Data mart

About: Data mart is a research topic. Over the lifetime, 559 publications have been published within this topic receiving 8550 citations.

Integral data mart structure, and operation supporting system

Abstract: PROBLEM TO BE SOLVED: To quickly prepare a data mart corresponding to the request of a user by automatically generating a high speed data mart preparation program by operating selective designation from a screen according to the model of a prepared program structure SOLUTION: This integral data mart structure and operation supporting system are provided with a data mart automatic generating function, a web retrieving/report preparing function, and an operation control function so that a specific data base for extracting and working data from a trunk data base, and for preserving necessary information can be constructed and operated

Evaluating open access journals using Semantic Web technologies and scorecards

Abstract: This paper describes a process to develop and publish a scorecard from an OAJ Open Access Journal on the Semantic Web using Linked Data technologies in such a way that it can be linked to related datasets. Furthermore, methodological guidelines are presented with activities related to each step of the process. The proposed process was applied to a university OAJ, including the definition of the KPIs Key Performance Indicators linked to the institutional strategies, the extraction, cleaning and loading of data from the data sources into a data mart, the transformation of data into RDF Resource Description Framework, and the publication of data by means of a SPARQL endpoint using the Virtuoso software. Additionally, the RDF data cube vocabulary has been used to publish the multidimensional data on the Web. The visualization was made using CubeViz, a faceted browser to present the KPIs in interactive charts.

Clinical benchmarking enabled by the digital health record.

Abstract: Office-based physicians are often ill equipped to report aggregate information about their patients and practice of medicine, since their practices have relied upon paper records for the management of clinical information. Physicians who do not have access to large-scale information technology support can now benefit from low-cost clinical documentation and reporting tools. We developed a hosted clinical data mart for users of a web-enabled charting tool, targeting the solo or small group practice. The system uses secure Java Server Pages with a dashboard-like menu to provide point-and-click access to simple reports such as case mix, medications, utilization, productivity, and patient demographics in its first release. The system automatically normalizes user-entered clinical terms to enhance the quality of structured data. Individual providers benefit from rapid patient identification for disease management, quality of care self-assessments, drug recalls, and compliance with clinical guidelines. The system provides knowledge integration by linking to trusted sources of online medical information in context. Information derived from the clinical record is clinically more accurate than billing data. Provider self-assessment and benchmarking empowers physicians, who may resent "being profiled" by external entities. In contrast to large-scale data warehouse projects, the current system delivers immediate value to individual physicians who choose an electronic clinical documentation tool.

Custom data mart creation

Abstract: Systems, methods, and computer-readable media for creating custom data marts are provided. A selection of at least one table from a data source stored within a data warehouse is received. A selection of at least one column from the at least one table is received. Joins are created based on the selections, metadata is created and stored, and physical schema is generated to store the data mart data. The custom data mart fact table is populated with data from the selected columns. Facilities are provided for the end-user to create an abstraction layer for business intelligence reporting needs.

Building a Data Warehouse step by step

Abstract: Data warehouses have been developed to answer the increasing demands of quality information required by the top managers and economic analysts of organizations. Their importance in now a day business area is unanimous recognized, being the foundation for developing business intelligence systems. Data warehouses offer support for decision-making process, allowing complex analyses which cannot be properly achieved from operational systems. This paper presents the ways in which a data warehouse may be developed and the stages of building it.