At a Glance
Title: Business Skills for Data Scientists: Practical Guidance in Six Key Topics
Target Audience: Data Scientists, Analysts, Business Decision Makers
Subject: Business Skills for Data Scientists
Author: David Stephenson, John Elder (Foreword)
Language: English
Pages: 306
Price: Kindle $9.99, Paperback $28.78
Positive: Practical guidance, comprehensive coverage of business skills
Negative: –
Buy: Amazon
In Detail
“Business Skills for Data Scientists” by David Stephenson and John Elder is a comprehensive manual for anyone working or planning to work in data science. It places a special focus on “soft” business skills that are often overlooked. A practical example from the book illustrates how a data scientist, while technically adept, but lacking in communication skills, led a crucial project to failure. The lack of effective communication led to misunderstandings with stakeholders and ultimately to the abandonment of the project.
The book is structured around six key areas:
Finding Your Place in the Company: This is often the first and crucial step. Here you learn how to understand your role in the context of the entire company and how to effectively position yourself in teams and projects.
Interacting with Complicated Colleagues: Once you have found your place, you need to learn how to deal with a variety of personalities. The book offers strategies for dealing with difficult colleagues and for creating a positive work environment.
Mastering Clear Communication: This area is at the heart of many challenges and solutions. You learn to communicate your ideas and results in a way that is understood by non-technical stakeholders.
Managing Expectations: This is about setting realistic goals and communicating them clearly to avoid disappointments and failures. The book offers techniques for effective communication and managing stakeholder expectations.
Executing Projects from Start to Finish: In this section, you will learn how to plan, execute, and complete projects while keeping all stakeholders in mind. Methods such as Agile and Scrum are discussed, which can be useful in data science.
Managing Your Career: This is an ongoing process that encompasses all other areas. It’s not just about the next promotion, but about continuous learning and adapting to new challenges and technologies.
These areas build on each other and are arranged to correspond to the typical career development of a data scientist. For example, clear communication is not only important in itself but is also crucial for managing expectations and successfully executing projects.
Although the book was not explicitly written for developing data strategies, it is nevertheless a valuable resource in this area. It offers concrete techniques for stakeholder management and emphasizes the importance of empathy and understanding the perspectives of others. This holistic perspective distinguishes it from other, more technically oriented books, making it an indispensable read for those seeking a comprehensive foundation for success in data science and data strategy development.
This text was created with the help of ChatGPT.
