Custom Data Visualisation Services
Custom Charts, Interactive Visualisations, and Data-Driven Graphics That Communicate With Clarity and Impact
We provide custom Data Visualisation services that design and build compelling visual representations of data — from interactive web charts and maps to infographics, animated data stories, and embedded analytics components. Our data visualisation work combines data expertise, visual design skill, and technical development to produce visualisations that are both analytically accurate and visually excellent.
Do you need custom visualisations that go beyond what standard BI tools provide? Are you publishing data publicly and need it to look as good as it works? Do you have complex data relationships that standard chart types cannot convey? Techmits IT Solutions designs and builds custom visualisations using D3.js, Chart.js, Recharts, and other visualisation libraries — creating purpose-built visual representations for any data and any audience.
We deliver data visualisation for businesses, publishers, and organisations across India, the UK, Australia, the USA, Canada, UAE, and the Middle East — building embedded product analytics, public data journalism visualisations, interactive map-based data presentations, custom chart types for specific domain needs, and data-driven infographics for marketing and communication purposes.
Why Choose Techmits for Data Visualisation?
Great data visualisation requires the rarest combination in digital work: deep understanding of data, expertise in visual communication, and technical development capability. Most teams have one or two of these, rarely all three. At Techmits IT Solutions, we bring all three to every visualisation project — producing work that is analytically sound, visually excellent, and technically well-built.
Custom Chart Development
We build custom chart types that standard libraries cannot produce — unique layouts, novel encodings, domain-specific visualisations — using D3.js and WebGL for complete flexibility in visual representation.
Interactive Visualisations
We build interactive charts with filtering, zooming, hover details, animated transitions, and user-driven exploration — enabling audiences to engage with data at their own depth of interest.
Geographic Data Mapping
We build interactive map-based visualisations — choropleth maps, point maps, flow maps, and custom map layers — making geographic data patterns immediately visible and explorable.
Responsive & Accessible
We build visualisations that work across all device sizes and that meet accessibility standards — including colour-blind-safe palettes and screen reader support for data tables.
Data Story Design
We design data stories — narrative-driven data presentations that guide audiences through findings with a combination of visualisation, annotation, and text — for reports, presentations, and web publications.
Infographic Design
We design and produce data-driven infographics — combining accurate data visualisation with compelling graphic design — for marketing, public reporting, and communication purposes.
How We Build Data Visualisations
Our Data Visualisation Process
Data & Audience Analysis
We understand the data, the audience, the communication goal, and the delivery context — establishing the design requirements before any visualisation approach is chosen.
Visualisation Concept
We select and sketch visualisation approaches — proposing 2–3 concept directions that suit the data and communication goal — for client review and direction.
Visual Design
We design the selected visualisation — colour, typography, labels, annotations, and all visual elements — to professional presentation standard.
Development
We build the visualisation using appropriate libraries (D3.js, Chart.js, Mapbox, Recharts) — implementing interactions, responsive behaviour, and data binding.
Responsive Testing
We test across devices — desktop, tablet, mobile — ensuring the visualisation adapts appropriately and remains usable on every screen size.
Data Validation
We validate visualisation output against source data — confirming accuracy of every value, calculation, and visual encoding.
Audience Testing
We test with representative audience members where appropriate — confirming the visualisation communicates what it is designed to communicate.
Delivery
We deliver the final visualisation in the required format — embedded code, standalone web page, static export, or handover of source files.
Everything You Need to Know About Data Visualisation
Get answers to questions about visualisation approaches, tools, accessibility, interactivity, map-based visualisation, responsive design, and how to choose the right visualisation for your data.
When should I use custom data visualisation vs a BI tool?
Standard BI tools (Power BI, Tableau) are excellent for dashboard and reporting use cases where standard chart types work well. Custom visualisation is the right choice when: you need visualisation types that BI tools do not provide; you are embedding analytics in a product with specific design requirements; you are publishing data publicly and need pixel-perfect visual quality; you have domain-specific data relationships that require novel visual encodings; or the interactivity and animation you need exceeds BI tool capabilities.
What is D3.js and why is it used for custom visualisation?
D3.js (Data-Driven Documents) is a JavaScript library for producing dynamic, interactive data visualisations in web browsers. It provides complete control over the visual output — any chart type, any layout, any interaction — making it the industry standard for custom, complex, and novel data visualisations. D3.js has a steep learning curve, which is why custom D3 visualisations are typically built by specialist developers. The output is SVG or Canvas rendered in the browser, providing high-quality visuals at any resolution.
How do you ensure data visualisations are accessible?
Accessibility in data visualisation requires several considerations: colour choices that work for colour-blind users (avoiding red-green distinctions, using perceptually uniform colour scales); sufficient contrast between visual elements and background; text alternatives for chart data (underlying data tables); keyboard navigable interactive elements; and screen reader compatible markup for key data values. We implement accessibility requirements by default in all visualisation work and can produce WCAG 2.1 AA compliant visualisations where required.
Can visualisations handle large datasets?
Large datasets present both data loading and rendering challenges. We address these through: data aggregation at the server (presenting summary statistics rather than individual records for large datasets), pagination or virtual rendering for large tables, canvas-based rendering (faster than SVG for large point datasets), progressive loading (loading visible data first, then expanding), and client-side data processing with efficient algorithms. The approach depends on your specific data volume and the type of visualisation required.
Can you build map-based visualisations with our geographic data?
Yes. We build interactive map visualisations using Mapbox GL JS, Leaflet, and Google Maps — including choropleth maps (areas coloured by value), point maps (individual locations), heat maps (density), flow maps (movement between locations), and custom overlay maps using your own geographic boundaries. We work with standard geographic formats (GeoJSON, Shapefile) and can build custom boundary files from administrative boundary data.
What formats can you deliver visualisations in?
We deliver visualisations in the format appropriate for your use case: JavaScript code for embedding in web pages or applications (HTML, React component, or Web Component); standalone HTML files for internal distribution; static exports (PNG, SVG) for print and presentations; animated GIFs or MP4 videos for social media and presentations; and fully documented source code for your development team to maintain and extend.
How do we ensure a visualisation communicates what we intend?
We test communication effectiveness with representative audience members — showing the visualisation to people matching your target audience and assessing whether they correctly understand the intended message, can accurately read specific values, and find the visualisation trustworthy. We iterate based on what we learn. This testing step is particularly important for public-facing visualisations and complex data stories where miscommunication has real consequences.