What is Data Exploration?

Data exploration is like searching for oil—figuring out where to drill is a combination of art and science, and making the right choices can bring in a gusher. In both cases, exploration is about searching for something when you don’t know where it is. Data exploration is one of the initial steps in the analysis process and is used to begin exploring and determining what patterns and trends are found in the dataset. An analyst will usually begin data exploration by using data visualization techniques and other tools to describe the characteristics of a dataset. At this point, analysts aren’t sure what they are looking for in the dataset because it’s so early in the process. But using the right data exploration tools and techniques can bring forth a wealth of information and eventually insights. Using the best tools for data exploration enables analysts, IT professionals and business executives to draw substantive insights and quickly identify which data to analyze further.

Let’s take a more in-depth look at data exploration, why it’s important, and how Alteryx can help business users, data analysts and technical users do data exploration faster and more efficiently than ever before.

Why Data Exploration?

Before deeper analysis can be done, you must summarize the characteristics of a dataset: number of cases, variables included, missing observations or values, and any prospective hypotheses the data might support. These characteristics of a dataset are the basis on which further analysis can be made. It’s impossible to find valuable insights if analysts don’t know what the dataset has inside. So while it could save some time to skip the process, it does provide valuable information that can affect the remainder of the analysis process. 

When reviewing the data, the analyst hopes to immediately zero in on variables that will lead to valuable insights about their business. If several data points correlate, those may be great candidates for in-depth analysis. By skipping this first exploratory step, the analyst won’t immediately understand the key issues or won’t be able to guide the deeper analysis in the right direction. Later on in the analysis process, analysts may struggle to find the key insights because they didn’t spend time on initially exploring the information in the dataset. This process can guide and refine analysis for more productive results.

Data Exploration: Using Visual Tools

Historically, analysts have used statistical software for data exploration, but now most use data visualization software and tools. Visualizing data through the use of dashboards, graphs and charts, analysts are better able to quickly discover the most relevant aspects of their datasets. Time can be a crucial factor in data analysis, and using these visualization tools can help accelerate the process.

The best tools don’t just help visualize data, they interact with their analyst as they perform data exploration. Instead of just spitting out limited data exploration reports, the best data exploration tools now interact with the analyst and their team, allowing everyone to collaboratively annotate and search datasets, make recommendations for visualizations, and even automate the exploration process through machine-learning. Using these innovative and visual tools saves organizations valuable time and money while allowing them to get the best data exploration results.

Interactive Exploration with Designer Cloud

Designer Cloud’s unique data wrangling software was designed with data exploration in mind. Designer Cloud offers easy-to-use, intelligent and interactive visual analysis that improves the users ability to understand data immediately. Designer Cloud automatically presents the user with the most compelling and appropriate visual representation based on their data for example, geographic elements are presented as maps. Every profile is customized and completely interactive – allowing the user to simply select certain elements of the profile to prompt transformation suggestions. Using Designer Cloud, analysts are able to quickly identify the characteristics of a dataset and use those to guide the process of deeper analysis. Designer Cloud combines the science and the art of data exploration and analysis.

Experience our innovated approach to data wrangling for yourself. Try out the 30 day free trial of Designer Cloud.

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