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Journal articles on the topic 'OLAP technology'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 August 2024

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1

Sun, Lei, Hong Mei Xing, and Wei Wang. "Basic Technology of OLAP." Advanced Materials Research 1030-1032 (September 2014): 1892–95. http://dx.doi.org/10.4028/www.scientific.net/amr.1030-1032.1892.

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s.The technology and principle involved in the on-line analytical processing is presented in theory, such as an overview of the on-line analytical technology, the operation of the on-line analytical technology, etc, which sets a technological foundation to build a system to realize online analysis.

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Bhardwaj, Vinayak, and Rincy Jacob. "Data Warehousing and OLAP Technology." Journal of Advance Research in Computer Science & Engineering (ISSN: 2456-3552) 1, no. 3 (March 31, 2014): 05–11. http://dx.doi.org/10.53555/nncse.v1i3.521.

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Data warehousing and Online Analytical Processing (OLAP) are essential elements of decision support, which has increasingly become a focus of the database industry. Data warehouse provides an effective way for the analysis and tatic to the mass data and helps to do the decision making. Many commercial products and services are now available and all of the principal database management system vendors now have offering in these areas. The paper introduces the data warehouse and online analysis process with an accent on their new requirements.

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3

Akushko, D. V. "OLAP TECHNOLOGY AS DECISION-MAKING SUPPORT TOOL." Litiyo i Metallurgiya (FOUNDRY PRODUCTION AND METALLURGY), no. 2 (July 4, 2017): 51–53. http://dx.doi.org/10.21122/1683-6065-2017-2-51-53.

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The present article discloses the basic principles of work with OLAP technologies, shows key features in comparison with traditional systems of the reporting. The simplified structure of an OLAP cube for the analysis of cost of products of the steelsmelting shop is considered.

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4

Jaroli, Priyanka, and Palak Masson. "Data Warehousing and OLAP Technology (Data warehousing)." International Journal of Engineering Trends and Technology 51, no. 1 (September 25, 2017): 45–50. http://dx.doi.org/10.14445/22315381/ijett-v51p208.

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5

Guo, Jun, De Qing Gan, Jing Tan, and Xu Long Yao. "Based on OLAP Realize Real-Time Integrated Analysis of the Underground Metal Mines Cost Information." Applied Mechanics and Materials 214 (November 2012): 809–13. http://dx.doi.org/10.4028/www.scientific.net/amm.214.809.

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Through OLAP technology study and solve the data issues during the real-time integrated of cost information process. Using OLAP technology does classified and sequenced analyses on mines production cost multi-dimensionally and multi-angle computationally. It is carried the deep study that the application of OLAP theory and technology in underground metal mines cost analysis field, and meanwhile the relative OLAP modeling is put forward.

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Le, Hien Thi Kim, Lien Bich Nguyen, and Phuc Do. "Applying OLAP technology to support decision making in sales process." Science and Technology Development Journal 19, no. 2 (June 30, 2016): 41–57. http://dx.doi.org/10.32508/stdj.v19i2.727.

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OLAP (Online Analytical Processing) is a technology that enables the user to easily and selectively extract and view data from different points of view. It is also an important part of the decision system. This study proposes the decisions in fulfillment process which could be supported by the OLAP technology, including the quality of sales, the main product of the company, the salary and the bonus for sales staff, the credit limit and the price policy for the customer. Furthermore, this research also demonstrates the application of the OLAP technology in the decision making for the main product of A manufacturing and distributing company.

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Sharma, Pitambar, and Piyush Girdhar. "Online Analytical Processing (OLAP)." Journal of Advance Research in Computer Science & Engineering (ISSN: 2456-3552) 1, no. 3 (March 31, 2014): 01–04. http://dx.doi.org/10.53555/nncse.v1i3.520.

