data visualization

In many ways the planning system has done a good job: trying to balance competing demands for scarce resources and mediating between economic forces and the views of local communities. And, over the years, it has proved remarkably resilient.
What these films and shows don't highlight is the amount of data analysis that would need to go on in the background in real life. Let's take Containment to start with: how would they know how much of the city to cordon off?
Climate change happens on such a big scale and over such long time periods it is hard to comprehend at human scale. But we can already see its impact in extreme weather events that are becoming more common.
Not hugely useful. With 17 series, the colours are difficult to distinguish; if we tried labelling every line, it would also
In the world of business intelligence and visualisation, it has never been truer that a picture is worth a thousand words. When used properly, rather than just being an aesthetic adaptation, expressing quantitative data visually can provide a valuable method of extracting meaning and therefore critical business insights from data sets.
For many years, data visualisations have been transforming the way people see and understand data. Looking back at the history of data visualisation helps us in our work today.
One of the many pieces of feedback you often hear from business intelligence (BI) users is that prior to using BI, they felt they were doing fine. The perception was that BI tools were an unnecessary luxury, too complicated to implement and use without hiring specialist staff. New staff hires, which just couldn't be justified based on the minimal perceived benefits BI would bring.
There's a reason why 'Where's Wally' is so effective and enduringly popular. The human brain is evolved to use colour, shapes and patterns as catalysts for cognitive recognition. These originally enabled us to spot threats in the environment; now they enable us to spot trends and sequences in charts more easily.
As we all know, a lot of today's businesses have extensive data on us as consumers. Be it our favourite social network, the local supermarket or the bank. But not a lot of that insight is ever used to its full potential, either for the business, or the consumer.
If there's one thing that working with data teaches you, it's to expect the unexpected. After all, it's easy to look at data sets and extrapolate the obvious conclusions that stand out from the most glaring statistics. But what if the real value of the data was to be found elsewhere?