Data generated by The Internet of Things is having a major effect on insurance companies’ approaches to enterprise data management Introduction Even before the use of computers, data was at the heart of the insurance business. Unlike other enterprises that sell a tangible product, insurers sell a promise. In exchange for your premium dollar today, the insurer promises to pay
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 The concept of open data is not new, but its use is becoming more prevalent as the availability of sources, and the validity of those sources, grows. Problems often arise because these sources are commercially
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 the Semantic Web has skyrocketed, along with interest in the implications of semantic technologies on traditional data management. The promises of the Semantic Web – for example, being able to find information regardless of the
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 systems, ontologies are used to improve search capabilities and make inferences for improved human or computer reasoning. By relating terms in ontology, the user doesn’t need to know the exact term actually stored in the
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 bringing business data together from multiple sources in order to make it available across different departments. Organizations that use a traditional system development approach on their data warehouse (DW) projects usually run into severe source
