What is small data? Well, let’s begin by understanding a little bit about big data. Other than sometimes significant differences in the type and volume of data used; one of the major differences between the use of big and small data solutions is the way that analytics are approached to solve problems. In the case of both big and small data analytics solutions, the goal is to turn data into information that can be used to guide decisions. However, with big data, the working pool of data is virtually infinitely large. Typically, the idea is to cast your analytical net far and wide into this vast, complex pool of data and wait for the insights to reveal themselves. This type of analytic approach naturally lends itself to discovery of new ideas and new connections that can lead to the coveted land of business innovation. However, because most organizations are not equipped with the technological resources or the team of skilled data scientists, engineers and analysts required, substantial upfront and, often, prolonged financial investment can result.