Data discovery requires you to undergo a five-step process. Smart data discovery is also iterative, which allows your company or organization to continue collecting, analyzing, and developing your data discovery approach over time, based on their results and feedback from various enterprise stakeholders. Implement smart data discovery into your business and transform the way you use data and gather insights.
The first step in data discovery requires you to begin with a clear purpose, such as seeking the resolution of an ongoing issue, identifying market opportunities, understanding customers, and addressing other business objectives. This requires you to explore and consider what kinds of data should be identified, while also remaining open to contingent insights from the analysis. Some businesses do manual data discovery, but there are a
variety of software and tools available that can help in the discovery process. This is followed by combining data from relevant sources such as survey data, cloud applications, site information, and user databases.
Effective data discovery requires you to integrate data from various sources because single data streams seldom tell the entire story. This process is often referred to as data crunching.
The third step of advanced data discovery involves cleaning and organizing the data to prepare it for analysis. This allows you to eliminate noisy data to achieve a clearer direction from your data analyses. The fourth and perhaps the most crucial step in smart data discovery is analyzing the data. By using the information combined from multiple sources, integrated with external data and prepped for analysis, you are given a complete perspective of your business operations and the ability to solve the hurdles that are detrimental to the success of your enterprise.
Lastly, you will need to relay the insights you've arrived at to your organization. This can be done through visual presentations like charts and maps. Effective data visualization is key when presenting information to management and top business executives who have a financial interest in the organization.
Read more: How to start a successful privacy data mapping project 
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