'I encounter many data scientists and analysts whose sole focus is solving analytical problems and developing accurate models. They all need to read this excellent book and adopt its recommendations!'.
- Thomas H. Davenport, Distinguished Professor, Babson College, Research Fellow, MIT Initiative on the Digital Economy
'This book provides a compelling, credible and sound narrative to de-code complexity by developing a set of competencies (action, social, awareness, cognitive, exploration and organizational) supported by emotional intelligence. A must read for Leaders and HR practitioners, for the intellectual curious eager to understand that Human Beings will have to remain central to Human Development'.
-Paolo Gallo, Former CHRO at World Economic Forum, World Bank and European Bank
Shedding new light on the human side of big data through the lenses of emotional and social intelligence competencies, this book advances the understanding of the requirements of the different professions that deal with big data. It also illustrates the empirical evidence collected through the application of the competency-based methodology to a sample of data scientists and data analysts, the two most in-demand big data jobs in the labor market. The book provides recommendations for the higher education system to offer better designed curricula for entry-level big data professions. It also offers managerial insights in describing how organizations and specifically HR practitioners can benefit from the competency-based approach to overcome the skill shortage that characterizes the demand for big data professional roles and to increase the effectiveness of the selection and recruiting processes.
Sara Bonesso is associate professor of Business Organization and Human Resources Management at the Ca' Foscari University of Venice. She is also one of the founders and the Vice-Director of the Ca' Foscari Competency Centre.
Elena Bruni is a post-doc researcher at the Department of Management, Ca' Foscari University of Venice.
Fabrizio Gerli is Associate Professor of Business Organization and Human Resources Management at Ca' Foscari University of Venice. He is also one of the founders and the Director of the Ca' Foscari Competency Centre.
Autorentext
Sara Bonesso is associate professor of Business Organization and Human Resources Management at the Ca' Foscari University of Venice, Italy. She is also one of the founders and the Vice-Director of the Ca' Foscari Competency Centre.
Elena Bruni is post-doc researcher at the Department of Management, Ca' Foscari University of Venice, Italy.
Fabrizio Gerli is Associate Professor of Business Organization and Human Resources Management at Ca' Foscari University of Venice, Italy. He is also one of the founders and the Director of the Ca' Foscari Competency Centre.
Klappentext
Shedding new light on the human side of big data through the lenses of emotional and social intelligence competencies, this book advances the understanding of the requirements of the different professions that deal with big data. It also illustrates the empirical evidence collected through the application of the competency-based methodology to a sample of data scientists and data analysts, the two most in-demand big data jobs in the labor market. The book provides recommendations for the higher education system to offer better designed curricula for entry-level big data professions. It also offers managerial insights in describing how organizations and specifically HR practitioners can benefit from the competency-based approach to overcome the skill shortage that characterizes the demand for big data professional roles and to increase the effectiveness of the selection and recruiting processes.
Inhalt
This section provides the motivation for this project, the relevance of the topic addressed by the book
and a synopsis of the main themes covered by each chapter.
Chapter 1.
Big data analytics professionals: emerging trends and job profiles
Organizations have been deeply changing because of the digital transformation. New jobs are
becoming central to the success of any company, regardless the sector and the industry (Vidgen et al.
2017; Davenport and Harris 2017, 2007; Lorenz et al. 2015). One of the most pertinent definition
about professionals working in Big Data field is from American Marketing Association website:
Big Data professionals [are] individuals who can apply sophisticated quantitative skills to
data transcribing actions, interactions, or other behaviors of people to derive insights and
prescribe actions. Big Data professionals are further distinguished due to their ability to
work with extremely large datasets that may be problematic for standard tools. Data
Scientists are another subset of Big Data professional, and typically work with
continuously streaming, unstructured data that may come from social media, audio, or
video files (Keller, Ahern, & Works).
Scientific literature is still struggling to find a common definition of professionals working with Big
Data. More importantly, there is still confusion about the boundaries of different groups of jobs.
Indeed, job profiles, duties, tasks, and responsibilities are often overlapping. A first macro distinction
was recognized by Harris and Mehrotra (2014) between data scientists and analysts in general. They
distinguished the two categories according to five dimensions: types of data, preferred tools, nature of
work, typical educational background, and mind-set. However, nowadays organizations have different
profiles and all of them contribute in maintaining and providing solutions leveraging on a large
volume of data, for instance system architects, data analysts, data engineers, business analysts, and
data scientists. System architects are responsible to build and maintain the full technology
infrastructure for data ecosystems. Therefore, they manage the company's server platform; they
support processes to load and manage the analytical data store; they integrate new data sources. Data
analysts on the other hand are responsible to support other IT functions regarding data processing in a
specific domain. Data engineers are quantitative analysts (such as programmers, software engineers)
and they support the data governance. They collect, cleanse, blend, form, organize data in the general
data warehouse. They solve more conventional quantitative analysis problems and their main
responsibility is to ensure data quality so that it can be properly analyzed. Business analysts analyze
data and communicate results through reports and dashboards to facilitate (and possibly give advice
to) business decision making. Lastly, data scientists are statisticians with a strong scientific
background. They acquire and bring structure to large quantities of formless data (or Big Data) to
generate value to the company. Despite the current literature acknowledges about these four macro
categories of job profiles, there is still a confusion about their impact within organizations and how
they contribute in decision making process. Therefore, this chapter will contribute to the extant
literature by addressing the following questions: which is the macro trend in the labor market of Big
Data professionals? What is the role and the main responsibilities of these eme…
