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Journal articles on the topic 'Data warehouse'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Yang, Peiyuan, Zuwei Shui, Zhou Chen, Baoming Wang, and Han Lei. "Integrated Management of Potential Financial Risks Based on Data Warehouse." Journal of Economic Theory and Business Management 1, no. 2 (2024): 64–70. https://doi.org/10.5281/zenodo.10970487.

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A data warehouse is used to manage an enterprise's vast data sets, providing a storage mechanism to transform data, move data, and present it to end users. This paper introduces the challenges and changes facing the financial industry in the Internet era, and the new needs for data warehouse architecture transformation. The traditional data warehouse architecture has many limitations in the utilization of storage space, computing power and processing of real-time data flow, which is difficult to meet the needs of the rapid development of financial services. Therefore, there is an urgent need f

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Izabela, Rojek. "Data warehouse in production planning." Studies and Materials in Applied Computer Science (ISSN 1689-6300) 11, no. 1 (2020): 8–13. https://doi.org/10.5281/zenodo.4321139.

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The article describes data warehouses in production planning. In particular, the characteristics of production planning and the flow of information and decisions in this planning were discussed. Data warehouses were defined and the architecture of data warehouse systems was presented. As a special case, the possibility of using a data warehouse in production planning in a selected production company was discussed. This article is the first in the introductory cycle to the chosen topic.

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Barahama, A. D., and R. Wardani. "Utilization Extract, Transform, Load For Developing Data Warehouse In Education Using Pentaho Data Integration." Journal of Physics: Conference Series 2111, no. 1 (2021): 012030. http://dx.doi.org/10.1088/1742-6596/2111/1/012030.

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Abstract The utilization of data warehouses in various fields is an absolute necessity. A data warehouse is a database that contains large amounts of data that aims to help organizations, fields, and institutions specifically for decision making. Data warehouses can produce important information in the future. Loading data from various sources and processed through an ETL (Extract, Transform, Load) process that displays data consistently is the basis for creating a data warehouse architecture. The development of a data warehouse in education will provide significant benefits for the progress o

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Vaibhavi, Chide Rajashree Dange* Gauri Darandale Chaitali Dhokane Soham Dhokte Dr. S. D. Mankar. "A Review on Good Warehousing Practices." International Journal of Pharmaceutical Sciences 3, no. 4 (2025): 3014–22. https://doi.org/10.5281/zenodo.15277548.

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Warehouse efficiency is now used by organizations as a strategic weapon or as a center of knowledge.  An efficient warehouse can help a business succeed by promptly meeting consumer needs.  Thus, this study aims to investigate the relationship between warehouse features and warehouse efficiency.  This study examines two aspects of warehouses: their design and how they are used.  This article addresses the vital need to preserve data integrity, accuracy, and dependability in contemporary organizational environments by providing a thorough framework for data quality assurance

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Tan, Jun, and Hai Ming Zhao. "Construction of Data Warehouse Platform in Continual Quality Improvement." Applied Mechanics and Materials 519-520 (February 2014): 13–16. http://dx.doi.org/10.4028/www.scientific.net/amm.519-520.13.

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Aiming at improving product quality continually, we proposed an association rules mining system (ARMS) based on idea of PDCA cycling. Data warehouse is very useful for integrating heterogeneous database. Therefore, this paper designed a data warehouse platform as process data exchange module in ARMS. The role of data warehouse platform module is to integrate XML with enterprise process for realizing process data exchange among departments. In design of data warehosue, this paper chooses three-tier data warehouse structure and snowflake schema for indicating the complex relation between process

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Cravero Leal, Ania, Jose Norberto Mazón, and Juan Trujillo. "A business-oriented approach to data warehouse development." Ingeniería e Investigación 33, no. 1 (2013): 59–65. http://dx.doi.org/10.15446/ing.investig.v33n1.37668.

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Several surveys have indicated that many data warehouses fail to meet business objectives or are outright failures. One reason for this is that requirement engineering is typically overlooked in real projects. This paper addresses data warehouse design from a business perspective by highlighting business strategy analysis, alignment between data warehouse objectives and a firm's strategy, goal-oriented information requirements' modelling and how an underlying multidimensional data warehouse model may be derived. A set of guidelines is provided allowing developers to design a data warehouse ali

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Yang, Xiu Fang. "Key Technologies Analysis on Management System Data Warehouse." Applied Mechanics and Materials 644-650 (September 2014): 2925–28. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.2925.