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This paper is basically accustomed define On-Line Analytical method (OLAP), WHO uses it and why, and to review the key choices required for OLAP code. On-Line Analytical method (OLAP) could also be a category of code technology that allows analysts, managers and executives to appreciate insight into info through fast, consistent, interactive access to an honest reasonably gettable views of {data of information} that has been transformed from data to mirror spatiality of the enterprise as understood by the user. whereas OLAP systems have the ability to answer "who?" and "what?" queries, it's their ability to answer "what if?" and "why?" that sets them except info Warehouses. OLAP applications span a variety of structure functions. Finance departments use OLAP for applications like budgeting, activity-based accountancy (allocations), cash performance analysis, and cash modelling. Sales analysis and prognostication square measure a pair of the OLAP applications found in sales departments. Among totally different applications, promoting departments use OLAP for analysis, sales prognostication, promotions analysis, consumer analysis, and market/customer segmentation. Typical manufacturing OLAP applications embody production coming up with and defect analysis. Although OLAP applications square measure found in wide divergent sensible areas, all of them want the following key choices like 3-D views of information, Calculation –intensive capabilities and Time Intelligence.

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Chaudhuri, Surajit, and Umeshwar Dayal. "An overview of data warehousing and OLAP technology." ACM SIGMOD Record 26, no. 1 (March 1997): 65–74. http://dx.doi.org/10.1145/248603.248616.

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Nabibayova, G. Ch. "Application of OLAP Technology in the Environment of Electronic Demography." Informacionnye Tehnologii 27, no. 10 (October 8, 2021): 542–49. http://dx.doi.org/10.17587/it.27.542-549.

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The article proposes an approach to the development of an electronic demographic decision support system using technologies of Data Warehouse (DW) and Interactive Analytical Processing OLAP. This makes it possible to conduct high-level demographic research and provide support to decision-makers in demographic sphere. The article notes that demography is an interdisciplinary field of research and is defined as a complex science. Each industry of demography has many indicators. A sample list of these indicators is presented. The main characteristics of the DW, which should be taken into account when developing its architecture, are stated. Among these characteristics, one can find the main defining characteristics of Big Data — volume, velocity, variety, veracity, variability, visualization, value etc. For a more rational and efficient use of a large amount of information, taking into account its constant increase, to ensure the speed of execution of requests for a given system, it is proposed to use a Bus of Interconnected Data Marts (DM) as an architecture of DW. One of the advantages of using DM is that their use assumes distributed parallel data processing. This architecture allows for much faster results generation. It is based on the MapReduce distributed computing model and the Hadoop project. In addition, to effectively use large amounts of data, it is also proposed to use OLAP operations such as roll-up and drill-down, as well as fuzzy set theory, based on the technique of computing with words. The article also shows the practical application of interconnected DM. An OLAP cube is built on the basis of these DM. OLAP operations provide the ability to view cubes in different slices and provide aggregate data.

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Errattahi, Rahhal, Mohammed Fakir, and Fatima Zahra Salmam. "Explanation in OLAP Data Cubes." Journal of Information Technology Research 7, no. 4 (October 2014): 63–78. http://dx.doi.org/10.4018/jitr.2014100105.

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OLAP is an important technology that offers a fast and interactive data navigation, it also provides tools to explore data cubes in order to extract interesting information from a multidimensional data structures. However, the OLAP exploration is done manually, without tools that could automatically extract relevant information from the cube. In addition OLAP is not capable of explaining relationships that could exist within data. This paper presents a new approach to coupling between data mining and online analytical processing. Its approach provides the explanation in OLAP data cubes by using the association rules between the inter-dimensional predicates. The mining process could be done by one of the two algorithms, Apriori and Fp-Growth, in which aggregate measures to calculate support and confidence are exploited. It also evaluates the interestingness of mined association rules according to the Lift criteria.

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Mansmann, Svetlana, and Marc H. Scholl. "Empowering the OLAP Technology to Support Complex Dimension Hierarchies." International Journal of Data Warehousing and Mining 3, no. 4 (October 2007): 31–50. http://dx.doi.org/10.4018/jdwm.2007100102.

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Tao, Jun, and Jiao Liang Yu. "Study on E-Government and its Decision Support System." Applied Mechanics and Materials 635-637 (September 2014): 1738–41. http://dx.doi.org/10.4028/www.scientific.net/amm.635-637.1738.

