SAS Data Analytic Development

Preface

Because SAS practitioners are software developers, too!

Within the body of SAS literature, an overwhelming focus on data quality eclipses software quality. Whether discussed in books, white papers, technical documentation, or even posted job descriptions, nearly all references to quality in relationship to SAS describe the quality of data or data products.

The focus on data quality and diversion from traditional software development priorities is not without reason. Data analytic development is software development but ultimate business value is delivered not through software products but rather through subsequent, derivative data products. In aligning quality only with data, however, data analytic development environments can place an overwhelming focus on software functional requirements to the detriment or exclusion of software performance requirements. When SAS literature does describe performance best practices, it typically demonstrates only how to make SAS software faster or more efficient while omitting other dimensions of software quality.

However, what about software reliability, scalability, security, maintainability, or modularity—or the host of other software quality characteristics? For all the SAS practitioners of the world—including developers, biostatisticians, econometricians, researchers, students, project managers, market analysts, data scientists, and others—this text demonstrates a model for software quality promulgated by the International Organization ...