Data discovery: What is it and why is it important?

In the current era, often referred to as the Golden Age of data, businesses have access to a vast array of data sources, which, when effectively analyzed through data discovery processes, can provide crucial insights for strategic decision-making. Data discovery involves extracting meaningful patterns by combining and analyzing data from various sources, a process that has been significantly enhanced by advancements in artificial intelligence and machine learning. This iterative process includes steps such as identifying goals, collating data sources, cleaning the data, visualizing, and analyzing it to reveal actionable insights, which help businesses become more agile and cost-effective. The importance of data discovery has grown with the increase in data generated by remote working and digital interactions, emphasizing the need for smart, automated solutions like those provided by behavioral data analytics tools such as Snowplow. These tools enable businesses to leverage complex behavioral data, traditionally seen as challenging, to gain deeper insights and personalize customer experiences, similar to the approaches used by leading tech companies like Airbnb and Spotify.