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Based on the analysis of E-government decision support system's basic theory and mainstream solutions, combined with the popular OLAP technology, presents a white spoon OLAP based decision support system to improve e-government program, using data warehouse and model library together to support OLAP analysis, test cases and successfully used with the project, the results show that this scheme can achieve the desired requirements, with better performance and fast response performance multidimensional analysis, OLAP operations can be completed with reference promotional value.

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Prado, Alysson Bolognesi, Carmen Freitas, and Thiago Ricardo Sbrici. "Using OLAP Tools for e-HRM." International Journal of Technology and Human Interaction 6, no. 4 (October 2010): 49–62. http://dx.doi.org/10.4018/jthi.2010100104.

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In the growing challenge of managing people, Human Resources need effective artifacts to support decision making. On Line Analytical Processing is intended to make business information available for managers, and HR departments can now encompass this technology. This paper describes a project in which the authors built a Data Warehouse containing actual Human Resource data. This paper provides data models and shows their use through OLAP software and their presentation to end-users using a web portal. The authors also discuss the progress, and some obstacles of the project, from the IT staff’s viewpoint.

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Jin, Jennifer, and Masahiro Hayakawa. "Network analysis and GOLAP." Encyclopedia with Semantic Computing and Robotic Intelligence 02, no. 02 (November 14, 2018): 1850016. http://dx.doi.org/10.1142/s2529737618500168.

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Online Analytical Processing (OLAP) is an effective approach to analyzing various complex business problems, and graph is considered as a common scheme to represent the business datasets. Network analysis is a broad analytics scheme for exploring the connectivity and deriving useful analytics results. However, network analysis for graph-based OLAP presents a set of more specific analytics methods by utilizing graph model, network property, and OLAP principles. In this paper, we present a comprehensive survey on network analysis conducted on graph model for the purpose of OLAP, and we summarize the current research focus, paradigms, and the future needs on the target technology.

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Cristescu, Marian Pompiliu. "Using OLAP Data Cubes in Business Intelligence." Scientific Bulletin 21, no. 2 (December 1, 2016): 80–86. http://dx.doi.org/10.1515/bsaft-2016-0039.

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Abstract The purpose of this paper is to demonstrate that it is possible to develop business intelligence projects in big and medium-size organizations, only with Microsoft products, used in accordance with standard OLAP cube technology, and presented possible alternatives, in relation with the requested functions.

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16

Wang, Chunfeng. "Optimization Research of the OLAP Query Technology Based on P2P." TELKOMNIKA (Telecommunication Computing Electronics and Control) 12, no. 4 (November 1, 2014): 1039. http://dx.doi.org/10.12928/telkomnika.v12i4.436.

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17

Nabibayova, Gulnara. "Expanding the intellectual capabilities of OLAP technology using neural networks." Problems of Information Society 15, no. 2 (July 2, 2024): 43–48. http://dx.doi.org/10.25045/jpis.v15.i2.05.

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The article highlights the main characteristics, features and structure of Online Analytical Processing systems based on the same technology that perform online analytical processing of data. This technology allows analysts to explore and navigate a multidimensional indicator structure called an online analytical processing cube (data cube). Indicators (measures) of data cube play an important role in the decision-making process. To solve certain problems, these measures often need to be classified or grouped. Moreover, empty measures are common in data cube. This fact negatively affects strategic decision making. Unfortunately, online analytical processing itself is not well suited for classifying, clustering, and predicting empty measures of data cube in the presence of large data. In this regard, today there is a need to use new technologies to solve such problems. Such technologies include neural networks. The article discusses the problem of integrating online analytical processing and a neural network, showing the possibilities and advantages of such integration. It mentions that in the case of big data, the integration of OLAP and neural networks is very effective in solving problems of classification, clustering and empty measure prediction of data cube. An architectural and technological model for the integration of online analytical processing and neural networks is presented.

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18

Chen, Li Yong, and Xiu Ye Yin. "Application of Multi-Dimensional Analysis Technology in Telecom Industry." Advanced Materials Research 219-220 (March 2011): 643–47. http://dx.doi.org/10.4028/www.scientific.net/amr.219-220.643.

