According to official data, small businesses with fewer than 50 employees are the largest and most potential portion of UK economic activity. Other advanced industrial countries are likely to have a similar proportion. It is also known that such businesses experience a high closure rate after major incidents whether the cause be floods or pandemics.
Community insights and announcements
Read the latest insights and announcements from ICAEW's Data Analytics Community.
As a profession, this is our moment to step up. The health crisis caused by COVID-19 continues, but our economic crisis is only starting to be felt. This is the time when businesses need support and guidance to channel the oxygen of cash and navigate the changes we’re all facing.
How can your organisation balance insight, efficiency and governance? In partnership with Tableau, we hear from Gary Collins, Director of Finance Systems how Carnival UK have revolutionised their commercial analytics, moving away from producing static .pdf outputs to enabling Self Service Analytics for end users.
Europe’s top 1000 non-financial companies have €353 billion in accounts receivable outstanding at any given point in time (Source: FactSet). That amount is roughly the same as Denmark’s GDP! The ability to carefully manage working capital is critical during a crisis like COVID-19, when cash - that most liquid of assets - is king.
By embedding sensors into objects of all kinds, businesses are increasingly able to generate data on almost any aspect of their assets and operations. But what will this huge influx of data mean for accountants?
In this series I am looking at different contextual, editorial, analytical, or design challenges encountered when working on data visualisation tasks. Each will be framed around a specific 'everyday' challenge with five possible methods, ideas or observations presented. Focusing on just five is deliberately arbitrary and non-exhaustive: just enough to provide some different ideas but not enough to pretend to be definitive.
Spreadsheets are good aren’t they, they are familiar, you know what to do with them, everyone uses them, why change?
This article firstly covers how to interpret box plots, before setting out how to understand distribution using violin plots. Finally, it shows how to use the ‘split violin plot’ to reveal a wealth of information about a data set in a single glance.