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In order to further analyze data warehouse’s application value in teaching management system, this paper first analyzes the disadvantages of previous teaching management system data extraction, illustrates the basic structure of data warehouse system, then discusses the establishment of three kinds of models of data warehouse, finally from the demand perspective of teaching management system, analyzes key technologies such as the design of data warehouse model of teaching management system, the upload of teaching data, data display and data warehouse interfaces.

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Li, Hanzhe, Xiangxiang Wang, Yuan Feng, Yaqian Qi, and Jingxiao Tian. "Integration Methods and Advantages of Machine Learning with Cloud Data Warehouses." International Journal of Computer Science and Information Technology 2, no. 1 (2024): 348–58. http://dx.doi.org/10.62051/ijcsit.v2n1.36.

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A data warehouse is a subject-oriented, integrated, relatively stable collection of data that reflects historical changes and is used to support management decisions. Common tools for building a data warehouse are IBM Cognos and SAP BO. However, both of the above use centralized single-node mode to build data warehouses. This type of data warehouse has poor scalability, and due to the rapid increase in the scale of the Internet, traditional data warehouses can no longer meet the actual needs of use. This paper mainly introduces the integration of cloud data warehouse and machine learning as we

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Spruit, Marco, and Catalina Sacu. "DWCMM: The Data Warehouse Capability Maturity Model." JUCS - Journal of Universal Computer Science 21, no. (11) (2015): 1508–34. https://doi.org/10.3217/jucs-021-11-1508.

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Data Warehouses and Business Intelligence have become popular fields of research in recent years. Unfortunately, in daily practice many Data Warehouse and Business Intelligence solutions still fail to help organizations make better decisions and increase their profitability, due to intransparent complexities and project interdependencies. In addition, emerging application domains such as Mobile Learning & Analytics heavily depend on a well-structured data foundation with a longitudinally prepared architecture. Therefore, this research presents the Data Warehouse Capability Maturity Model (

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Haxhiu, Valdrin. "Decision making based on data analyses using data warehouses." International Journal of Business & Technology 6, no. 3 (2018): 1–6. http://dx.doi.org/10.33107/ijbte.2018.6.3.04.

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Data warehouses are a collection of several databases, whose goal is to help different companies and corporations make important decisions about their activities. These decisions are taken from the analyses that are made to the data within the data warehouse. These data are taken from data that companies and corporations collect on daily basis from their branches that may be located in different cities, regions, states and continents. Data that are entered to data warehouses are historical data and they represent that part of data that is important for making decisions. These data go under a t

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Ghadge, Nagnath G., Vishwanath D. Panchal, and Riyaj Shaikh. "An Examination of Factors Influenced in the Quality Checking of Data in a Data Warehoused." International Journal of Trend in Scientific Research and Development 2, no. 1 (2017): 1509–17. https://doi.org/10.31142/ijtsrd8213.

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Data quality checking in a data warehouse is a key success factor for each Business Intelligence project. In fact, it has a direct impact on taken decisions. If the Data quality checking is good enough for decision makers, the decision support system is very helpful for them. It allows them to have the right inputs to take the right decisions wherever and whenever they need them. But when the data warehouse is of poor Data quality checking, it can have serious impacts on taken decisions that may be even disastrous. Considering this importance of Data quality checking in data warehouse, we aim

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Hamad, Murtadha M., and Muhammed Abdul Raheem. "EVALUATION OF BITMAP INDEX USING PROTOTYPE DATA WAREHOUSE." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 2, no. 2 (2012): 39–42. http://dx.doi.org/10.24297/ijct.v2i1.2614.

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Bitmap indices have become popular access methods for data warehouse applications and decision support systems with large amounts of read-mostly data. This paper could arrive a number of results such as ; Bitmap Index highly improves the performance of Query Answering in Data Warehouses, It highly increases the efficiency of Complex Query processing through using bitwise operations (AND, OR). A prototype of Data Warehouse â€œSTUDENTS DWâ€ has been built according to the conditions of W. Inomn of Data Warehouses. This prototype is built for student's information.

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Rostek, Katarzyna. "Data Analytical Processing in Data Warehouses." Foundations of Management 2, no. 1 (2010): 99–116. http://dx.doi.org/10.2478/v10238-012-0023-x.

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Data Analytical Processing in Data Warehouses The article presents issues connected with processing information from data warehouses (the analytical enterprise databases) and two basic types of analytical data processing in data warehouse. The genesis, main definitions, scope of application and real examples from business implementations will be described for each type of analysis. There will be presented copyrighted method of knowledge discovering in databases, together with practical guidelines for its proper and effective use in the enterprise.