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With the rapid development of China's telecom industry, the management of domestic enterprises are constantly changing. Operate method was closed to internationalization constantly. In this process, the technology of OLAP plays a very vital role for the development of enterprises. China's telecom industry should depend on the technology of OLAP to get an efficient decision support system to make an accurate in time efficient decision if they want to survive in the world keen competition, and then leading enterprises moving in the right direction. This paper introduced Multi-dimensional analysis technology, Illustrates the application of drilling and rotation Combined with concrete examples. Hope to provide some help for the development of enterprises, promote the rapid development of China's telecom industry through this paper.

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Alzeini, Haytham, Shihab A. Hameed, and Mohamed Hadi Habaebi. "Building Textual OLAP Cubes Using Real-Time Intelligent Heterogeneous Approach." International Journal of Intelligent Information Technologies 14, no. 3 (July 2018): 83–108. http://dx.doi.org/10.4018/ijiit.2018070105.

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This article describes how the ever-growing amount of data entails introducing innovative solutions in or-der to capture, process, and store the information. OLAP has been considered a powerful analytical technology that enables analysts to gain insight into data and project information from diversified points of view. Thereupon, OLAP has been utilized in a broad spectrum of sensitive applications in the industry. The technology has occupied its place at the forefront of the vibrant information technology landscape of research in order to meet the evolving needs. One of these needs that has enticed the researchers' attention is providing real-time answers which suggests, in particular cases, processing billions of records in few seconds or less. The limited processing capacities have arisen as a major hurdle in the way of achieving such an aim. Although numerous improvements have been suggested, few have considered the heterogeneous computing approach, whereby quantum leap in terms of the response time has been achieved, albeit in most cases, only numerical data have been utilized. In this article, the authors introduce a novel heterogeneous OLAP approach targets textual OLAP cubes aggregation and can be utilized efficiently in OLAP-based pattern recognition problems. In this context, the approach (a) exploits the GPU along with the CPU in order to process textual data. (b) Stores the queries aggregations' hash table in the global memory such that the higher aggregations levels are being answered in a shorter time (c) Introduces an intelligent self-evaluating mechanism (ISEM), that evaluates the resource efficiency on query-basis by deciding which resource (CPU or GPU+CPU) is more reliable to process each query. The authors' empirical results have shown the achieved gain is up to thirty-two folds over the parallel CPU-based counterpart solution. Furthermore, their approach has demonstrated that adopting aggregation-memory optimization significantly improves the performance of high-level textual aggregations.

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КАМАЛОВА, Г. А., А. А. ГУМАРОВА, and М. Н. ТҮТКІШБАЕВА. "МНОГОМЕРНЫЕ ДАННЫЕ И ФОРМИРОВАНИЕ OLAP КУБОВ." Industrial transport of Kazakhstan, no. 4(73) (December 15, 2021): 147–54. http://dx.doi.org/10.58420/itk.2021.73.4.012.

