Data Visualisation and Correlation Analysis: A Practical Guide

An exploration of visualisation tools, when not to visualise, and choosing the right correlation method. Author's Note: This article follows APA 7th edition conventions - including in-text citations and a formatted reference list - adapted for a blog format The goal is to bridge academic rigour with practical readability. Introduction Data is everywhere, but insight is not. The gap between raw numbers and meaningful understanding is where data visualisation lives and where correlation analysis helps us quantify relationships we can only guess at by looking at charts alone. This article tackles three questions that anyone working with data will eventually face: Which visualisation tool should I use? When should I skip the chart entirely? And how do I pick the right correlation method for my data? Part 1: The Visualisation Tool Landscape in 2026 The market for data visualisation tools has matured considerably. Current research identifies several leaders, each occupying a distinct niche: