The Covid-19 pandemic has forced many managed service providers to seek faster, easier and more scalable ways to manage their customers’ data.Continue reading
Your data, your company’s most valuable asset. Applications use data to run but more importantly, it is the data they generate that gets used by businesses to do the analyses required to understand their customers, their competitors, their way forward. Being able to visualise this data effectively is an intuitive way of getting this value out of it. But it goes beyond spreadsheets, bar charts and infographics.
More elaborate analysis is a function of ever-growing data volumes. Unfortunately, after data has been analysed and visualised, of the live version as it were, it gets decommissioned to be preserved. And more often than not, once it’s served its primary purpose, this preservation results in archiving and the data is forgotten about.
In recent years, companies have been rediscovering the value of so-called “stale” data – they have started getting rid of the ROT (Redundant, Obsolete, and Trivial). As part of the overall Data Management life cycle, re-using data becomes prudent. As new forms of data visualisation are being explored, the data’s original value is exceeded.
Understanding business indicators remains at the heart of BI. That’s why billions of dollars are spent annually on developing and getting the best software the market has to offer. But one has to ensure that the data is available to be analysed. This is where data backups become integral to the use of historical data in business projections. If data backups are kept religiously (the appropriate software and with sufficient RPOs in place), it ends up being a huge encyclopaedia of your business history and can be mined for the nuggets of understanding it contains.
The world of 3D data visualisation is vast, as vast as the subject matters it aims to represent: social sciences such as social networking; natural sciences such as astronomy and biology; or even 3D modelling, such as molecular structures and architectural plans.
It seems that a 3D representation of quantitative messages isn’t so much about its accuracy as it is about allowing the viewer to transition from the first two dimensions, side and top views, into a third. This is where techniques such as 3D Scatter Plots and Network Analyses become immensely useful. The former plots data points on a three-dimensional space in order to find correlations between them. The latter assists the viewer in identifying clusters and thereby allowing them to deduce the most influential nodes.
As part of this revolution in understanding large data sets, innovative methods are being devised. Take for instance Cascade, developed by the R&D group at the New York Times. It tracks the inception of news-worthy posts, and shows you how they get spread through social media.
The field of astronomy is equally studious, being littered with all manner of representations of the Universe – and probably also one of the biggest generators of data on Earth. There again, the value of the data lies in the interpretation thereof – its visualisation is key.
Have a look at the Periodic Table of Visualisation Methods to see which visuals your company could benefit from. Assess if you already have the data or if perhaps it is time to start building a suitable repository that could provide some benefit later.
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