Introduction

The previous two chapters describe some of the technical aspects to consider when implementing data science in an organization. Merely focusing on the technicalities of analyzing data is, however, not enough to create value for an organization. A data science manager needs to manage people, systems, and process to develop a data-driven organization.

Decision makers sometimes ignore even the most useful and aesthetic visualizations, even when the analysis is sound. Data science using best practices, as described in Chapter 2, Good Data Science, is only the starting point for creating a value-driven organization. A critical aspect of ensuring that managers use the results is to foster a data-driven culture, which requires managing people.

To enable data science to flourish, the organization needs to have a well-established suite of IT systems to store and analyze data and to present the results. A wide range of data science tools is available, each playing a different...