Data Governance and Data Management

Data Governance and Data Management
Author :
Publisher : Springer Nature
Total Pages : 218
Release :
ISBN-10 : 9789811635830
ISBN-13 : 9811635838
Rating : 4/5 (838 Downloads)

Book Synopsis Data Governance and Data Management by : Rupa Mahanti

Download or read book Data Governance and Data Management written by Rupa Mahanti and published by Springer Nature. This book was released on 2021-09-08 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book delves into the concept of data as a critical enterprise asset needed for informed decision making, compliance, regulatory reporting and insights into trends, behaviors, performance and patterns. With good data being key to staying ahead in a competitive market, enterprises capture and store exponential volumes of data. Considering the business impact of data, there needs to be adequate management around it to derive the best value. Data governance is one of the core data management related functions. However, it is often overlooked, misunderstood or confused with other terminologies and data management functions. Given the pervasiveness of data and the importance of data, this book provides comprehensive understanding of the business drivers for data governance and benefits of data governance, the interactions of data governance function with other data management functions and various components and aspects of data governance that can be facilitated by technology and tools, the distinction between data management tools and data governance tools, the readiness checks to perform before exploring the market to purchase a data governance tool, the different aspects that must be considered when comparing and selecting the appropriate data governance technologies and tools from large number of options available in the marketplace and the different market players that provide tools for supporting data governance. This book combines the data and data governance knowledge that the author has gained over years of working in different industrial and research programs and projects associated with data, processes and technologies with unique perspectives gained through interviews with thought leaders and data experts. This book is highly beneficial for IT students, academicians, information management and business professionals and researchers to enhance their knowledge and get guidance on implementing data governance in their own data initiatives.


Data Governance and Data Management Related Books

Data Governance and Data Management
Language: en
Pages: 218
Authors: Rupa Mahanti
Categories: Business & Economics
Type: BOOK - Published: 2021-09-08 - Publisher: Springer Nature

DOWNLOAD EBOOK

This book delves into the concept of data as a critical enterprise asset needed for informed decision making, compliance, regulatory reporting and insights into
Non-Invasive Data Governance
Language: en
Pages: 148
Authors: Robert S. Seiner
Categories: Computers
Type: BOOK - Published: 2014-09-01 - Publisher: Technics Publications

DOWNLOAD EBOOK

Data-governance programs focus on authority and accountability for the management of data as a valued organizational asset. Data Governance should not be about
Data Stewardship
Language: en
Pages: 248
Authors: David Plotkin
Categories: Computers
Type: BOOK - Published: 2013-09-16 - Publisher: Newnes

DOWNLOAD EBOOK

Data stewards in business and IT are the backbone of a successful data governance implementation because they do the work to make a company’s data trusted, de
The Data Governance Imperative
Language: en
Pages: 162
Authors: Steve Sarsfield
Categories: Business & Economics
Type: BOOK - Published: 2009-04-23 - Publisher: IT Governance Publishing

DOWNLOAD EBOOK

This practical book covers both strategies and tactics around managing a data governance initiative to help make the most of your data.
DAMA-DMBOK
Language: en
Pages: 628
Authors: Dama International
Categories: Database management
Type: BOOK - Published: 2017 - Publisher:

DOWNLOAD EBOOK

Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a