Let's imagine that you have several terabytes of data. Unfortunately, it is raw unstructured data. In order to get business insight from this data you have to spend a lot of time in order to prepare and clean the data. In addition, you are restricted by the capabilities of your machine. That's why a good data discovery tool usually is combined of software and hardware. As a result, this gives you more power for exploratory data analysis.
Let's imagine that this entire big data store is in Hadoop or any NoSQL data store. You have to at least be at good programmer in order to do analytics on this data. Here we can find other benefit of a good data discovery tool: it gives a powerful tool to business users, who are not as technical and maybe don't even know SQL.
Tip
Apache Hadoop is an open source software project that enables distributed processing of large data sets across clusters of commodity servers. It is designed to scale up from a single server to thousands of machines, with a very high degree of fault tolerance. Rather than relying on high-end hardware, the resilience of these clusters comes from the software's ability to detect and handle failures at the application layer.
A NoSQL data store is a next generation database, mostly addressing some of the following points: non-relational, distributed, open-source, and horizontally scalable.