Data Management: Managing Data as an Organizational Resource

New Directions for …, 1987

Administrative use of the microcomputer has had a profound impact on college and university operations. In particular, administrative computing activities, once the sole responsibility of the central computing enterprise within an institution, are now widely dispersed throughout the organization. Powerful, easy-to-use desktop computers and user-friendly software have enabled professionals at virtually every operational level to participate in the collection, analysis, and reporting of data. As users request and acquire data, and become more proficient in manipulating those data, they assume a more active role in data-related operations. It is these expanding roles, new capabilities, and new expectations that have serious implications for effective data administration and management.

Information Resources Management Journal, 2000

Quality: Data values are inaccurate, outdated, and inconsistent.

2018

In today's digital landscape, organizations face the challenge of managing vast amounts of data characterized by high volume, variety, and velocity. Without consistent data management practices, data becomes fragmented and unreliable, making it difficult to achieve high data quality and seamless integration. This paper addresses the role of Master Data Management (MDM) in overcoming these challenges, focusing on its impact on simplifying operations, enhancing strategic decision-making, and enabling scalability by showing the practical architecture of how MDM is created. This paper presents an approach to MDM implementation, showcasing practical architectures and real-world examples that bridge the gap between theoretical concepts and applied data management. The research introduces centralized data models and standardized quality control mechanisms, demonstrating how MDM serves as the backbone of modern data governance. The paper also explores the integration of MDM with Artificial Intelligence and Machine Learning for data quality optimization. The paper also examines the role of data stewards in supporting MDM initiatives. Findings indicate that well-implemented MDM strategies not only enhance operational efficiencies but also contribute to significant cost savings and improved regulatory compliance. By providing a roadmap for successful MDM implementation, this research offers valuable insight for data engineers, business leaders, and academics, contributing to the development of robust, scalable, and effective data management ecosystems in the ever-evolving digital era.

Data, Information and Knowledge Management

ment "is considered important. This multidisciplinary research book is considered to be important in that it contains both qualitative and quantitative examples. I hope that the topics in the book will guide the researchers who are interested in the future research. I would like to thank all the authors of the department, academicians and researchers, who have spent important time in the formation of the book and who made important researches, for their efforts and continued their success.

Enterprises are facing problems in managing the quality and value of their key data objects (often referred to as master data). This article presents the findings from a case study comprising six large enterprises. The study results point to the importance of the situational nature of master data as a strategic resource, which must be considered when analyzing how the quality of data affects its value for business.

Eddy Covariance, 2011

Computer, 2007

version (changing data into other forms, states, or products), or scrubbing (inspecting and manipulating, recoding, or rekeying data to prepare it for subsequent use). • Approximately two-thirds of organizational data managers have formal data management training; slightly more than two-thirds of organizations use or plan to apply formal metadata management techniques; and slightly fewer than one-half manage their metadata using computer-aided software engineering tools and repository technologies. 3 When combined with our personal observations, these results suggest that most organizations can benefit from the application of organization-wide data management practices. Failure to manage data as an enterprise-, corporate-, or organization-wide asset is costly in terms of market share, profit, strategic opportunity, stock price, and so on. To the extent that world-class organizations have shown that opportunities can be created through the effective use of data, investing in data as the only organizational asset that can't be depleted should be of great interest. Increasing data management practice maturity levels can positively impact the coordination of data flow among organizations, individuals, and systems. Results from a self-assessment provide a roadmap for improving organizational data management practices.

In challenging times good decision-making becomes critical. The best decisions are made when all the relevant data available is taken into consideration. The best possible source for that data is a welldesigned data warehouse. The concept of data warehousing is not hard to understand. The concept is to create a permanent storage space for the data needed to support analysis, reporting, and other organizational activities. The goal of this paper is to elicit the crucial role of data warehousing in an organization performance and decision making.