Why visualising your data correctly is so important when looking for actionable business intelligence
DoubleCloud talks a lot about our Managed Services for ClickHouse® and Apache Kafka® but what we wanted to talk to you about today was how important visualising your data is to garner actionable business intelligence and… of course… our free visualization tool.
We offer our users a wide variety of different data visualisation options to help look for meaning in their data and, given the large amounts of it they often have to deal with, portraying it both correctly and in a useful fashion, is vital, if not business critical.
If a user can’t tell at a glance what their data’s saying then are they, in fact, any better off than looking at it in its raw form?
Accurate and efficient data visualisations have to be considered the core to any modern data stack and analytics platform.
Now, what’s interesting is that the guiding principles to ‘good’ data visualization haven’t really changed at all in the last few decades. What has changed however is the tech powering them, the amount of data that can help form them and the ease in which said data can be displayed in a multitude of different ways.
The problem with so many different options however is that sometimes your data may be displayed in a way that’s not quite right, or certainly not the best or most efficient way it can be displayed.
Display it ‘wrong’ and the resulting chart may actually end up misleading your end users.
That’s why today, we’re talking through our free data visualization tool, what the best ways to display differing data sets are and how to select the right data visualization for the right task.
Line Charts had to be first, didn’t they?
They’re one of the easiest to read, most instantly recognisable, and probably one of the simplest data visualization representations to put together (at least manually).
Data trends can be identified at a glance (up or down) measured against another metric (usually time), with different subsets of data being represented by differing coloured lines.
Data is typically displayed over two axes with them at their most effective when displaying data over a time period be it, seasonality or a ratio of multiple measures at a single point in time.
However, this simplification of data trends can sometimes be a line charts downfall, as complicated, underlying trends will often be missed at this level.