Analytics for the Internet of Things (IoT)

Summary

In this chapter, we reviewed how to increase data scientist productivity by reducing time spent manipulating data. The concept of LAD was introduced, along with a process to build them.

Concepts to help prevent data lakes from turning into a data swamp was discussed. Changing perspectives from a data lake to a series of active refineries and production chains helps to plan for a useful data storage area.

Strategies for data retention were also reviewed. Consider the twin goals of maximizing value while minimizing costs when designing a retention strategy. In the next chapter, we will discuss the economics of IoT analytics. The chapter covers ways to look for business value in the data along with a detailed predictive maintenance example. ...