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Islam, Md Rakibul, Syed Mithun Ali, Amir Mohammad Fathollahi-Fard, and Golam Kabir. "A novel particle swarm optimization-based grey model for the prediction of warehouse performance." Journal of Computational Design and Engineering 8, no. 2 (2021): 705–27. http://dx.doi.org/10.1093/jcde/qwab009.

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Abstract Warehouses constitute a key component of supply chain networks. An improvement to the operational efficiency and the productivity of warehouses is crucial for supply chain practitioners and industrial managers. Overall warehouse efficiency largely depends on synergic performance. The managers preemptively estimate the overall warehouse performance (OWP), which requires an accurate prediction of a warehouse’s key performance indicators (KPIs). This research aims to predict the KPIs of a ready-made garment (RMG) warehouse in Bangladesh with a low forecasting error in order to precisely

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M Kirmani, Mudasir. "Dimensional Modeling Using Star Schema for Data Warehouse Creation." Oriental journal of computer science and technology 10, no. 04 (2017): 745–54. http://dx.doi.org/10.13005/ojcst/10.04.07.

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Data Warehouse design requires a radical rebuilding of tremendous measures of information, frequently of questionable or conflicting quality, drawn from various heterogeneous sources. Data Warehouse configuration assimilates business learning and innovation know-how. The outline of theData Warehouse requires a profound comprehension of the business forms in detail. The principle point of this exploration paper is to contemplate and investigate the transformation model to change over the E-R outlines to Star Schema for developing Data Warehouses. The Dimensional modelling is a logical design te

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Phyllis, Chepkonga. "Determination of Performance Indicators for Warehouse Evaluation: A Case of Medium Sized Warehouses in Nakuru Town." Journal of Procurement & Supply Chain 5, no. 2 (2021): 32–38. http://dx.doi.org/10.53819/81018102t5034.

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Evaluation of warehouse processes is required for decision making purposes and the improvement of warehouse operations. To evaluate warehouse processes, it is essential to identify key indicators in the warehouse operations. This research was intended to identify the significant indicators of warehouse performance that would support management decision making on the improvement of warehouse operations. In this research 20 indicators were identified in four warehouse activities based on Frazelle model. The most important indicators in each warehouse were then determined. The study was conducted

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Gluchowski, Peter. "Data Warehouse." Informatik-Spektrum 20, no. 1 (1997): 48–49. http://dx.doi.org/10.1007/s002870050052.

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Nazila Ragimova, Irada Seyidova, Nazila Ragimova, Irada Seyidova, and Jala Jamalova Jala Jamalova. "BUILDING DATA WAREHOUSING FOR MACHINE LEARNING AND CLIENT SCORING." ETM - Equipment, Technologies, Materials 23, no. 05 (2024): 90–97. http://dx.doi.org/10.36962/etm23052024-10.

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In modern business, data is a critical resource that can significantly increase the company's competitiveness. One of the key tasks associated with data is the creation of data warehouses that provide effective storage, processing and analysis of information. In particular, structured data warehouses play a critical role in the development of machine learning and customer scoring systems. In this article, we will look at the stages of building data warehouses, integrating them with machine learning systems, and the importance of structured data for customer scoring. At the end of the article,

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Dehdouh, Khaled, Omar Boussaid, and Fadila Bentayeb. "Big Data Warehouse." International Journal of Decision Support System Technology 12, no. 1 (2020): 1–24. http://dx.doi.org/10.4018/ijdsst.2020010101.

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In the Big Data warehouse context, a column-oriented NoSQL database system is considered as the storage model which is highly adapted to data warehouses and online analysis. Indeed, the use of NoSQL models allows data scalability easily and the columnar store is suitable for storing and managing massive data, especially for decisional queries. However, the column-oriented NoSQL DBMS do not offer online analysis operators (OLAP). To build OLAP cubes corresponding to the analysis contexts, the most common way is to integrate other software such as HIVE or Kylin which has a CUBE operator to build

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Tiwari, Rajdev, Anubhav Tiwari, and Manu Pratap Singh. "Fuzzy-Rule Based Adaptive Data Warehouse." International Journal of Applied Evolutionary Computation 3, no. 1 (2012): 47–65. http://dx.doi.org/10.4018/jaec.2012010103.

