Cecil Garapo Jr

The Challenge

Designing simple clear data visualisations, when using big data such as in-app dashboards and web pages. If you want to ensure that an analytical solution is widely accepted, you’ll need to put a lot of effort into designing the user interface (UI) and ensuring that it gives the greatest possible user experience (UX). Your end users should have a pleasant experience, allowing them to interact with data in ways that are natural to them.

Steps to Achieving this

Through intuitive User Research done extensively we can arrive at the following

1. Clearly Defining User Needs

Users should be able to grasp what data (and in what amounts) they want or need to see, therefore research should be aimed in that direction. A common mistake is displaying enormous quantities of data through graphs and charts, this is an innocent mistake at times by developers and designers as they are caught up in trying to demonstrate the depth of analytical capability the solution provides.

I’VE BEEN GUILTY OF THE ABOVE 😔

2. Design for Different Access Levels

Example of access level design

Level 1: Non Technical users

They may have the dumbed down easy to comprehend dashboard visualisations

Level 2: Management

Are more likely to use table selections and menu-based reports

Level 3: Data Scientists 

They are most likely to utilise a combination of menus, keyboard commands and advanced visualisations in order to get key insights

In Conclusion

Big data visualisations will always be an increasingly challenging area as more and more of it flows in, simplicity is required to make sure its interpreted by all stakeholders in ways they find best to consume it. The most important consideration when looking to build or buy a big data platform for your organisation is excellent user experience as it translates directly to the usage results

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