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February 23, 2018

The Top 10 Charts You’ve Never Heard Of

What do the words ‘Lollipop, ‘Dribble’, ‘Galileo’ and ‘Sperm’ all have in common?

By James Nunns

What do the words ‘Lollipop, ‘Dribble’, ‘Galileo’ and ‘Sperm’ all have in common? Behave! They are in fact all types of interactive charts that are growing in popularity in the brave new world of visual analytics.

We have been using pictures to understand data for centuries, delving deep into the histories of the earliest map-making and visual depiction dating back to 2300 B.C. An increase in statistical thinking and widespread data collection in the 19th century saw the invention of line and pie charts, as well as more complex statistical graphs. This vast history is proof that it works and, as the human race has progressed, so too has our curiosity. We are constantly searching for new ways to understand the ever-increasing amount of data before us.

The ‘Sperm’ Chart

It would not be possible to be where we are today in the world of visual analytics without the advancement of technology. Computers enable us to process large amounts of data at incredible speeds. Businesses are revolutionising as they learn the potential data has in facilitating business decisions, optimising efficiency and in turn, increasing profits.

Data locked in thousands of rows inside a spreadsheet is useless without the right tools to explore and understand it. However, as can be seen from the examples shown, each graph tells a different story in its own unique way. Choosing the right graph for the data set is crucial in ensuring total comprehension and avoiding mistaken data interpretation. This is the difference between data as a help and data as a hindrance. This means going further than just having a solid grasp of the data.

Crucially this isn’t as simple as just beginning with data and deciding the chart to build. The right chart can only be found by rapidly iterating through many views, manipulating the data and honing in on the best articulation of the insights it contains.

Employees need to understand its qualities such as size and cardinality, and what it is that needs to be visualised. The question to ask when visualising the data is ‘what kind of information do you want to communicate to your audience?’ Knowing your audience and understanding how they process visual information is a good indicator towards which visual asset will convey your information in the best and simplest form possible.

The ‘Galileo’ Chart

Every employee within a company benefits from visual analytics if used correctly. Take meetings for example. It can be difficult to follow what a co-worker is saying when faced with a text and data heavy presentation. By having a clear, easy to understand visualisation that lays out all the key points in an engaging way, team members are able to see the goal and how they plan to get there. Visualising data ultimately enables teams to ask and answer questions during a meeting in real-time, accelerating decision-making and boosting productivity.

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The power to unlock data lies in the C-suite’s ability to instil a data-driven culture. Give an employee a computer, and they will do the work that is asked of them. Give an employee access to their own data as well as the technology tools to be able to explore it, and they will be empowered and inquisitive beyond their original work scope. This starts with training and upskilling, like building up critical thinking and analytical curiosity. Every member of an organisation should go through appropriate training in

The ‘Comet’ Chart

order to match the company expectations and align with a data-literate workforce.

The leadership team is crucial as an organisation transitions into this data-heavy landscape. Many employees who have not studied STEM subjects at school may shy away from tasks that require them to use or understand data. The only way to foster a data culture that results in efficiencies and profits for the company in question is to ensure that there are steps to make it feel like the norm for everyone. A good place to start is for senior figures to begin demanding data-driven answers, which flows down the chain into each respective team. Ensuring data literacy is a part of all conversations is crucial; otherwise, the whole transition will be long-winded and confusing.

Although the lollipop and sperm graphs seem flippant and irrelevant in a boardroom, they highlight how much can be done when an employee is empowered to ask questions of their data. Exploring different thought-paths with visual analytics spawns new and energised business thinking.


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