Modern Data Strategy

• Κύριοι συγγραφείς: Fleckenstein, Mike (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Fellows, Lorraine (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Θέματα: Computers.; Management information systems.; Computer security.; Information Systems and Communication Service.; Business Information Systems.; Systems and Data Security.

 This book contains practical steps business users can take to implement data management in a number of ways, including data governance, data architecture, master data management, business intelligence, and others. It defines data strategy, and covers chapters that illustrate how to align a data strategy with the business strategy, a discussion on valuing data as an asset, the evolution of data management, and who should oversee a data strategy. This provides the user with a good understanding of what a data strategy is and its limits. Critical to a data strategy is the incorporation of one or more data management domains. Chapters on key data management domains-data governance, data architecture, master data management and analytics, offer the user a practical approach to data management execution within a data strategy. The intent is to enable the user to identify how execution on one or more data management domains can help solve business issues. This book is intended for business users who work with data, who need to manage one or more aspects of the organization's data, and who want to foster an integrated approach for how enterprise data is managed. This book is also an excellent reference for students studying computer science and business management or simply for someone who has been tasked with starting or improving existing data management. 

 1 Evolution to Modern Data Management -- 2 Big Data and Data Management -- 3 Valuing Data as an Asset -- 4 Physical Asset Management vs. Data Management -- 5 Leading Data Strategy -- 6 Implementing a Data Strategy -- 7 Overview of Data Management Frameworks -- 8 Data Governance -- 9 Data Architecture -- 10 Master Data Management -- 11 Data Quality -- 12 Data Warehousing and Business Intelligence -- 13 Data Analytics -- 14 Data Privacy -- 15 Data Security -- 16 Metadata -- 17 Records Management.