The Basics of Data Discovery
Data discovery starts with a sloppy crowd of data coming from multiple directions in a mess of forms. And yet, the process creates digestible information and ends with applicable insights. How does it happen? Data discovery compiles data from multiple sources, and then configures the data so it can be understood and examined. The steps in data discovery can be broken down a few different ways, but they all include (1) data preparation, (2) data visualization and (3) data analysis.
Using Data Discovery to Visually Explore and Understand Diverse Data
When working with complicated data, data discovery is a critical step in the data preparation process. Completing data discovery step allows you to gain some initial understanding as to what is actually in the dataset and how it can be leveraged for analytics and valuable business insights.
The process of data discovery can be difficult when working with various datasets that are not well structured to begin with or that are too large to use with common tools such as excel. For an analyst working with a new or third-party dataset, the faster they’re able to perform the process of data discovery, the faster they’re able to show value from their work.
The Benefits of Using Trifacta for Data Discovery
Learn more about how Trifacta accelerates data discovery
To learn more about how Trifacta accelerates data discovery and how it ties into the broader data wrangling process, we invite you to download our free ebook Six Core Data Wrangling Activities: An introductory guide to data wrangling with Trifacta.DOWNLOAD EBOOK