Warehouse Technology Research Articles

Application Research of Data Warehouse in CRM

Customer relationship management (CRM) is an integral part in the manufacturing enterprise information. The content of CRM is based on customer information and business transaction data, and using computer information technology to deeply analysis massive data of data warehouse. The purpose is to identify customers’ different features and analyze customer behaviors, then dig out the information of commercial value to help business planning and decision-making related business activities. The thesis introduces the system of the CRM based on Data Warehouse: to describe and predict the model of enterprise customers’ behavior by data warehouse and data mining theory and technology. The purpose is to optimize the entire CRM process, and effectively realize customer relationship management ultimately. Research and analysis of data warehouse in CRM to achieve other functions such as customer behavior analysis, key customers found and market performance evaluation. It can further analyze amounts of customer information in data warehouse, acquire efficient information about how to enhance the advantages of market competition, make the concept and goal of CRM can be achieved and satisfy the demand and challenge in modern e-commerce times. It can help enterprises increase market decision-making ability, gain competitive advantages and perfect business plan.

A Time and Cost Effective Approach to 3D Scenario Building in a Digital Game Design Class

This paper demonstrates an integration of modern technologies to provide an effective approach that can help teachers and students focus on creative design rather than on complex graphic tools or commercial game engines in a capstone class. Ignoring the unnecessary functions of expensive commercial packages, we develop and implement our own solution package that includes Google SketchUp, 3D Warehouse and Microsoft Virtual Worlds technology to teach gaming context and content design with 3D scenario building. The empirical experiment proved the feasibility of our work when the students were able to visualize and present their designs of digital games with less cost and fewer efforts than would be needed with the commercial software packages that are generally used to achieve this.

Ontology-based structured web data warehouses for sustainable interoperability: requirement modeling, design methodology and tool

The spectacular growth of the Internet and its widespread adoption by worldwide corporations lead to an enormous quantity of heterogeneous, distributed and autonomous data sources. To facilitate the access to these huge amounts of data and make these sources interoperable, two technologies may be combined: data warehousing and ontologies. Data warehouses are designed to aggregate data and allow decision makers in these companies to obtain accurate, complete and up to date information. In the past decade, Data Warehouse Technology (DWT) has been successfully applied in several domains such as telecommunication, retail, finance and many other industries. It supports a wide range of applications throughout the enterprise. The DWT has been largely used to offer sustainable solutions for enterprises. On the other hand, ontologies are models for specifying the semantics of concepts used by various heterogeneous sources in a well defined and unambiguous way. Ontologies exist in various domains (E-commerce, Engineering, Tourism, etc.) and are used to increase interoperability between sources. They may be used to improve communication between decision makers and users collaborating together, by specifying the semantics of the used concepts. In this paper, we propose a methodology for designing data warehousing applications from various sources. Each source has its local ontology referencing a global one. The presence of ontologies has three main contributions: (i) each owner of each source may use it to define his/her requirements, (ii) it reduces most important types of conflicts that may exist in sources and requirements (schematic and semantic) and (iii) it facilitates the sustainable urbanization of the target data warehouse. Our methodology is supported by a case tool facilitating the tasks of data warehouse designers.

Realization and Application of Customer Attrition Early Warning Model in Security Company

In this paper, we propose the customer attrition early warning model based on data warehouse and data mining technologies, which is achieved and applied in our security company. The modeling variables can be selected by means of the combination with decision tree and the gradual regression in Logistic regression. Then customer attrition early warning model can be constructed based on Logistic regression. The results show that the model can strongly promote the customer attrition capturing rate, push on the building of the company customer marketing management and customer service management organization, and economize the marketing cost. The company profits promotion and trade competitive power can be promised. DOI: h ttp://dx.doi.org/10.11591/telkomnika.v10i5.1270

Design of Automatic Guided Vehicles Based on Computer Control

The automated Guided Vehicles is the development trend of modern automated warehousing technology, which can realize the flexible transport, the use of flexible, high transport efficiency, energy saving, no pollution, significant savings in labor costs. The paper gave a brief introduction about the structure and function of the AGV, and a detailed description about the movement mathematical model and navigation calculation of the AGV. In the end the paper designed the control system of the AGV.

