What Is Exploratory Data Analysis?
Exploratory data analysis is like taking stock of your kitchen before cooking a meal—assessing which ingredients you have in your pantry and how they might coincide with each other will determine the recipe you make. In the same way, the key details you discover about your data during exploratory data analysis will guide the direction of your machine learning or analytics projects. Exploratory data analysis summarizes key characteristics of the data, such as number of cases, variables included or missing observations, to develop more informed hypotheses that led to better results.
Exploratory Data Analysis and Data Preparation
There is some debate as to whether exploratory data analysis should be done before you get to slicing, dicing, and chopping (or, in the data world, before you dive into the dirty work of data preparation) or after. More and more, data workers are answering: both. Exploratory data analysis should be viewed as an innately cyclical process. Preparing your data will likely prompt new questions that necessitate more data exploration, and so forth. It’s important to not only adopt new processes that allow you to quickly explore, prepare, and repeat, but also new technologies that aid agility.
Adopting this thinking around exploratory data analysis will also prompt new thinking around who should do this work. Historically, statistical software has been used for exploratory data analysis. While statistics are a skill that many data scientists or analysts have in their back pocket, it’s often doesn’t scale across the organization. And given that the purpose of exploratory data analysis is to uncover key insights that guide downstream analytics projects, those who know the data best need to be involved with exploratory data analysis. They will have the best perspective on the data. Visually-driven tools that allow anyone to both explore and prepare data ensure that the best eyes are always on the data and that everyone in the organization can speak the same language.
Interactive Exploratory Data Analysis with Designer Cloud
Alteryx Designer Cloud’s unique data preparation platform allows for efficient exploratory data analysis. Its interface is easy-to-use, intelligent and interactive, improving users’ ability to understand data immediately. Designer Cloud starts by automatically presents users with the most compelling and appropriate visual representation based on their data. Every profile is customized and completely interactive, allowing the user to simply select certain elements of the profile to prompt transformation suggestions. Finally, users can choose to explore more detailed visual representations which present the data at its most granular level for deeper data exploration analysis. Schedule a Demo for Designer Cloud today to see how it helps with exploratory data analysis.
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