The Importance of Granularity (…to Blend or not to Blend?)

The ‘Granularity’ (or ‘Grain’) of the data is the most important thing I consider for any data analysis. When I get a new data-set, my first question What is the Granularity? When designing a new (Tableau) visual model, my first consideration What Granularity do I need? When calculating a measure (or KPI), my first questions: What is the Granularity? and What Granularity do I need?

I’d go as far as saying “Understanding the Grain of your data is 99% of the solution”…

Managing by Averages… of Averages

Much of my visual analysis is performed to help large companies – usually retailers and their suppliers – to better understand a perplexing problem or opportunity in their organisation. How can we reduce waste in our stores? Which promotions drive the desired behaviour in customers and why? What effect does non-delivery at depot have on availability in store? What’s the optimum product range for our biscuits category? etc.

Sheet Swapping using Dashboard Actions (or the Illusion of a Full Outer Join on Blended Data)

As the title suggests, this nifty trick has the dual purpose of allowing you to trigger sheet swaps using Dashboard Actions and, when two data sources contain different levels of Granularity, it lets you analyse at both levels (the Granularity of the Primary and Secondary data source). This is the ‘illusion of a Full Outer Join’…All seems a little cryptic and techie. Let’s run through an example…

Why Data Animators?

Data is often perceived as dry, remote, and impersonal – even when it relates to customers, citizens, or friends and family. In the information age, an ever-growing stream of data is stored as digital bits in shapeless clouds of computer storage, processed by a million algorithms which divine our preferences for movies, holidays, and foodstuffs. It’s easy to feel that data has no direct relevance to any one of us and yet…