Building Con?ict-Aware Profiling Ontology from Data Warehouses

User profiles or user models are crucial in many areas in which it is essential to obtain knowledge about users of software applications such as data warehouse technologies. To enhance the personalized services, group profiles are derived through combining individual user profiles in order to represent group modelling. In this paper, we propose a new representation of group profiles in OLAP context using the ontological modelling. Our main aim is to semantically enrich the representation of group preferences in data warehouses. Our ontology is validated using set of real collected OLAP query logs in stock market area. General Terms Profiling, Data warehouses, Ontology.

Construction of Digital Mine and Key Technologies

In China, the mine is facing a stern challenge over its environmental protection, the limitation on its structure and function within its subsystem, optimization of its limited manpower, financial and material resources and its sustainable development. Digital mine is come up with to deal with all these problems. The Digital Mine can be liken to “a logistics supply chain”, the basic characteristic is the high-speed network, with broadband and two-way communication system, used as “path map”, which shall make sure the fast delivery of all the data within all the relevant enterprises in the country; It consists of vehicles, which refers to the techniques of Mine CAD, virtual reality, mine simulation, scientific calculation, artificial intelligence, visualization and office automation; goods, which refers to mine data and mind application model; package, which refers to 3DGM(3-Dimensional Geographical Model) and data mining; security system, which refers to the collection and renewal system of mine data; and dispatching system, which refers to MGIS(Mine Geographical Information System), the common carrier of the entire information and office decisions, controlling the use and operation of all vehicles as well as all of the goods production and the package system. The basic structure of the Digital Mine is composed of two parts: digital ground and digital mine. The digital ground is a management information system based on the EPR (Enterprise Resource Planning) and spatial information infrastructure and information system based on 3S technology and computer network. The digital mine regards the mine geology and surveying data as basic information data for spatial positioning, furthermore, inputting other relevant information if necessary, such as mining working-face, excavating working-face, underground chamber, mechanical and electronic equipments, ventilation and safety device, underground pipeline and communication and others, forming a spatial database. Thus, the entire mine’s information system of management and service and decision support system is established. The Digital Mine is a huge systematic project, involving 3S (GIS, GPS, RS), IT (Information technology), mine science, virtual reality technology and visualization technology. Based on computers and network communication, the Digital Mine realizes the digitization of storing, transporting, expressing and applying of all the relevant spatial data and attribute data, including mine construction, exploration, development, mining, environmental protection and control. In addition, it is also a huge artificial intellectual system that integrates digital construction, digital exploration, digital mining, digital environmental protection and digital forecasting based on data dictionary technology, data warehouse technology, WebGIS, virtual reality technology, multimedia technology, CASE technology and artificial intelligence technology.

Data Warehouse Design For Earth Observation Satellites

With the development of Earth observation technology and the growing demand of remote sending data and images, more and more Earth observation satellites are being launched, and more and more data is generated. To take full advantage of all the data, we introduce data warehouse technology to solve this problem. In this paper, we build a layering DW model, give an efficient ETL process for integrating the data and design two types of application program interface (API). The results show that data warehouse is an efficient way to solve mass data of Earth observation satellites.

Application Research of Data Warehouse Technology in Integrated Drilling Engineering Design

In the process of drilling engineering design, in order to meet the needs of different departments and designers of different levels, using data warehouse technique, this paper proposes to build a integrated design system of drilling engineering. Through the establishment of data warehouse system, realize the integrated management and application of geological design, drilling design and real time information of drilling. In the process of collaborative design under network environment, provide a convenient and unified data analysis platform for specialists and designers in different fields. This paper describes the design and implementation of data warehouse system in detail.

Transforming of Construction Contract Administration: Data Warehouse Modeling

Construction stakeholders always use standard form of contract to regulate their contractual obligations and expectations during contract administration process. They need to refer a vast of contract provisions in the process. It always leads misunderstanding and interpretation errors as most of construction practitioners are without a proper legal background. Hence the research aims to apply data warehouse technology to assist end-users for better and/or right decision making. A conceptual model of data warehouse for contract administration is developed and verified by twelve reputed experts in the construction industry. The results show that the data warehouse modeling is feasible and practical to the construction practitioners. It would render a more effective and proactive approach in contract administration towards dispute resolution or prevention.

