Abstract

As the industry is racing to harness the power of data, demand for data science professionals is growing at an increasing rate. However, almost every organization has a unique way of defining roles in data science and associated skills and knowledge. This has resulted in a confusing industry landscape for employers, academic and training institutions, and existing and aspiring data science professionals. This article is the first in a series authored by Initiative for Analytics and Data Science Standards (IADSS). 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. 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.

Highlights

  • This article is the first in a series authored by Initiative for Analytics and Data Science Standards (IADSS)

  • 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

  • We present a Data Science Knowledge Framework, that we believe can support industry standardization and building measurement and assessment methodologies for data science professionals

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Summary

Introduction

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. 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. 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.

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