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

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.

Publication Details

Journal
Libra
Published
2024-08-04
DOI
https://doi.org/10.18130/d2k5-vk35
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Libra
Big Data and Business Intelligence
article

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

article en

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.

Libra
Openalex Percentile: Top 47%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.