Some estimates predict the future demand for professionals with analytics and data science skills to exceed two to three million in the United States alone. Collectively, these professional disciplines are referred to as ‘analytics’ and ‘data science.’ The demand for analytics and data science skills parallels the growth of interest and investment in data science. The data could be structured or unstructured. The data could be in stored and managed in a variety of formats: from relational databases to NoSQL databases to massive data stores, file systems, federated or totally fragmented stores, or BigData platforms. These disciplines help unlock the value of data in a spectrum of organizations, businesses, scientific research, NGOs, and governments worldwide. Leading this transformation is a set of professional disciplines founded upon the principles of applied statistics, management science, and computer science, among several other fields. These developments have helped transform industries and led to the inception of new business models that focus on creating data-driven products, features, and services.
What do you think of when you hear the term ‘data science?’ More importantly, who are data scientists, data engineers, and analytics professionals? We have observed over the last decade a surge of interest in all things ‘data.’ Data collection, processing, and interpretation have evolved over the years to become increasingly sophisticated. Keywords: data science roles, skills and knowledge, hiring and assessment, industry standards, data analysis, data science, analytics. We then present a Data Science Knowledge Framework, that we believe can support industry standardization and building measurement and assessment methodologies for data science professionals. We review the history of data science, which we trace back to 1974, and the emergence of data science as a profession in the industry, followed by a classification of knowledge and skills commonly associated with data science professionals, pointing to a lack of detailed and consistent treatment of the topic. This article is the first in a series authored by Initiative for Analytics and Data Science Standards (IADSS). This has resulted in a confusing industry landscape for employers, academic and training institutions, and existing and aspiring data science professionals. However, almost every organization has a unique way of defining roles in data science and associated skills and knowledge. As the industry is racing to harness the power of data, demand for data science professionals is growing at an increasing rate.
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