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Data Warehouses (DWs) are aimed to empower the knowledge workers with information and knowledge which helps them in decision making. Technically, the DW is a large reservoir of integrated data that does not provide the intelligence or the knowledge demanded by users. The burden of data analysis and extraction of information and knowledge from integrated data still lies upon the analyst’s shoulder. The overhead of analysts can be taken off by architecting a new generation data warehouses systems those shall be capable of capturing, organizing and representing knowledge along with the data and i

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Boyko, N. I., and A. V. Chernenko. "Modern approaches to data storage: comparison of relational and cloud data warehouses using etl and elt methods." Reporter of the Priazovskyi State Technical University. Section: Technical sciences, no. 48 (June 27, 2024): 7–19. http://dx.doi.org/10.31498/2225-6733.48.2024.310669.

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The paper analyses various aspects of the use of relational and cloud data warehouses as well as methods of integrating ETL and ELT data. A comparative analysis of these approaches, their advantages and disadvantages are provided. A central relational data warehouse is proposed that provides a single version of truth (SVOT), which allows standardising and structuring data, avoiding differences and providing the access to the same information for all users of an organisation. It is analysed the methodological approaches to implementing a data warehouse: top-down, bottom-up, and from middle. It

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Shabina, Kausar* Prof. Kalpana Malpe. "AN IMPLEMENTATION OF “DECISION MAKER FOR EDUCATIONAL DOMAIN." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 5 (2016): 408–12. https://doi.org/10.5281/zenodo.51445.

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Utilizing a decision support system is a proactive way to use data to manage, operate, and evaluate educational institute in a better way. Depending on the quality and availability of the underlying data, such a system could address a wide range of problems by distilling data from any combination of education records maintenance system. The data mining from data warehouse can be a ready and effective system for the decision makers. Data-driven decision support systems, such as data warehouses can serve the requirement of extraction of information from more than one subject area. Data warehouse

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Uddin, Badie, Suryani Suryani, Ai Selpia Andita, and Anggi Puspita Sari. "Perancangan dan Implementasi Data Warehouse – A Systematic Literature Review (SLR)." Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) 7, no. 5 (2024): 1095–99. https://doi.org/10.32672/jnkti.v7i5.7971.

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Abstrak - Data warehouse berguna untuk analisis mendalam dan memperoleh informasi lebih akurat ketika pengambilan keputusan. Penelitian perancangan dan implementasi data warehouse meningkatkan proses pengambilan keputusan sebagai integrasi data dari berbagai sumber, memungkinkan analisis data lebih cepat dan akurat. Studi literatur ini mengulas berbagai pendekatan dalam perancangan dan implementasi data warehouse di berbagai bidang, termasuk penjualan produk tour, perpustakaan universitas, akademik perguruan tinggi, dan analisis kinerja perusahaan. Hasil tinjauan menunjukkan bahwa penerapan me

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Atay, Canan Eren, and Georgia Garani. "Maintaining Dimension's History in Data Warehouses Effectively." International Journal of Data Warehousing and Mining 15, no. 3 (2019): 46–62. http://dx.doi.org/10.4018/ijdwm.2019070103.

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A data warehouse is considered a key aspect of success for any decision support system. Research on temporal databases have produced important results in this field, and data warehouses, which store historical data, can clearly benefit from such studies. A slowly changing dimension is a dimension in which any of its attributes in a data warehouse can change infrequently over time. Although different solutions have been proposed, each has its own particular disadvantages. The authors propose the Object-Relational Temporal Data Warehouse (O-RTDW) model for the slowly changing dimensions in this

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YAO, CAN-ZHONG, JI-NAN LIN, and XU-ZHOU ZHENG. "MULTIFRACTAL DETRENDED CROSS-CORRELATION ANALYSIS FOR LARGE-SCALE WAREHOUSE-OUT BEHAVIORS." Fractals 23, no. 04 (2015): 1550044. http://dx.doi.org/10.1142/s0218348x15500449.

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Based on cross-correlation algorithm, we analyze the correlation property of warehouse-out quantity of different warehouses, respectively, and different products of each warehouse. Our study identifies that significant cross-correlation relationship for warehouse-out quantity exists among different warehouses and different products of a warehouse. Further, we take multifractal detrended cross-correlation analysis for warehouse-out quantity among different warehouses and different products of a warehouse. The results show that for the warehouse-out behaviors of total amount, different warehouse

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Mrđa, Bojan, and Dragan Soleša. "Data Warehouse and its tools." Ekonomija: teorija i praksa 16, no. 3 (2023): 71–89. http://dx.doi.org/10.5937/etp2303071m.