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Бұл мақалада зерттеу аймағы ретінде көп өлшемді деректер базасының құрылымы, қалыптастыру кезеңдері және реляциялық деректерді OLAP жүйесі арқылы көп өлшемді мәліметтерге түрлендіру мәселелері қарастырылды. Мақсаты жаңа деректер текшелерін құру кезінде пайдаланушылардың жұмысын автоматтандыру үшін жоғары деңгейін қамтамасыз ету. Сонымен қатар талдаудың интелектуалды әдістері саласындағы теориялық базаны зерттеп және шешім қабылдауды қолдаудың ақпараттық технологияларымен байланысты бағдарламалар мен жобаларды іске асыруға тікелей қатысуға мүмкіндік беретін түрлі практикалық әдістер меңгерілді. Жүргізілген зерттеулер барысында мынадай міндеттер шешілді: талдау кезінде деректерді сақтау технологиясын зерттеу, деректер базасы ретінде дерек қорынан алынатын реляциялық модельдер, Analysis Manager талдау менеджерінің аналитикалық мүмкіндіктерін игеру, есеп берудің мамандандырылған құралдары. Нәтижесінде көп өлшемді деректерді қалыптастыру және OLAP текшелерімен жұмыс атқару технологиясы ұсынылды. В этой статье были рассмотрены структура многомерной базы данных, этапы формирования и проблемы преобразования реляционных данных в многомерные данные с помощью системы OLAP в качестве области исследования. Цель состоит в том, чтобы обеспечить высокий уровень автоматизации работы пользователей при создании новых кубов данных. Также изучены теоретические основы в области интеллектуальных методов анализа и освоены различные практические методы, позволяющие непосредственно участвовать в реализации программ и проектов, связанных с информационными технологиями поддержки принятия решений. В ходе проведенных исследований были решены следующие задачи: изучение технологии хранения данных при анализе, реляционные модели, получаемые из базы данных в качестве базы данных, освоение аналитических возможностей аналитического менеджера Analysis Manager, специализированные средства отчетности. В результате была предложена технология формирования многомерных данных и работы с OLAP-кубами. In this article, the structure of a multidimensional database, the stages of formation and the problems of converting relational data into multidimensional data using the OLAP system were considered as an area of research. The goal is to provide a high level of user automation when creating new data cubes. We also studied the theoretical foundations in the field of intelligent analysis methods and mastered various practical methods that allow us to directly participate in the implementation of programs and projects related to information technologies for decision support. In the course of the conducted research, the following tasks were solved: the study of data storage technology in analysis, relational models obtained from the database as a database, the development of analytical capabilities of the analytical manager Analysis Manager, specialized reporting tools. As a result, a technology for generating multidimensional data and working with OLAP cubes was proposed.

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Tardío, Roberto, Alejandro Maté, and Juan Trujillo. "A New Big Data Benchmark for OLAP Cube Design Using Data Pre-Aggregation Techniques." Applied Sciences 10, no. 23 (December 4, 2020): 8674. http://dx.doi.org/10.3390/app10238674.

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In recent years, several new technologies have enabled OLAP processing over Big Data sources. Among these technologies, we highlight those that allow data pre-aggregation because of their demonstrated performance in data querying. This is the case of Apache Kylin, a Hadoop based technology that supports sub-second queries over fact tables with billions of rows combined with ultra high cardinality dimensions. However, taking advantage of data pre-aggregation techniques to designing analytic models for Big Data OLAP is not a trivial task. It requires very advanced knowledge of the underlying technologies and user querying patterns. A wrong design of the OLAP cube alters significantly several key performance metrics, including: (i) the analytic capabilities of the cube (time and ability to provide an answer to a query), (ii) size of the OLAP cube, and (iii) time required to build the OLAP cube. Therefore, in this paper we (i) propose a benchmark to aid Big Data OLAP designers to choose the most suitable cube design for their goals, (ii) we identify and describe the main requirements and trade-offs for effectively designing a Big Data OLAP cube taking advantage of data pre-aggregation techniques, and (iii) we validate our benchmark in a case study.

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Yin, Yucan. "Energy Efficiency Evaluation Method for Township Power Users Based on OLAP Technology." Journal of Physics: Conference Series 2530, no. 1 (June 1, 2023): 012015. http://dx.doi.org/10.1088/1742-6596/2530/1/012015.

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Abstract With the development of the smart grid and energy Internet, the traditional demand side response is further expanded to the integrated energy management of users, which puts forward higher requirements for the energy management level of users. The energy consumption structure of users has changed greatly. How to measure the rationality of energy consumption, reduce the cost of energy consumption, save energy, and improve efficiency is very important for users. Aiming at the energy efficiency evaluation of township power users, this paper constructs an index system including users’ energy utilization. It also establishes an evaluation method based on the NSGA-III algorithm combined with OLAP technology to measure the closeness between each energy use scheme and the optimal energy use scheme. Finally, through the example analysis and verification, the results indicate that the proposed energy efficiency evaluation method based on OLAP technology is reasonable. Energy efficiency evaluation can meet the needs of information interaction between users and the smart grid, and improve the energy efficiency and energy-saving effect of township power users through energy efficiency evaluation and management.

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Guo, Min. "Financial System Analysis and Research of OLAP and Data Warehouse Technology." Information Technology Journal 13, no. 3 (January 15, 2014): 522–28. http://dx.doi.org/10.3923/itj.2014.522.528.

