The MAGIC of Data Management: Understanding the Value and Activities of Data Management

TL;DR

This paper introduces the MAGIC framework, a simple and comprehensive model for understanding data management activities, emphasizing their importance in maximizing data value and reducing failures.

Contribution

It presents a new, accessible framework called MAGIC that clearly delineates key data management activities for education, research, and practice.

Findings

Defines five core activities of data management: Modeling, Acquisition, Governance, Infrastructuring, Consumption.

Provides a structured approach to teaching and understanding data management.

Enhances clarity on the importance of data management in technological innovation.

Abstract

In an era dominated by information technology, the critical discipline of data management remains undervalued compared to the innovations it enables, such as artificial intelligence and social media. The ambiguity surrounding what constitutes data management and its associated activities complicates efforts to explain its importance and ensure data are collected, stored and used in a way that maximizes value and avoids failures. This paper aims to address these shortcomings by presenting a simple framework for understanding data management, referred to as MAGIC. MAGIC encompasses five key activities: Modeling, Acquisition, Governance, Infrastructuring, and Consumption support tasks. By delineating these components, the MAGIC framework provides a clear, accessible approach to data management that can be used for teaching, research and practice.