In Kiwi-Random-House/R-Projects: Building Analytic Apps with R

Preface {-}

What is the Motivation Behind this Book? {-}

Books about R tend to focus on data analytics, graphics, statistics, machine learning, programming skills, and data science (whatever that means). The code and examples in these books are divorced from a design of real-world software systems. Understandably, the examples in these books are oversimplified to keep the focal point on the technique.

Very few books talk about the holistic approach for undertaking endeavours in R. In particular, two books discuss standard ways to build and deploy applications in R:

1. R packages [@Wickham2015], provides a framework for building R packages; and
2. Engineering Production-Grade Shiny Apps [@Fay2020], provides a framework and a methodology for building robust Shiny applications.

There is, however, a topic that neither of these books covers - building analytic applications. This book aims to fill this gap.

Who Should Read this Book? {-}

Every data science project has at least a project lead and a data scientist. Sometimes they are the same person. In any case, the first task facing the project lead is creating a template repository [@Microsoft2017]. Most practitioners use a former project, which is by itself a reincarnation of a former project, as the template repository. Regardless of what template repository is employed, its mechanics have to be communicated and thought with collaborators and your future self. Having a framework that is well documented and generalises well to a wide range of analytic applications means reducing everyone's cognitive effort and time spent teaching and learning different templates.

The core audience of this book is data science project lead who is seeking to adopt a framework for building analytic applications in R.

The book also aims to lighten the education of the project lead and team members by concentrating attention on a few essential analytic application components, the R startup process, and procedures of reproducibility. The numbers of the sections may be used as references in code review and induction of team members.

Kiwi-Random-House/R-Projects documentation built on Dec. 31, 2020, 2:10 p.m.