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As the battle for every and even the smallest piece of the pile on the market is great, a growing number of companies are finding solutions to improve their business as much as possible. One of the solutions is Data Warehouse and OLAP, that is, their tools, which gives managers or users the ability to access, with minimal effort, the very important data that is important to them for the business. This paper presents data analysis on concrete examples of the Belgrade Academy, where the mentioned tools were used with the aim of improving the quality of teaching.

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Wen, Wei Jun. "Research on the Incremental Updating Mechanism of Marine Environmental Data Warehouse." Applied Mechanics and Materials 668-669 (October 2014): 1378–81. http://dx.doi.org/10.4028/www.scientific.net/amm.668-669.1378.

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Marine environment data warehouse can store massive data. After the full amount of historical data has been initially loaded, the incremental update mode must be applied to ensure timely updates of data. In this paper, in view of the marine environment data warehouse’s characteristics, such as massive data amount, large number of historical data and low update frequency, a complete set of mechanisms for incremental update of marine environment data warehouse was proposed to greatly improve the operating efficiency of marine environment data warehouse.

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Aljuwaiber, Abobakr. "Data Warehousing as Knowledge Pool : A Vital Component of Business Intelligence." International Journal of Computer Science, Engineering and Information Technology 12, no. 4 (2022): 21–26. http://dx.doi.org/10.5121/ijcseit.2022.12402.

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Increasing amounts of information and diverse formats have forced organizations to create large data repositories in response to the information explosion in the 21st century. As a result, the model of a data warehouse has been introduced to define a large data repository. The purpose of this article is to describe the principles of data warehousing in business and how it can enhance the generation of new knowledge throughout the organization. Definitions of data warehousing are considered and include methods of its use, namely query and data simulation. The steps required prior to transformin

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Mujiono, Mujiono, and Aina Musdholifah. "Pengembangan Data Warehouse Menggunakan Pendekatan Data-Driven untuk Membantu Pengelolaan SDM." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 10, no. 1 (2016): 1. http://dx.doi.org/10.22146/ijccs.11184.

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The basis of bureaucratic reform is the reform of human resources management. One supporting factor is the development of an employee database. To support the management of human resources required including data warehouse and business intelligent tools. The data warehouse is an integrated concept of reliable data storage to provide support to all the needs of the data analysis. In this study developed a data warehouse using the data-driven approach to the source data comes from SIMPEG, SAPK and electronic presence. Data warehouses are designed using the nine steps methodology and unified mode

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Wiwik, Budiawan, Singgih Saptadi, and Ary Arvianto. "The Development of Data Warehouse to Support Data Mining Technique for Traffic Accident Prediction." E3S Web of Conferences 73 (2018): 12007. http://dx.doi.org/10.1051/e3sconf/20187312007.

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Traffic accidents are one of the major health problems that cause serious death in the world and ranks 9th in the world. Traffic accidents in Indonesia ranks 5th in the world. One effort to improve traffic safety is to design traffic accident prediction models. Prediction models will utilize accident-related data in traffic through data mining processing. The data warehouse offers benefits as a basis for data mining. Building an effective data warehouse requires knowledge and attention to key issues in database design, data acquisition and processing, as well as data access and security. This

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Arif, Bramantoro. "Data Cleaning Service for Data Warehouse: An Experimental Comparative Study on Local Data." TELKOMNIKA Telecommunication, Computing, Electronics and Control 16, no. 2 (2018): 834–42. https://doi.org/10.12928/telkomnika.v16.i2.7669.

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Data warehouse is a collective entity of data from various data sources. Data are prone to several complications and irregularities in data warehouse. Data cleaning service is non trivial activity to ensure data quality. Data cleaning service involves identification of errors, removing them and improve the quality of data. One of the common methods is duplicate elimination. This research focuses on the service of duplicate elimination on local data. It initially surveys data quality focusing on quality problems, cleaning methodology, involved stages and services within data warehouse environme

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Aufaure, Marie-Aude, Alfredo Cuzzocrea, Cécile Favre, Patrick Marcel, and Rokia Missaoui. "An Envisioned Approach for Modeling and Supporting User-Centric Query Activities on Data Warehouses." International Journal of Data Warehousing and Mining 9, no. 2 (2013): 89–109. http://dx.doi.org/10.4018/jdwm.2013040105.

