Data Discovery: What is It, What is Its Purpose, and How Can Tools Help

in #data4 years ago (edited)

A business-user-oriented process, data discovery involves the collection and analysis of data to identify patterns and gain insights. Automation-powered data discovery tools enable automatically cataloging data, managing risks, detecting sensitive data, and compiling data.

What Exactly is Data Discovery?

As discussed, it is a process to find patterns in data. Its significant purpose is to gain insights into collected data, communicate them in user-friendly manner, and ultimately help businesses improve processes.

As a business may have a huge amount of data to process, data discovery tools are used to process various resources and consolidate the collected data into one location. In this way, a business gets a single big picture of all the collected data.

One of the major functions of these tools is that they help create an interactive visual analysis of data, which allows non-technical users to understand data and analyze it to make informed decisions.

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Types of Data Discovery

Data discovery can be done in two ways:

Manual data discovery

Automatic data discovery

As the name suggests, manual data discovery is a type where the collected data is analyzed and processed by experienced humans. Before AI-powered data discovery tools, data specialists manually identified, mapped, and prioritized data.

On the other hand, automatic data discovery is a smart way of collecting, analyzing, and processing the collected data. Using tools, businesses can catalog and map sensitive data. In addition, they can add context to data relationships.

Use of Automation Powered by AI for Data Discovery

Earlier, manual analysis of data was a long, time-consuming process, which also had the risks of errors. However, AI-powered tools for data discovery have changed the way data is collected, analyzed, stored, processed, and communicated to business users.

Mapping Sensitive Data

Using smart tools for data discovery, businesses can have a better insight of data for the industrial ecosystem. They can use the tools to catalog and map data for in-depth analysis and insights. All this happens quickly and with fewer errors than manual mapping.

Easy-to-understand Outcomes

In addition to effectively processing and analyzing data, these smart tools can help generate reports and graphs that even non-technical users can understand and use. These automated reports keep businesses informed about the latest trends in the collected data to make informed decisions.

Data Comparison

Businesses need to identify and find trends in the data to know where changes need to be made. Using data discovery tools, they can correlate the collected data and notice patterns. In addition, they can find links between multiple data points to find out the best ways to make decisions.

In the End

Data Discovery is essential for businesses, especially ones that need to analyze data and use it to make crucial business decisions. Using AI-powered tools, they can automate the processing of data and get user-friendly reports, which further can be useful to compare data and make informed decisions.

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