Construction contract administration in Malaysia using DFD: a conceptual model

PurposeThe purpose of this paper is to propose a conceptual model which is aimed at assisting end‐users, i.e. construction practitioners who are without a proper legal background for effective administration of construction contracts, to enable them to make correct interpretations and decisions in dealing with vast amount of legal information.Design/methodology/approachThis study proposes the application of data warehouse technology in the contract administration process of the construction industry. Upon identification of a comprehensive list of problems associated with construction contracts based on the feedback from 12 reputed experts in the construction industry, a conceptual model is developed using data flow diagram.FindingsThe results show that data warehouse technology is feasible and practical to the construction practitioners in the contract administration process.Research limitations/implicationsThis research focuses only on the development of a conceptual model and thus the practicability aspect of the model is a major concern. As such, the resulting practical implications are limited and are constrained only to the construction industry in Malaysia, raising the question of generalizability of the proposed model, as well as across different industries and countries.Practical implicationsIt is posited that the proposed conceptual model, when implemented, would enable construction practitioners to administer construction contracts with better clarity and accuracy, so that interpretation errors and disputes can be mitigated. This will facilitate the development of harmonious working relationships.Originality/valueThe application of data warehouse technology in contract administration is rather new in the construction industry. The conceptual model thus offers a more effective and proactive approach in construction contract administration towards dispute resolution and/or prevention.

A Survey on Data Warehouse Evolution

The data warehouse (DW) technology was developed to integrate heterogeneous information sources for analysis purposes. Information sources are more and more autonomous and they often change their content due to perpetual transactions (data changes) and may change their structure due to continual users' requirements evolving (schema changes). Handling properly all type of changes is a must. In fact, the DW which is considered as the core component of the modern decision support systems has to be update according to different type of evolution of information sources to reflect the real world subject to analysis. The goal of this paper is to propose an overview and a comparative study between different works related to the DW evolution problem.

Multi-dimensional building performance data management for continuous commissioning

Current buildings’ performance assessment tools are deficient in their ability to integrate and process building monitoring data to generate actionable information that can assist in achieving a higher level of building performance. Therefore, this paper addresses this problem by proposing the design and implementation of a multi-dimensional data analysis concept for building monitoring data. Firstly, the development of the multi-dimensional performance data model is described based on data warehouse technology. Secondly, a dedicated graphical user interface is introduced bringing the benefits of the multi-dimensional model to different stakeholders. Finally, the advantages of multi-dimensional performance data management is demonstrated in a real life case study for on-site and e-service performance management.

Applied Study on the Mine Production & Management Decision Support System Based on Data Warehouse

With accumulating data in mine production, integration of the existing separate information systems is of great importance in enhancement of both production management and support decision-making. BIStar, a production & management decision support system base on data warehouse technology was developed as a user-friendly data analysis, display and decision support tool, and was presented with illumination of its main framework and detailed discussion of its certain key points of the subsystem, such as data acquisition system, central database system, access tools. An application example of information analysis conducted by a large mine corporation was also cited for analysis of feasibility & cost-effectiveness.

The present and future land requirements of logistical activities

The dominant logistical activities of storage, freight transport and materials handling require substantial amounts of land. It is estimated, for example, that in 2006 warehousing occupied around 23,500 ha in England and Wales. This paper examines the changing demand for land from the logistics sector. It begins by classifying logistics-related land uses and reviewing available statistics from government sources and property consultants, most of which apply to warehousing. Recent trends in warehouse development are discussed, particularly the centralisation of floorspace in a smaller number of larger distribution centres. Previous attempts to forecast the future land requirements of logistics have assumed a close correlation between warehouse floorspace and economic growth. This paper argues that this relationship is likely to be distorted by several factors over the next few decades. A model is presented which shows the interaction between a range of factors likely to influence future logistics land requirements. These include the off-shoring of manufacturing, the rebalancing of logistical cost trade-offs in an era of higher oil prices and lower inventory costs, modal shift to rail and water, the growth of online retailing, advances in warehouse technology, the reconfiguration of the waste supply chain and the adaptation of logistical systems to the effects of climate change. The main section of the paper examines the possible effects of each of these factors on the amount of land that will be needed to support logistical activities, and its spatial distribution.