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In this vision paper, the authors discuss models and techniques for integrating, processing and querying data, information and knowledge within data warehouses in a user-centric manner. The user-centric emphasis allows us to achieve a number of clear advantages with respect to classical data warehouse architectures, whose most relevant ones are the following: (i) a unified and meaningful representation of multidimensional data and knowledge patterns throughout the data warehouse layers (i.e., loading, storage, metadata, etc); (ii) advanced query mechanisms and guidance that are capable of extr

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Shobirin, Kheri Arionadi, Adi Panca Saputra Iskandar, and Ida Bagus Alit Swamardika. "Data Warehouse Schemas using Multidimensional Data Model for Retail." International Journal of Engineering and Emerging Technology 2, no. 1 (2017): 84. http://dx.doi.org/10.24843/ijeet.2017.v02.i01.p17.

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A data warehouse are central repositories of integrated data from one or more disparate sources from operational data in On-Line Transaction Processing (OLTP) system to use in decision making strategy and business intelligent using On-Line Analytical Processing (OLAP) techniques. Data warehouses support OLAP applications by storing and maintaining data in multidimensional format. Multidimensional data models as an integral part of OLAP designed to solve complex query analysis in real time.

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Sari, Devi Julisca, Siska Kurnia Gusti, Elin Haerani, and Fadhilah Syafria. "DESAIN ARSITEKTUR DATA WAREHOUSE PADA DATA TRANSAKSI PENJUALAN ROTTE BAKERY." Jurnal Teknik Informasi dan Komputer (Tekinkom) 5, no. 2 (2022): 253. http://dx.doi.org/10.37600/tekinkom.v5i2.605.

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The increasingly fierce competition between competitors requires companies to be able to compete and maintain their existence in order to continue to grow, for that utilizing information technology such as data warehouses will play a large enough role, because optimal data processing will produce quality information in supporting companies to take appropriate policies. as well as increasing the productivity and effectiveness of the company's performance. The application of the data warehouse can be started by making an architectural design that will be made, for that the researcher aims to pro

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Saketh Reddy Cheruku, Pandi Kirupa Gopalakrishna Pandian, and Prof.(Dr.) Punit Goel. "Implementing Agile Methodologies in Data Warehouse Projects." International Journal for Research Publication and Seminar 15, no. 3 (2024): 306–17. http://dx.doi.org/10.36676/jrps.v15.i3.1498.

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Agile techniques have transformed project management and software development by stressing flexibility, collaboration, and customer-centricity. Data warehouse initiatives have traditionally used a waterfall methodology, which may delay, cost more, and misalign with business needs. Agile techniques are applied to data warehouse projects in this article, examining their pros and cons. The study starts with Agile fundamentals including iterative development, incremental delivery, and adaptive planning. It compares these concepts with the linear, sequential waterfall approach employed in data ware

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Saketh Reddy Cheruku, Pandi Kirupa Gopalakrishna Pandian, and Dr. Punit Goel. "Implementing Agile Methodologies in Data Warehouse Projects." Darpan International Research Analysis 12, no. 1 (2024): 65–79. http://dx.doi.org/10.36676/dira.v12.i1.75.

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Agile techniques have transformed project management and software development by stressing flexibility, collaboration, and customer-centricity. Data warehouse initiatives have traditionally used a waterfall methodology, which may delay, cost more, and misalign with business needs. Agile techniques are applied to data warehouse projects in this article, examining their pros and cons.The study starts with Agile fundamentals including iterative development, incremental delivery, and adaptive planning. It compares these concepts with the linear, sequential waterfall approach employed in data wareh

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Larutama, Wiku, Dewang Rangga Bentar, Rifqy Oktavian Risdayanto, and Ridwan Salman Alvariedz. "Implementation of Warehouse Management System Planning in Finished Goods Warehouse." Journal of Logistics and Supply Chain 2, no. 2 (2022): 81–90. http://dx.doi.org/10.17509/jlsc.v2i2.62840.

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Warehouses play an important role in the supply chain by serving as a link between producers and end consumers. Warehouses not only serve as a place to store goods, but also have other important functions. Operational efficiency and logistics control in finished goods warehouses are increasingly becoming an urgent need for companies in various industries. However, ineffective warehouse management can lead to negative impacts such as decreased profits and customer dissatisfaction. Therefore, efforts are needed to manage warehouses with good efficiency and structure. This article discusses the c

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Nuzhat, Younis, Aamir Khush Naseeb Rao, and Kausa Uzma. "Warehouse Management System as locomotive of Supply Chain Management: Some Evidences from United Kingdom manufacturing sector." International Journal of Management Sciences and Business Research 2, no. 12 (2013): 01–07. https://doi.org/10.5281/zenodo.3441863.

