What is data exploration?
Data exploration is the first step of data analysis used to explore and visualize data to uncover insights from the start or identify areas or patterns to dig into more. Using interactive dashboards and point-and-click data exploration, users can better understand the bigger picture and get to insights faster.
Why is data exploration important?
Starting with data exploration helps users to make better decisions on where to dig deeper into the data and to take a broad understanding of the business when asking more detailed questions later. With a user-friendly interface, anyone across an organization can familiarize themselves with the data, discover patterns, and generate thoughtful questions that may spur on deeper, valuable analysis.
Data exploration and visual analytics tools build understanding, empowering users to explore data in any visualization. This approach speeds up time to answers and deepens users’ understanding by covering more ground in less time. Data exploration is important for this reason because it democratizes access to data and provides governed self-service analytics. Furthermore, businesses can accelerate data exploration by provisioning and delivering data through visual data marts that are easy to explore and use.
What are the main use cases for data exploration?
Data exploration can help businesses explore large amounts of data quickly to better understand next steps in terms of further analysis. This gives the business a more manageable starting point and a way to target areas of interest. In most cases, data exploration involves using data visualizations to examine the data at a high level. By taking this high-level approach, businesses can determine which data is most important and which may distort the analysis and therefore should be removed. Data exploration can also be helpful in decreasing time spent on less valuable analysis by selecting the right path forward from the start.