build dashboards in Power BI or Tableau?
Our work is built on open-source tools or custom code. If you already use a tool such as Power BI, tell us and we will say honestly whether we are the right fit.
Can I see an example?
Our public demo dashboard shows the style of interface we build. All its figures are sample data, and it says so on the page.
Do you build with a specific tool?
We choose between open-source options such as Apache Superset or Plotly Dash and custom builds depending on how much control and maintenance your team wants.
How is the work priced?
The 'starting at' figure is indicative. After a short discovery conversation we share a written scope and an estimate based on what the project actually involves.
Who owns the code and the data?
This is agreed in writing before work starts. Our default is that you own what we build for you, and that your data stays in systems you control.
Dashboards nobody trusts or uses?
Show us what exists today and the decisions it should support. We will tell you what we would change.