Dashboards That Load in Seconds, Even at Millions of Rows
A good dashboard answers a few questions at a glance, for a specific person, every time they open it. Most dashboards fail because they try to answer everything for everyone, or because they take thirty seconds to load and nobody waits.
We design dashboards around decisions and build them on data structured for speed. Large datasets are pre-aggregated, stored in databases built for analytics, and refreshed incrementally, so a chart over fifty million rows feels as quick as one over five hundred.
This is for you if
- ✓Your dashboard takes so long to load that people stopped opening it
- ✓You have millions of rows of orders, events or readings and spreadsheets have given up
- ✓You need a dashboard inside your own product for your customers
- ✓Leadership wants one page that shows how the business is doing this week
This is probably not for you if
- ✕The underlying numbers are not trusted yet — fix the definitions first, or the dashboard just spreads the confusion faster
We would rather tell you now than take the project and disappoint you.
Worth knowing: Slow dashboards are almost never a charting problem. They are a data problem: every view recalculating totals from raw rows. Pre-computing the totals people actually look at — by day, by region, by product — often turns a forty-second load into a one-second one without changing a single chart.
What you get
Designed around decisions
Each dashboard built for a named audience and the questions they ask, with the most important number first.
Built for big data
Aggregations, materialized views and columnar engines such as BigQuery, ClickHouse or DuckDB, so millions of rows stay fast.
The right chart
Lines for trends, bars for comparisons, tables when people need exact numbers. No 3D pies.
Filters that do not break it
Date ranges, segments and drill-downs designed with the data model, so every combination stays fast.
Accessible and mobile-friendly
Color-blind-safe palettes, readable labels, and layouts that still work on a phone.
Refresh you can trust
Scheduled or incremental updates with a visible "last updated" time, and an alert if a refresh fails.
Power BI, Looker Studio or a custom dashboard?
| Power BI | Looker Studio | Custom (React) | |
|---|---|---|---|
| Cost | Per-user licences to share reports | Free | Build cost, then hosting only |
| Best for | Microsoft 365 companies and internal reporting | Google Analytics, Ads and Sheets data | Dashboards inside your product, or very large data |
| Large datasets | Good with a proper model and aggregations | Slows down without a fast source behind it | As fast as the database behind it |
| Branding and control | Limited | Limited | Complete |
For internal reporting, Power BI or Looker Studio is usually the right and cheaper answer. Custom dashboards earn their cost when they face your customers, or when the data is too big for a BI tool to handle comfortably.
How we keep millions of rows fast
- Pre-aggregate — Totals by day, week and segment computed once, so charts read thousands of rows instead of millions.
- Use a columnar engine — Analytics databases read only the columns a chart needs and compress them heavily, which is how they scan hundreds of millions of rows in seconds.
- Partition by time — Most questions are about recent data, so the database skips the months it does not need.
- Refresh incrementally — Only new rows are processed on each refresh, instead of rebuilding everything every night.
- Cache the common views — The views most people open are computed before the morning rush.
Tools we use
BI tools for internal reporting, custom code when the dashboard is part of your product.
BI tools
Power BI, Looker Studio, Metabase
Custom charts
React, ECharts, D3, hand-built SVG
Fast data
BigQuery, ClickHouse, DuckDB, Postgres materialized views
Pipelines
Scheduled SQL, dbt, Python jobs
Not sure whether a dashboard is what you actually need? Send over what you are trying to fix and we will tell you straight — including if a smaller job would do it.
Ask us first →How it works
Who and what for
The audience, the questions and the decisions, agreed before any chart is drawn.
Data check and quote
We confirm the data can answer those questions fast enough, then quote a fixed price.
Build and review
A working draft early, refined with the people who will use it.
Launch and train
Refresh schedules and alerts switched on, and a short walkthrough for the team.
Work you can check
Real work that uses the same skills. Every card links to something you can open and inspect yourself.
Pulse dashboard template
Our open-source React dashboard: sortable tables and hand-drawn SVG charts in a color-blind-safe palette.
Collected and checked dataAnswering services compared
Every provider's prices read from its own website, turned into comparable plans, and dated.
Product, built and launchedCrewCalculator
Thirteen building-trade calculators that draw every result to scale and check it against building code.
Questions
How much does dashboard development cost?
A Power BI or Looker Studio dashboard on clean data starts at $1,800. Custom dashboards built into your product, or dashboards over very large datasets that need a data pipeline behind them, usually run $5,000–$20,000.
Can dashboards handle millions of rows?
Yes, when the data is prepared for it. Raw rows go into an analytics database, the totals people look at are computed in advance, and the dashboard queries those. Hundreds of millions of rows are routine for engines like BigQuery and ClickHouse.
Do you build Power BI dashboards?
Yes, including the data model behind them, which is where most Power BI performance problems actually live. We also build in Looker Studio and Metabase, or custom in React when those fit better.
Can you put dashboards inside our app?
Yes, in two ways. Embedding a BI tool is quick but comes with per-viewer licensing and limited styling. Building the charts directly into your app costs more up front and nothing per viewer.
How often can the data refresh?
Anything from daily to near real time. Most business dashboards are fine refreshed hourly or overnight; live operational screens can update every few seconds when the data source supports it.
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