Medical Knowledge Discovery and Management

Although the volume of medical information is growing rapidly, the ability to rapidly convert this data into "actionable insights" and new medical knowledge is lagging far behind. The first step in the knowledge discovery process is data management and integration, which logically can be accomplished through the application of data warehouse technologies. A key insight that arises from efforts in biosurveillance and the global scope of military medicine is that information must be integrated over both time (longitudinal health records) and space (spatial localization of health-related events). Once data are compiled and integrated it is essential to encode the semantics and relationships among data elements through the use of ontologies and semantic web technologies to convert data into knowledge. Medical images form a special class of health-related information. Traditionally knowledge has been extracted from images by human observation and encoded via controlled terminologies. This approach is rapidly being replaced by quantitative analyses that more reliably support knowledge extraction. The goals of knowledge discovery are the improvement of both the timeliness and accuracy of medical decision making and the identification of new procedures and therapies.

Managing Very Large Databases and Data Warehousing

Major libraries have large collections and circulation. Managing libraries electronically has resulted in the creation and management of large library databases. The interconnection of libraries and sharing resources across libraries has resulted in the management of very large databases. Most large and/or multinational industries worldwide have exploited such opportunities by applying data warehouse technology to their data repositories to discover knowledge that had helped them to gain competitive advantage through decision making. The same can be done for libraries using the available large databases. This paper identifies the changes that had taken placed in libraries due to technology and how the data warehouse technology could assist them to discover knowledge and improve services. DOI: http://dx.doi.org/10.4038/sllim.v2i1.438 Sri Lankan Journal of Librarianship and Information Management Volume 2, No.1 pp.22-29 The full text of this article is available on the NILIS website.

A digital earth prototype system: DEPS/CAS

Digital Earth is an information expression of the real Earth, and is a new way of understanding the Earth in the twenty-first century. This paper introduces a Digital Earth Prototype System (DEPS) developed at the Chinese Academy of Sciences (CAS) and supported by the Knowledge Innovation Program of the Chinese Academy of Sciences. Discussions are made to the theoretical model and technical framework of the Digital Earth, and its related key technologies on spatial information processing, spatial data warehouse technology, virtual reality technology, high-performance and parallel computing. The DEPS consists of seven sub-systems including the spatial data, metadata, model database, Grid geoscience computing, spatial information database, maps service and virtual reality. Meanwhile, we developed a series of application systems such as the environment monitoring for the Olympic Games 2008 in Beijing, natural disasters evaluation, digital city, digital archeology, Asia regional aerosol and climate change. The DEPS/CAS displayed the application ability and potential of the Digital Earth in three levels: the global, national and regional.

From conceptual models to schemata: An object-process-based data warehouse construction method

Data warehouse modeling is a complex task, which involves knowledge of business processes of the domain of discourse, understanding the structural and behavioral system's conceptual model, and familiarity with data warehouse technologies. The suitability of current data warehouse modeling methods for large-scale systems is questionable, as they require multiple manual actions to discover measures and relevant dimensional entities and they tend to disregard the system's dynamic aspects. We present an Object-process-based Data Warehouse Construction (ODWC) method that overcomes these limitations of existing methods by utilizing the operational system conceptual model to construct a corresponding data warehouse schema. We specify the ODWC method, apply it on a case study, evaluate it, and compare it to existing methods.

Multiversion join index for multiversion data warehouse

The data warehouse (DW) technology is developed in order to support the integration of external data sources (EDSs) for the purpose of advanced data analysis by On-Line Analytical Processing (OLAP) applications. Since contents and structures of integrated EDSs may evolve in time, the content and schema of a DW must evolve too in order to correctly reflect the evolution of EDSs. In order to manage a DW evolution, we developed the multiversion data warehouse (MVDW) approach. In this approach, different states of a DW are represented by the sequence of persistent DW versions that correspond either to the real world state or to a simulation scenario. Typically, OLAP applications execute star queries that join multiple fact and dimension tables. An important optimization technique for this kind of queries is based on join indexes. Since in the MVDW fact and dimension data are physically distributed among multiple DW versions, standard join indexes need extensions. In this paper we present the concept of a multiversion join index (MVJI) applicable to indexing dimension and fact tables in the MVDW. The MVJI has a two-level structure, where an upper level is used for indexing attributes and a lower level is used for indexing DW versions. The paper also presents the theoretical upper bound (pessimistic) analysis of the MVJI performance characteristic with respect to I/O operations. The analysis is followed by experimental evaluation. It shows that the MVJI increases a system performance for queries addressing multiple DW versions with exact match and range predicates.