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This Warehouse management system play an important role in the modern world of technology and using the Information technology enhance the performance and efficiency of warehouse management to manage and handle inventories which lead to proactive management of supply chain management process. In this research paper, we investigate the barrier of warehouse implementation along with failures which are associated with warehouse management system and then we move to study of warehouses to understand the problems they were facing and how they handle those issues using warehouse management system, a

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Mathur, Sonali, Shankar Lal Gupta, and Payal Pahwa. "Enhancing Security in Banking Environment Using Business Intelligence." International Journal of Information Retrieval Research 10, no. 4 (2020): 21–34. http://dx.doi.org/10.4018/ijirr.2020100102.

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Data warehouses are the most valuable assets of an organization and are basically used for critical business and decision-making purposes. Data from different sources is integrated into the data warehouse. Thus, security issues arise as data is moved from one place to another. Data warehouse security addresses the methodologies that can be used to secure the data warehouse by protecting information from being accessed by unauthorized users for maintaining the reliability of the data warehouse. A data warehouse invariably contains information which needs to be considered extremely sensitive and

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Jagan Nalla. "Performance Engineering in Cloud Data Warehouses: A Systematic Approach to Optimization." Journal of Computer Science and Technology Studies 7, no. 5 (2025): 612–20. https://doi.org/10.32996/jcsts.2025.7.5.67.

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Cloud data warehouses have emerged as the cornerstone of modern enterprise analytics infrastructure, yet achieving optimal performance across platforms like Redshift, Snowflake, and Synapse requires specialized knowledge that extends beyond traditional on-premises optimization techniques. This article presents a systematic framework for performance tuning in cloud data warehouse environments, encompassing critical aspects from foundational data modeling principles to advanced query optimization strategies. The interplay between schema design decisions, partitioning schemes, and indexing mechan

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Primasari, Dewi, Khidir Zahid Muchtadiabillah, and Freza Riana. "Application of Fuzzy C Means and TOPSIS in Warehouse Selection at PT Warung Islami Bogor." Jurnal Riset Informatika 5, no. 3 (2023): 311–20. http://dx.doi.org/10.34288/jri.v5i3.517.

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PT Warung Islami Bogor needs a warehouse to store goods that come from suppliers. Currently, the selection of warehouses is still done manually and is subjective. It is feared that this will lead to inaccuracies in renting the warehouse. So an application is needed to assist companies in choosing a warehouse. The fuzzy C-Means method can be used to classify warehouse data based on the characteristics of each group. After obtaining the next group is to make a rating of each group. One method that can be used is the TOPSIS method. The TOPSIS method can be applied to this application to rank the

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Primasari, Dewi, Khidir Zahid Muchtadiabillah, and Freza Riana. "Application of Fuzzy C Means and Topsis in Warehouse Selection at PT. Warung Islami Bogor." Jurnal Riset Informatika 5, no. 3 (2023): 311–20. http://dx.doi.org/10.34288/jri.v5i3.223.

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PT Warung Islami Bogor needs a warehouse to store goods that come from suppliers. Currently, the selection of warehouses is still done manually and is subjective. It is feared that this will lead to inaccuracies in renting the warehouse. So an application is needed to assist companies in choosing a warehouse. The fuzzy C-Means method can be used to classify warehouse data based on the characteristics of each group. After obtaining the next group is to make a rating of each group. One method that can be used is the TOPSIS method. The TOPSIS method can be applied to this application to rank the

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Zein, Kevin, Arum Ambarsari, and Danang Manumono. "Pengadaan Barang di Gudang PT. Bumitama Gunajaya Agro Kecamatan Kota Waringin Barat Barat Kalimantan Tengah." AGRIFITIA : Journal of Agribusiness Plantation 3, no. 2 (2023): 82–86. http://dx.doi.org/10.55180/aft.v3i2.493.

