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• Over the past 20 years, hospitals have also adopted and implemented data warehouse technology to facilitate the reuse of administrative and clinical data for research.
• Implementation of clinical data warehouses encounters ethical, ...

The increasing implementation and use of electronic health records over the last few decades has made a significant volume of clinical data being available. Over the past 20 years, hospitals have also adopted and ...

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Material management is an important part of project cost control, only starting from the key material entry and exit acceptance can we effectively improve the management status of the project site and promote the lean management of construction ...

Integrated learning has attracted much attention from industry and academia. In the new era, colleges and universities need to discuss information management in light of actual conditions, integrate different data in each information system into the same ...

Business Intelligence is the key technologies that ensures effective decision making through extracting relevant information and providing adapted systems as the Data Warehouses. To access decisional information, the decision maker should express ...

In big data, analysis data is collected from different sources in various formats, transforming into the aspect of cleansing the data, customization, and loading it into a Data Warehouse. Extracting data in other formats and transforming it to the ...

In this paper, we present an intelligent methodology for assisting decision-makers in both understanding the structure of a data warehouse model and making decisions. The support module proposed by our method comprises three operations: (i) transforming ...

To facilitate the development of new varieties and conserve plant germplasm data for future needs, Thailand organizations have developed plant germplasm search systems that provide access and exchange plant genetic resource data like the ...

Nowadays, supermarkets and retail stores all use software systems with databases to store customer transactions. Over time, the volume of data is also increasing and it contributes a lot of hidden value in this data warehouse, mining data from ...

In business applications, data integration is typically implemented as a data warehouse architecture. In this architecture, heterogeneous and distributed data sources are accessed and integrated by means of Extract-Transform-Load (ETL) processes. ...

Multi-model DBMSs, which support different data models with a fully integrated backend, have been shown to be beneficial to data warehouses and OLAP systems. Indeed, they can store data according to the multidimensional model and, at the same time,...

• DW provides a versatile solution to the user, who can explore database effectively.

The quantity of electronic bank data grows exponentially with development of Information Technology (IT). The size of these data is impossible for traditional database and human analyst to come up with interesting information that will ...

In advanced database design such as Big Data Warehouses, optimizing large-scale decision support queries passes through the selection of redundant structures such as materialized views and indexes. Materialized View Selection (M V S) ...

Through data mining from vehicle construction equipment, the paper presents a unique approach to the early diagnosis of machinery failures. We used an effective K-means clustering algorithm to discover inconsistencies in field data. ...

Carrying out OLAP analyses in hands-free scenarios requires lean forms of communication between the users and the system, based for instance on natural language. In this paper we introduce VOOL, a framework specifically devised for vocalizing the ...

Analyze and understand how to combine data warehouse with business intelligence tools, and other useful information or tools to visualize KPIs are critical factors in achieving the goal of raising competencies and business results of an ...

The ability to query vast amount of historical data for statistical analysis and reporting is provided by Data Warehouses. They facilitate Business Intelligence for effective decision-making significantly. In recent years, great progress has been ...

The main contribution of this paper is to materialize right cubes according to the users’ priority at the right time which can significantly reduce delays in information retrieval and achieve faster decision making. Therefore, we propose a ...

The Data Atlas is the centerpiece of the PERISCOPE project’s data-driven research. The Atlas constitutes a centralized access point for the exploration, visualization and analysis of the original data produced by PERISCOPE partners, integrated ...

Recent developments in Big Data in financial industry has created a huge opportunity for design and development of effective aggregation (higher level) analytical measures (Fund, Portfolio, Sector, Industry etc.). Lack of these aggregated measures ...

Users of a business intelligence (BI) system employ an approach referred to as online analytical processing (OLAP) to view multidimensional data from different perspectives. Query languages, e.g., SQL or MDX, allow for flexible ...

• Individual OLAP queries are insufficient for documenting and sharing best-practice solutions for analytical problems.