Book Image

Principles of Strategic Data Science

By : Peter Prevos
Book Image

Principles of Strategic Data Science

By: Peter Prevos

Overview of this book

Mathematics and computer science form an integral part of data science, and understanding them is crucial for efficiently managing data. This book is designed to take you through the entire data science pipeline and help you join the dots between mathematics, programming, and business analysis. You’ll start by learning what data science is and how organizations can use it to revolutionize the way they use their data. The book then covers the criteria for the soundness of data products and demonstrates how to effectively visualize information. As you progress, you’ll discover the strategic aspects of data science by exploring the five-phase framework that enables you to enhance the value you extract from data. Toward the concluding chapters, you’ll understand the role of a data science manager in helping an organization take the data-driven approach. By the end of this book, you’ll have a good understanding of data science and how it can enable you to extract value from your data.
Table of Contents (6 chapters)

Process

Chapter 2, Good Data Science, mentioned the requirement for governance in data science to ensure the outcomes of projects are sound. The process of creating value from data follows an iterative workflow that works from raw data to a finished project. (Wickham, H., & Grolemund, G. (2016). R for data science: Import, Tidy, Transform, Visualize, and Model Data Sebastopol, CA: O'Reilly. Available athttps://r4ds.had.co.nz/). The workflow starts with defining a problem that needs solving as shown in Figure 4.2. The next step involves loading and transforming the data into a format that is suitable for the required analysis. The data science workflow contains a loop that consists of exploration, modelling, and reflection, which is repeated until the problem is solved or is shown to be unsolvable.

Figure 4.2: Data science workflow
Figure 4.2: Data science workflow

The workflow for a data project is independent of the aspect of the data science continuum under consideration. The same principles...