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This research aims to determine the procedures for procurement of goods in warehouses related to company operations. This research uses a basic qualitative descriptive method, a location determination method using a purposive method and was carried out at PT. Bumitama Gunajaya Agro (BGA). Data obtained from interviews with the Head of Warehouse, Warehouse Mador and KTU. The results obtained from this research are that the procurement of goods in warehouses has been implemented by PT. Bumitama Gunajaya Agro has used procurement procedures from planning to control, but there is still a need for

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Atigui, Faten, Franck Ravat, Jiefu Song, Olivier Teste, and Gilles Zurfluh. "Facilitate Effective Decision-Making by Warehousing Reduced Data." International Journal of Decision Support System Technology 7, no. 3 (2015): 36–64. http://dx.doi.org/10.4018/ijdsst.2015070103.

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The authors' aim is to provide a solution for multidimensional data warehouse's reduction based on analysts' needs which will specify aggregated schema applicable over a period of time as well as retain only useful data for decision support. Firstly, they describe a conceptual modeling for multidimensional data warehouse. A multidimensional data warehouse's schema is composed of a set of states. Each state is defined as a star schema composed of one fact and its related dimensions. The derivation between states is carried out through combination of reduction operators. Secondly, they present a

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Rabuzin, Kornelije. "Deductive Data Warehouses." International Journal of Data Warehousing and Mining 10, no. 1 (2014): 16–31. http://dx.doi.org/10.4018/ijdwm.2014010102.

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This paper presents the idea of deductive data warehouses. Deductive data warehouses rely on deductive databases but instead of a database in the background a data warehouse is used. The authors show how Datalog (as a logic programming language) can be used to perform OLAP analysis on data. Since data warehouses don't use all the technologies that databases do (locking, transactions, integrity constraints, etc., which are not relevant in this context), some things are different and simpler then when working with deductive databases. The authors demonstrate the idea on an example and the author

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Pinet, François. "Brief Report on the Advanced Use of Prolog for Data Warehouses." Applied Sciences 12, no. 21 (2022): 11223. http://dx.doi.org/10.3390/app122111223.

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Data warehouses have demonstrated their applicability in numerous application fields such as agriculture, the environment and health. This paper proposes a general framework for defining a data warehouse and its aggregations using logic programming. The objective is to show that data managers can easily express, in Prolog, traditional data warehouse queries and combine data aggregation operations with other advanced Prolog features. It is shown that this language provides advanced features to aggregate information in an in-memory database. This paper targets data managers; it shows them the di

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Alasta, Amro F., and Muftah A. Enaba. "The Impact of Using Data Warehouse on Manpower Employment Decision Support System." Advanced Materials Research 383-390 (November 2011): 4653–59. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.4653.

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Since the use of computers in business world, data collection has become one of the most important issues due to the available knowledge in the data; such data has been stored in database. Database system was developed which led to the evolvement of hierarchical and relational database followed by Standard Query Language (SQL). As data size increases, the need for more control and information retrieval increase. These increases lead to the development of data mining systems and data warehouses. This paper focuses on the use of data warehouse as a supporting tool in decision making. We to study

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Viti, Francesco, Serge P. Hoogendoorn, Lambertus H. (Ben) Immers, Chris M. J. Tampère, and Sascha Hoogendoorn Lanser. "National Data Warehouse." Transportation Research Record: Journal of the Transportation Research Board 2049, no. 1 (2008): 176–85. http://dx.doi.org/10.3141/2049-21.

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Golfarelli, Matteo, and Stefano Rizzi. "Data Warehouse Testing." International Journal of Data Warehousing and Mining 7, no. 2 (2011): 26–43. http://dx.doi.org/10.4018/jdwm.2011040102.

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Testing is an essential part of the design life-cycle of a software product. Although most phases of data warehouse design have received considerable attention in the literature, not much research has been conducted concerning data warehouse testing. In this paper, the authors introduce a number of data mart-specific testing activities, classify them in terms of what is tested and how it is tested, and show how they can be framed within a reference design method to devise a comprehensive and scalable approach. Finally, the authors discuss some practical evidences emerging from a real case stud

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Sakka, Amir, Sandro Bimonte, Francois Pinet, and Lucile Sautot. "Volunteer Data Warehouse." International Journal of Data Warehousing and Mining 17, no. 3 (2021): 1–21. http://dx.doi.org/10.4018/ijdwm.2021070101.

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With the maturity of crowdsourcing systems, new analysis possibilities appear where volunteers play a crucial role by bringing the implicit knowledge issued from practical and daily experience. At the same time, data warehouse and OLAP systems represent the first citizen of decision-support systems. They allow analyzing a huge volume of data according to the multidimensional model. The more the multidimensional model reflects the decision-makers' analysis needs, the more the DW project is successful. However, when volunteers are involved in the design of DWs, existing DW design methodologies p

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