Charts and dashboards in Kolkata

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Charts and dashboards

Reporting screens built around the decisions they support, rather than every number the database happens to hold.

Data visualisation

Chosen per project

Maintainable handover

Most business dashboards fail in the same way: they show everything measurable, arranged by how easy it was to query, and nobody can tell from a glance whether today is going well. A useful dashboard answers a small number of questions somebody actually asks each morning.

Chart.js is a sensible default for building them — light, canvas-based and quick to render — provided the aggregation happens on the server. Sending fifty thousand rows to the browser to draw a line is the usual reason a reporting screen feels slow.

What we build with Chart.js

Management dashboards for sales, stock and collections

Operational screens showing today’s position at a glance

Customer-facing usage and billing charts

Reports that were previously assembled in a spreadsheet each week

Where it fits — and where it does not

Good fit when

Standard chart types — lines, bars, pies, stacked comparisons

Dashboards embedded in an existing application

Screens that must load quickly on a mid-range phone

Consider something else when

Complex bespoke visualisations, where D3 gives more control

Analysts needing to build their own reports — a BI tool fits better

Chart choice

Picking the right chart

Most dashboard confusion comes from four common mismatches.

Change over time

Line chart — never a pie.

Comparing categories

Bar chart, sorted by value.

Part of a whole

Stacked bar; pie only for two or three parts.

A single number

Show the number, large, with its trend.

How we work with Chart.js

Start from the question

Each chart earns its place by answering a question somebody actually asks, and is removed if it does not.

Aggregate server-side

The API returns points ready to plot, not raw rows for the browser to summarise.

Readable without colour alone

Labels, patterns and direct values, so the chart works when printed or seen by a colour-blind reader.

Numbers alongside

A table beneath the chart, because managers copy figures into messages and reports.

Our typical Chart.js setup

Typical Chart.js stack choices and what we use for each
ConcernWhat we use
LibraryChart.js for standard charts; D3 where bespoke visuals are needed
DataPre-aggregated by the API, with sensible cache headers
InteractionDate range and filters that update the URL so views can be shared
AccessibilityData table alternative and non-colour-dependent encoding
ExportCSV and print-friendly layout where reports are circulated

Frequently asked questions

Usually because it queries raw tables on every load and aggregates in the browser. Pre-aggregating on the server, and caching where the data only changes hourly, generally fixes it without new hardware.

If the audience is your own users inside your application, build it in. If the audience is analysts who need to create their own reports, buy a BI tool — building that is a much larger project.

Yes — scheduled PDF or CSV delivery is a common addition, and often more used than the dashboard itself.

Topics people search for

Services built with Chart.js

Tell us what you are trying to build

Describe the problem in plain language and we will tell you what it would take to solve it — the approach, the moving parts and the sensible order to build them in. No obligation either way.

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