Chapter 1. Introducing Agile Analytics

Like Agile software development, Agile Analytics is established on a set of core values and guiding principles. It is not a rigid or prescriptive methodology; rather it is a style of building a data warehouse, data marts, business intelligence applications, and analytics applications that focuses on the early and continuous delivery of business value throughout the development lifecycle. In practice, Agile Analytics consists of a set of highly disciplined practices and techniques, some of which may be tailored to fit the unique data warehouse/business intelligence (DW/BI) project demands found in your organization.

Agile Analytics includes practices for project planning, management, and monitoring; for effective collaboration with your business customers and management stakeholders; and for ensuring technical excellence by the delivery team. This chapter outlines the tenets of Agile Analytics and establishes the foundational principles behind each of the practices and techniques that are introduced in the successive chapters in this book.

Agile is a reserved word when used to describe a development style. It means something very specific. Unfortunately, “agile” occasionally gets misused as a moniker for processes that are ad hoc, slipshod, and lacking in discipline. Agile relies on discipline and rigor; however, it is not a heavyweight or highly ceremonious process despite the attempts of some methodologists to codify it with those trappings. Rather, Agile falls somewhere in the middle between just enough structure and just enough flexibility. It has been said that Agile is simple but not easy, describing the fact that it is built on a simple set of sensible values and principles but requires a high degree of discipline and rigor to properly execute. It is important to accurately understand the minimum set of characteristics that differentiate a true Agile process from those that are too unstructured or too rigid. This chapter is intended to leave you with a clear understanding of those characteristics as well as the underlying values and principles of Agile Analytics. These are derived directly from the tried and proven foundations established by the Agile software community and are adapted to the nuances of data warehousing and business intelligence development.