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CAO, Li-juan. "Research of Web-OLAP system based on distributed data cache technology." Journal of Computer Applications 28, no. 2 (July 10, 2008): 515–18. http://dx.doi.org/10.3724/sp.j.1087.2008.00515.

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Akhmedyanova, Gulnara F. "Application of OLAP-technology in decision support system for enterprise management." IOP Conference Series: Materials Science and Engineering 971 (December 1, 2020): 052010. http://dx.doi.org/10.1088/1757-899x/971/5/052010.

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Heginbothom, M. L. "On-line analytical processing (OLAP); a step forward in surveillance technology." Journal of Infection 55, no. 3 (September 2007): e80. http://dx.doi.org/10.1016/j.jinf.2007.04.116.

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Ding, Heng, Qian Yuan Zhang, Yan Ping Wang, and Yan Jiang. "Data Warehousing and Data Mining Technology Implementation in Jpeen_CRM System Design." Applied Mechanics and Materials 610 (August 2014): 769–74. http://dx.doi.org/10.4028/www.scientific.net/amm.610.769.

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In this paper, on the basis of in-depth study of data warehouse, OLAP, data mining and other key technologies, according to the characteristics of the Jpeen customer relationship management (Jpeen_CRM), developed a Web-based customer relationship management system. First of all, research the demand for Jpeen company and create Jpeen_CRM data warehouse. Second, create the OLAP multidimensional cube which is applied to the analysis of customer transactions. Using the decision tree algorithm to create mining models for customers to choose glasses, and gives pruning optimize decision tree. Using decision tree to classify users and recommend them the hot products they prefer. Finally, realize the Jpeen_CRM on J2EE platform, provide a decision support for Jpeen company to better serve customers and make the company itself have the advantages in a competitive environment.

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Akimkina, E. E. "Recommendations for deploying multidimensio." Informacionno-technologicheskij vestnik 11, no. 1 (March 30, 2017): 68–80. http://dx.doi.org/10.21499/2409-1650-2017-1-68-80.

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A comparative analysis of different approaches to analytical data and shows that the most ample opportunities has a multi-dimensional approach, implemented with the help of OLAP technology. Presented multidimensional OLAP-cube model with the measurements for the analysis and processing of process data. Practical recommendations for the deployment of a multidimensional data modeling systems with regard to their integration into existing enterprise management system.

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Ahmed, Waqas, Esteban Zimányi, Alejandro Ariel Vaisman, and Robert Wrembel. "A Temporal Multidimensional Model and OLAP Operators." International Journal of Data Warehousing and Mining 16, no. 4 (October 2020): 112–43. http://dx.doi.org/10.4018/ijdwm.2020100107.

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Usually, data in data warehouses (DWs) are stored using the notion of the multidimensional (MD) model. Often, DWs change in content and structure due to several reasons, like, for instance, changes in a business scenario or technology. For accurate decision-making, a DW model must allow storing and analyzing time-varying data. This paper addresses the problem of keeping track of the history of the data in a DW. For this, first, a formalization of the traditional MD model is proposed and then extended as a generalized temporal MD model. The model comes equipped with a collection of typical online analytical processing (OLAP) operations with temporal semantics, which is formalized for the four classic operations, namely roll-up, dice, project, and drill-across. Finally, the mapping from the generalized temporal model into a relational schema is presented together with an implementation of the temporal OLAP operations in standard SQL.

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Budianto, Galih. "Data Warehouse Modeling Using Online Analytical Processing Approach." Jurnal Ilmiah Informatika dan Ilmu Komputer (JIMA-ILKOM) 1, no. 1 (March 22, 2022): 7–13. http://dx.doi.org/10.58602/jima-ilkom.v1i1.2.

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Increasing business needs affect business competition in many companies that utilize information technology. The competition aims to gain advantages that utilize information technology in facilitating business processes. One of the conveniences offered is the use of information technology to support decision making in carrying out existing business processes in middle-to-upper scale companies that have large amounts of data. Online Analysis Processing (OLAP) is an approach method to present answers to the demand for a dimensional analysis process quickly, namely the design of applications and technologies that can collect, store, manipulate multidimensional data for analyst purposes. Information delivery generated from Online Analysis Processing (OLAP) can help executive information systems in generating sales reports because it has a response time of 0.0038769999519 seconds.

