The goal of data analytics is to find patterns within the information you capture and store. Patterns indicate correlations, predict trends, reveal anomalies and highlight outliers. Cumulatively, these resemble firm evidence that informs better decision-making and lowers risk. Here’s the good news: humans are fantastic pattern-recognisers. We’ve evolved and survived by recognising and interpreting patterns in 3D space for millennia. It’s the way we process information best, and that’s why we’ve built illumr to take advantage of this.
Introduction to illumr:
what do we do?
Our 2 minute animation is the fastest way to find out how illumr works and what it can do for you.
A four year old can instantly recognise a flock of birds but only the world’s most advanced pattern-recognition technologies come anywhere close to this – inconsistently and at great expense
How does Augmented Cognition work?
Augmented Cognition capitalises on our innate capacity to recognise patterns and combines it with the computational requirements to do it at massive scale.
It works by rendering the data points (and the rules that govern them) as self-organising 3D models. This presents the user with a physical space to navigate, interact with and amend in real time.
You don’t need a hypothesis to start exploring your data. You can just dive in and start evaluating, experimenting and improving straight away.
Why analyse rules?
Rules reveal the hidden relationships between the different nodes and values in a data set. They help to identify correlations, causalities, outliers and anomalies between different factors, events and transactions that might otherwise be impossible to see.
Historically, data analysis has been about just that: analysing the data to produce rules that accurately describe it. But there are some serious flaws in the methodologies and tools used to generate those rules.
Previously, creating a rule was a matter of educated guesswork. Data scientists would select a subset of data they wanted to explore and run queries against it to identify a rule that analysed the data in question accurately. In other words, it asked the analyst to hypothesise first, and then put the burden to disprove it on them.
illumr’s 3D visualisation enables users to fundamentally change the way they create rules – beginning with unbiased observation instead of subjective estimation – in order to improve the accuracy, quality and efficiency of both new and existing rules.
Who can use illumr?
In short, everyone. Data analytics is often overwhelming to non-technical users because the tools (and subject matter) typically require specialised knowledge to comprehend.
illumr changes that. You don’t need a PhD to use illumr. You just need to see patterns.
We’ve combined the depth of functionality needed for thorough, academic study of complex data with a simple and intuitive interface. The result is a tool that supports transparent dialogue between specialised data analysts and non-technical executives and managers.
This bridges the gap between locating patterns, deriving valuable insight from them, and turning them into actionable business decisions and behaviours.
Once the relationship between initial investment and business outcomes becomes more clearly defined, it’s easier to get new data analytics projects off the ground. We’ve had great success in using illumr to reveal new insights into older data sets that customers thought they fully understand.