Data analysis is a process, not a single task. It begins with raw information that needs to be hewn into a digestible form. Exploratory data analysis is a preliminary task that analysts perform before they’ve identified patterns.
What is Exploratory Data Analysis?
Analysts such as https://shepper.com/ spend the early stages of their work investigating patterns and identifying anomalies. As they explore, they’ll also look for errors or outlying data points. This ensures that their outcomes aren’t pushed out of shape by unusual occurrences that don’t form a part of the usual trends.
Types of Exploratory Data Analysis
A data analysis company will use three broad methods of analysis to gain an understanding of the variables. Univariate analysis zooms in on the traits of a single variable. Bivariate analysis focuses on the relationship between two variables. This kind of analysis intends to find connections and correlations. Multivariate analysis identifies connections between more than two variables in a set of data. This helps analysts find the interactions that inform statistical modelling.
Steps of Exploratory Data Analysis
Exploratory analysis occurs in stages. The first step involves defining the problem and characterising the initial data. Once that’s done, the data can be loaded into an analysis environment and inspected. Finally, analysts explore the characteristics of their data and process visualisations, often with the help of automation.
Exploratory data analysis is crucial for determining the accuracy of the analytics that follow. It plays a key role in deciding which modelling techniques are best and how data needs to be adjusted.
