Data management

About: Data management is a research topic. Over the lifetime, 31574 publications have been published within this topic receiving 424326 citations.

VisTrails: visualization meets data management

Abstract: Scientists are now faced with an incredible volume of data to analyze. To successfully analyze and validate various hypothesis, it is necessary to pose several queries, correlate disparate data, and create insightful visualizations of both the simulated processes and observed phenomena. Often, insight comes from comparing the results of multiple visualizations. Unfortunately, today this process is far from interactive and contains many error-prone and time-consuming tasks. As a result, the generation and maintenance of visualizations is a major bottleneck in the scientific process, hindering both the ability to mine scientific data and the actual use of the data. The VisTrails system represents our initial attempt to improve the scientific discovery process and reduce the time to insight. In VisTrails, we address the problem of visualization from a data management perspective: VisTrails manages the data and metadata of a visualization product. In this demonstration, we show the power and flexibility of our system by presenting actual scenarios in which scientific visualization is used and showing how our system improves usability, enables reproducibility, and greatly reduces the time required to create scientific visualizations.

An Introduction to Geographical Information Systems

Abstract: 1. What is GIS? 2. Concepts of Space 3. The Evolution of Computer Methods for the Handling of Spatial Data 4. Modelling Systems Thinking and GIS 5. Spatial Data Models 6. Attribute Data Management 7. Data Encoding and Manipulation 8. Data Analysis 9. Data Output 10. Data Quality Issues 11. Organisational Issues 12. Project Design

BigDataBench: A big data benchmark suite from internet services

Abstract: As architecture, systems, and data management communities pay greater attention to innovative big data systems and architecture, the pressure of benchmarking and evaluating these systems rises. However, the complexity, diversity, frequently changed workloads, and rapid evolution of big data systems raise great challenges in big data benchmarking. Considering the broad use of big data systems, for the sake of fairness, big data benchmarks must include diversity of data and workloads, which is the prerequisite for evaluating big data systems and architecture. Most of the state-of-the-art big data benchmarking efforts target evaluating specific types of applications or system software stacks, and hence they are not qualified for serving the purposes mentioned above.

Talent management: A strategy for improving employee recruitment, retention and engagement within hospitality organizations

Abstract: Purpose – The purpose of this article is to clarify what is meant by talent management and why it is important (particularly with respect to its affect on employee recruitment, retention and engagement), as well as to identify factors that are critical to its effective implementation. Design/methodology/approach – This article is based on a review of the academic and popular talent management literatures. Findings – Talent management is an espoused and enacted commitment to implementing an integrated, strategic and technology enabled approach to human resource management (HRM). This commitment stems in part from the widely shared belief that human resources are the organization's primary source of competitive advantage; an essential asset that is becoming in increasingly short supply. The benefits of an effectively implemented talent management strategy include improved employee recruitment and retention rates, and enhanced employee engagement. These outcomes in turn have been associated with improved operational and financial performance. The external and internal drivers and restraints for talent management are many. Of particular importance is senior management understanding and commitment. Practical implications – Hospitality organizations interested in implementing a talent management strategy would be well advised to: define what is meant by talent management; ensure CEO commitment; align talent management with the strategic goals of the organization; establish talent assessment, data management and analysis systems; ensure clear line management accountability; and conduct an audit of all HRM practices in relation to evidence‐based best practices. Originality/value – This article will be of value to anyone seeking to better understand talent management or to improve employee recruitment, retention and engagement.

A systems thinking framework for knowledge management

Abstract: Myriad frameworks have been developed for knowledge management However, the field has been slow in formulating a generally accepted, comprehensive framework for knowledge management This paper reviews the existing knowledge management frameworks and provides suggestions for what a general framework should include The distinguishing feature of this research is that it emphasizes placing knowledge management in a larger context of systems thinking so that the influencing factors on its success or failure can better be recognized and understood