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A Data Office has become a reality as part of many organizations’ enterprise architecture frameworks. A data office can support moving the organization toward a
A shift in technologies and data management will expand traditional methods of data generation, data storage, and data analysis capabilities that will reduce friction and
Data Science is a complex function, where data manipulation, analysis and data management combine with scientific methods, processes, and systems to extract knowledge or insights
Data generated by The Internet of Things (IoT) is having a major effect on insurance companies’ approaches to enterprise data management Introduction Even before the
An enterprise architecture (EA) is a series of conceptual blueprints that defines the structure and operation of an organization to enable strategic progress. Enterprise Architecture
The use of open data is becoming more popular. Data management professionals should develop familiarity with the concept, use, and challenges of open data. Introduction
Proper enterprise architecture must include business focus and business involvement, and models of business requirements at all levels are needed as well as models for
Data rationalization through managed metadata and data modeling, can support semantic resolution, enabling improved analysis and knowledge transfer. Introduction Across the Internet and within internal
The Semantic data web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries Introduction Interest in
Business-focused data analysis activities allow for understanding data and correcting any discrepancies, regardless of systems design or implementation Introduction initiative is the first attempt at
