This chapter focuses specifically on the analytics concepts that will enable an organization to make analytics operational. As we discuss, not everything in the world of operational analytics is new, but there are some new and unique challenges that must be understood and accounted for.
Do not forget that making analytics operational is an evolution, which means that all the lessons and guidelines from the past related to how to build analytics processes still apply, but with a few new twists. Organizations that are already good at building and leveraging analytics and that already have a solid team of analytics professionals on staff are positioned to succeed.
Creating Operational Analytics Processes
We defined operational analytics in Chapter 1. Let's start here with a few topics surrounding the creation and deployment of operational analytics. It will become apparent that operational analytics have a lot in common with traditional batch analytics, and it isn't necessary to start from scratch. At the same time, as also discussed in Chapter 1, organizations can't leapfrog into operational analytics without first gaining competency in traditional batch analytics.
Consistency of the Analytics Process
As big data has emerged and people with different backgrounds enter the world of analytics, there are debates about whether a new analytics workflow is required. The answer is no. At a fundamental level, the workflow for developing analytics is very consistent ...