Data mart

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

Data Warehouse Strategy to Enable Performance Analysis

Abstract: The Virginia Department of Transportation (VDOT) has engaged to implement an enterprise data warehouse as part of a strategic investment in its information technology (IT) infrastructure. Data warehousing provides an information architecture that serves as the enterprisewide source of data for performance analysis and organizational reporting. To assist VDOT in achieving its strategic outcome area objectives, a programming and scheduling (P&S) data mart is being developed to track preconstruction project activities. This data mart and subsequent data marts function as departmental decision support platforms, enabling VDOT's operating divisions to perform their own enhanced analytical processing, visualization, and data mining for more informed business decision capabilities. Presented is a case study based on the enterprise data warehouse and P&S data mart being developed and implemented for VDOT by TransCore. Explicitly described is how one VDOT division, Programming and Scheduling, will benefit by inves...

Big data-based aid decision making platform for planning design of intelligent power distribution network

Abstract: The invention discloses a big data-based aid decision making platform for planning design of an intelligent power distribution network. The platform comprises an application layer and an offline layer, wherein a data center, a prediction analysis module, a project optimization module and a project management module service layer are arranged in the application layer; a data exchange module, a data calculation module, a data analysis module, a data management module and an integrated service module are arranged in the service layer; and a data mart layer, a data warehouse layer and a unified view region are arranged in the offline layer. According to the big data-based aid decision making platform for the planning design of the intelligent power distribution network, through the arrangement of the offline layer, a large amount of data can be effectively collected; through the arrangement of the service layer, the data can be effectively processed; through the arrangement of the application layer, an optimized project can be created effectively according to the data; and therefore, the problems of difficult data collection, difficult prediction, difficult analysis and difficult management control are effectively solved.

Ontology-Based Big Dimension Modeling in Data Warehouse Schema Design

Abstract: During data warehouse schema design, designers often encounter how to model big dimensions that typically contain a large number of attributes and records. To investigate effective approaches for modeling big dimensions is necessary in order to achieve better query performance, with respect to response time. In most cases, the big dimension modeling process is complicated since it usually requires accurate description of business semantics, multiple design revisions and comprehensive testings. In this paper, we present the design methods for modeling big dimensions, which include horizontal partitioning, vertical partitioning and their hybrid. We formalize the design methods, and propose an algorithm that describes the modeling process from an OWL ontology to a data warehouse schema. In addition, this paper also presents an effective ontology-based tool to automate the modeling process. The tool can automatically generate the data warehouse schema from the ontology of describing the terms and business semantics for the big dimension. In case of any change in the requirements, we only need to modify the ontology, and re-generate the schema using the tool. This paper also evaluates the proposed methods based on sample sales data mart.

Actualizing Personalized Healthcare for Women through Connected Data Systems: Breast Cancer Screening and Diagnosis.

Abstract: Background: Healthcare organizations have invested in electronic patient data systems, yet use of health data to optimize personalized care has been limited. Primary Study Objective: To develop and pilot an integrated source of health system data related to breast healthcare. Methods/Design: This study is a quality improvement project. Patient-level data from multiple internal sources were identified, mapped to a common data model, linked, and validated to create a breast healthcare-specific data mart. Linkages were based on matching algorithms using patient identifiers to group data from the same patient. Data definitions, a data dictionary, and indicators for quality and benchmarking aligned with standardized measures. Clinical pathways were developed to outline the patient populations, data elements, decision points, and outcomes for specific conditions. Setting: Electronic data sources in a community-based health system in the United States. Participants: Women receiving breast cancer screening, preve...

Construction graphique d'entrepôts et de magasins de données.

Abstract: Nowadays, decisional systems have became a significant research topic in databases. Data warehouses and data marts are the main elements of such systems. This paper presents our decisional support system. We present graphical interfaces which help the administrator to build data warehouses and data marts. We present a data warehouse building interface based on an object-oriented conceptual model. This model allows the warehouse data historisation at three levels: attribute, class and environment. Also, we present a data mart building interface which allows warehouse data to be reorganised through a multidimensional object-oriented model.