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The decision making process is mainly data driven, which makes Data Warehousing play a crucial role in providing a reliable and efficient tool to meet analytical needs and provide end users and decision makers with useful insights. However, several surveys show that a significant percentage of Data Warehouse (DW) projects fail to meet their business goals. Indeed, it is mainly due to the lack of any...
The main purpose of data warehouses (DW) is to maintain large volumes of historical data (originating from multiple heterogeneous data sources and representing the different states of a system caused by various business events or activities) in a format that facilitates its analysis in order to support timelier and better decision-making, at both the operational and strategic level. In order for a...
This paper discusses an integrated methodology to structure and formalize business requirements in large dataintensive projects, e.g. data warehouses implementations, turning them into precise and unambiguous data definitions suitable to facilitate harmonization and assignment of data governance responsibilities. We place a business information model in the center — used end-to-end from analysis,...
Petrology, petrography and ordinary geologic data compose an ever increasing collection of information for post-processing analysis. Geoscientists at Universidad Autónoma de Chihuahua, are consistently working with these data collections for research purposes. Scientists record this information, as well as that obtained in bibliography references, in order to study it and lead to important research...
With the appearance of computer network, could computing, the internet of things, big data more and more get the attention of people. Understanding and Application big data, and make a scientific decision, become the most necessary and urgent problem. Big data, not only let the database have always been known for efficient and secure storage embarrassed, but also allow the data warehouse that provide...
Article is devoted to working out the information technology for monitoring of business processes of the enterprise, allowing to automate formation processes of representations for the given business process. The block diagram of this technology is developed and appointment of its basic elements is considered. The technique for adjustment of the offered information technology taking into account features...
Based on data requirements for remote maintenance for low-speed maglev train, this paper analyzed the key data sources, maintenance operations and the needs of decision-makers of the train, combined with the characteristics of data warehouse technology, and a maglev train remote maintenance support system data warehouse was designed according to the process of data warehouse design, which provided...
The availability of reference models for data warehouses lowers the obstacles that inhibit small and medium-sized enterprises (SMEs) from using business intelligence technology. Service providers may offer to companies a set of pre-configured reference models for various industries. Modelers may then customize the chosen reference model, tailoring the model to the specific needs of the individual...
Aiming at such problems in the smart city program like long cycle, low efficiency, high cost, low reusability, maintenance difficulty, this paper puts forward development platform of rapid workflow building system which is based on intelligent spreadsheets to accelerate the development process and enhance the efficiency.
In this paper, we propose a new conceptual model based on the visualization of data flow showing transformations of records accompanied with attribute transformations. A data warehouse development relies on the development of Extract, Transform, and Load (ETL) processes responsible for extracting data from transactional systems, data quality checks, transformation and conversion and loading data to...
The paper presents a coordinated set of data modeling styles relevant for data warehouse design in the context of relational databases. The scope of presented models covers: a) entity relationship models of existing relational DB sources, b) logical data vault model for integrated enterprise data warehouses as a system of records, c) dimensional fact model for analysis leading to query prototyping...
Today for compliance reasons as well as for optimization of business processes companies need to store runtime data of processes. However, creating and adapting an analytics infrastructure using data warehousing is a cumbersome task. In previous work we introduced the aPro architecture in order to enable companies with heterogeneous infrastructures to create near real-time monitoring and analytics...
In a Dimensional Model of Data Warehouse, process of designing conceptual schema based on user requirements face some challenges due to data sources may lack some important elements. One way to improve schema is by utilizing alternative sources of knowledge that act as DW additional data sources. Since past few years, there are several researchers who present the use of Ontology to improve several...
An assessment of a method that enabled to design a data warehouse logical model in accordance with the business viewpoint of an enterprise showed that not considering the physical viewpoint when designing the data warehouse was the major flaw of the method, and that a tool has to be proposed to generate the data warehouse data instances when business viewpoints or input databases are modified. Our...
This study explores the architecture of Decision Support System for Tariff and Trade that not only facilitates data analysis and trade forecast by providing an integration of report generation tools, but also enhances the retrieval of information and support decision-making by providing economic quantitative analysis tools and system modeling tools. Based on multi-dimensional modeling techniques of...
Planning and development an data warehouse ETL (Extraction, Transformation and Load) system, is typically a complex and time consuming task whose complexity is highly influenced not only by the amount of data to analyze, but also the computational effort required to integrate these data in same data structure and storage model in order to load it into a final data repository. Despite its enormous...
Organizations use the techniques of data warehouse and knowledge discovery in databases to generate useful information to support their strategic decisions. These techniques, if properly combined, can offer a broad knowledge of business domain treaty. This paper proposes the use of ontology to organize and categorize the relevant data from the field of social vulnerability. With the exploration of...
To analyze large quantity of information in medication with scientific technique and to provide decision supports for doctors, we set up the research on Adverse Drug Reactions (ADRs) by constructing a multidimensional data warehouse. Adopted SQL Server 2005 business intelligence tools, we extracted, transformed and loaded the data from spontaneous reporting system (SRSs) of ADRs to the data warehouse,...
Although much progress has been made to plan and execute Software Development projects in an agile manner, Data Warehouse or Business Intelligence projects seem to still execute in a more traditional manner. Data Warehouse projects are quite different than Software Development projects and need a set of Agile practices that are distinctly their own. This paper is an account of Data Warehouse redevelopment...
The need to analyze huge amount of data for various business intelligence applications is well known. However, the rate at which enterprise data is generated now demands periodic migration of older data from the operational data warehouse to magnetic tapes. In this paper, we propose an "Active data archival service" in which the data is seamlessly archived on the cloud while ensuring that...
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