Preattentive processing occurs without our consciousness at an extremely high speed. It is tuned to detect a specific set of visual attributes called Preattentive Attributes. If you want to understand more about how we process a visual, please refer to this post on Visual Perception. Preattentive attributes determine what information catches our attention. This is important in…
Data is the backbone of business decisions, research and scientific discoveries. But not all data is made equal. Understanding data types and measurement scales is essential for collecting, analysing and interpreting data correctly. Each type of data carries unique properties that dictate what analyses are valid, how results can be visualised and what conclusions can…
One of the trickiest parts of working with time series data? Incomplete periods. Imagine tracking yearly revenue, quarterly sales, monthly website traffic, or weekly customer sign-ups, and the latest period isn’t finished yet. If you simply plot the data as is, the incomplete period can look like a sudden drop, misleading stakeholders and causing a lot of panic. If you omit the current data, you are missing valuable early signals and not showing the complete picture.
Don’t let your message be lost amongst mountains of text. In most organizations, powerpoint has become the de facto presentation tool. When asked to run a meeting, we instantly open powerpoint to create a presentation. This may come as a surprise, but how often do we pause and ask the question – Is powerpoint the…
The problem with using so many colors in a chart is it introduces a sense of complexity. People perceive more aesthetic designs as easier to use. They tend to be more engaged with a chart if it appears pretty.
A waterfall chart is used to show how an initial value is increased and/or decreased by a series of intermediate values, leading to a final value.
A cycle plot shows both days of the week/month of the year effect and trend/cycle in data. Cycle plots were created by Willian Cleveland and his colleagues in 1978 at Bell Labs.
For this week, I created a quick makeover using Datawrapper. My aim was to allow easy comparison between the 10 waste sources. I chose to use the trusted old bar chart.