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Deployment guide

Some tips to help you move from prototype to production

Data modeling

When you’re kicking off a new visualization project, you’ll probably want to start coding right away. After all, you’re eager to see nodes in your charts and events in your timelines.

But we’ve found that teams who take time to plan their data and visual models are more likely to succeed than those who try to figure it out later on.

This is especially true when moving from prototype to production. You’re probably visualizing different data and will have some new, very important stakeholders: end-users. They’ll thank you for taking the time to create a clear, simple, and insightful model from the outset.

The ultimate guide to graph data modeling

How do you transform flat, tabular data into an intuitive graph model that will work for all your users? What becomes a node, a link, or an attribute?

This guide will help you decide.

Building the visual data model

Once you’ve got your data model down, you need to think about the visual model. It rarely makes sense to draw every node and link in the database.

There are some simple best practices.

The ultimate guide to timeline data modeling

Many graph best practices apply to timelines, too, but there are some differences.

This blog post shows an example of creating a visual and data model for a timeline visualization.

Data visualization at scale

When you’re planning a data visualization, it’s tempting to put all your data in at once, and assume your users will find the answers they need. This rarely works.

Most people can store between 4 and 7 items in their short-term memory, so you’ll need to bring your data down to a more human-friendly scale.

There are plenty of straightforward strategies and techniques to help you do this. Many of them are useful analysis techniques in their own right, so users will discover new and unexpected insights along the way.

Five steps to tackle big graph data visualization

How do you turn millions (or billions) of nodes into something your users will understand?

The data funnel, combined with KeyLines’ and ReGraph’s functionality, makes it simple.

Visualizing a Twitter troll dataset in KronoGraph

KronoGraph handles huge datasets, but there are tools to make the experience even better.

See how you can give users a clear, simple and rewarding experience.

Exploring our toolkits’ performance

This article looks specifically at how to maximize the performance of a ReGraph component, but it also applies to KeyLines projects.

Common first-time problems

It makes every graph pro’s heart sink: you’ve created a great visualization application, designed a bullet-proof data model and visual model, and you’re ready to see your data for the first time. But you click ‘load’ and… it’s a mess.

Hairballs, snowstorms and starbursts. They’re a problem for many graph visualization projects, obscuring data and preventing users from finding the insight they need. But we have solutions – click on the images below to learn more.

The hairball effect

The snowstorm effect

The starburst effect

UI and UX

The best data in the world is useless if your users can’t access it. A carefully designed, intuitive user experience (UX) makes all the difference.

You need to think about the user experience on two levels: with the visualization, and with the wider application.

Designing intuitive data experiences

With the right approach to graph visualization UX and UI, even the most complex visualizations can become intuitive tools for discovery – not frustration.

Let’s explore how thoughtful design transforms graph visualizations from overwhelming to empowering.

Building accessible applications

Nearly 15% of people have a disability that could impact their ability to use software. Accessibility is essential.

Help your team design graph UIs that are more usable, inclusive, and effective from the start – not added as an afterthought.

4 easy styling options

As SDKs, our graph visualization products let you build the UX that makes the most sense for your users.

This article shares 4 smart and simple styling options that take full advantage of that flexibility.

 

Choosing data visualization colors

Familiar with pre-attentive processing? It’s how the brain instinctively accumulates and interprets certain cues. You can use it to make visualizations that feel so intuitive, the user instantly understands what’s going on.

 

Get inspired

Any guide to using our products can only really scratch the surface. The advantage of an SDK is the flexibility it gives to create applications that are 100% customized to your users, their data and the questions they need to answer.

With that in mind, here are some other places you can find more information.

Find some inspiration

We work with almost 300 organizations worldwide, who use our technology in countless ways – from stopping cyber attacks to detecting fraud.

Some of them have kindly agreed to share their work through case studies. Take a look behind the scenes and get inspiration from other teams who are facing similar challenges to you.

Team of colleagues from Cambridge Intelligence discussing new data visualization techniques and tools

Join our online conversations

Connected Insights is our series of free online conversations and training to help you make the most of your investment in data visualization. Our regular sessions are a great way to connect with peers and discuss your projects and experiences with our team, either face-to-face or virtually.

Look out for our email invitations, or visit the events page for more information.

Two employees discussing risk and compliance related concerns

Check out the SDKs, or ask for support

You’ll find a wealth of resources on each of our products’ SDK sites.

They include ‘getting started’ tutorials, copyable demos, full API documentation and articles explaining common problems or answering frequently asked questions.

If there’s something you can’t find, our dedicated support team is always on hand.