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Raswa, Raswa. "PERANCANGAN PEMETAAN MODEL KOMPETENSI DI TEMPAT KERJA BERBASIS SISTEM OLAP." JTT (Jurnal Teknologi Terapan) 6, no. 2 (June 30, 2020): 102. http://dx.doi.org/10.31884/jtt.v6i2.255.

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Graduate profile matches with needed competency by the workplace to be very important learning target sought in the vocational education. This research worshe a On Line Analyical Processing (OLAP) System Design, it can solve to competency model mapping problem, that is done and developed in workplace. This design aim to be helped in formulation of the outcome’s profile, and to be used as source’s information to curriculum development and learning outcome on vocational education. This research is designed as engeneering research with laboratory-explanatory on quasi-experiment by incremental model, and data analytical technic is descriptive-evaluative. As research object is The Network Administrator of the Competency Ocupation Mapping on Communication and Imformation Technic.The conclutions obtained the competency model can be extracted to be multidimensional data so by implementation the OLAP system design can be founded the critical aspects of the competency model. Futher research recommendations are needed field research in OLAP system development for the mapping of competency model by Machine Learning and Deep Learning Technology.

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Lukashevich, Pavel, Alexei Belotserkovsky, and Hrachya Astsatryan. "Modern Systems for Processing and Analyzing GEO-data Based on OLAP Technology." Computer Modeling and Intelligent Systems 2864 (2021): 216–25. http://dx.doi.org/10.32782/cmis/2864-19.

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KOSTISHYN, Sergii. "Ways and possibilities of creating medical information systems based on OLAP-technology." PRZEGLĄD ELEKTROTECHNICZNY 1, no. 5 (May 5, 2017): 112–15. http://dx.doi.org/10.15199/48.2017.05.22.

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Mathur, Nikhita. "An Overview of Data Warehouse and OLAP Technology Used in Banking System." International Journal of Computer Trends and Technology 33, no. 2 (March 25, 2016): 76–79. http://dx.doi.org/10.14445/22312803/ijctt-v33p116.

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Schoech, Dick, John D. Fluke, Randy Basham, Donald J. Baumann, and Gary Cochran. "Visualizing Multilevel Agency Data Using OLAP Technology: An Illustration and Lessons Learned." Journal of Technology in Human Services 22, no. 4 (September 14, 2004): 93–111. http://dx.doi.org/10.1300/j017v22n04_06.

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Nabibayova, G. Ch. "Ensuring Information Security of OLAP-Containing Distributed Electronic Systems using Blockchain Technology." Informacionnye Tehnologii 29, no. 5 (May 16, 2023): 250–56. http://dx.doi.org/10.17587/it.29.250-256.

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The article outlines the properties of blockchain technology, according to which the content of blockchain blocks is immutable and the use of a peer-to-peer (P2P) network implies decentralized management. It describes the essence and meaning of smart-contracts and smart-views derived from them, which are involved in the process of data analysis and decision making. The article considers the papers devoted to various approaches to the problem of integration of blockchain technology and data storage. To ensure all three key aspects of information security — the integrity, availability and confidentiality of information, which is important for both government and corporate structures, the article proposes to use a private blockchain, instead of a public one. A modification of the model of an electronic decision support system containing an OLAP block, which includes a private blockchain, is developed. It is shown that this DSS model can be used as an electronic demographic DSS, which is an infrastructure for solving state problems in this area, since many of the characteristics of this model correspond to the multisectoral nature of demography.

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Abril Fradel, Diego Orlando, and José Nelson Pérez Castillo. "Current data warehousing and OLAP technologies’ status applied to spatial databases." Ingeniería e Investigación 27, no. 1 (January 1, 2007): 58–67. http://dx.doi.org/10.15446/ing.investig.v27n1.14782.

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Organisations require their information on a timely, dynamic, friendly, centralised and easy-to-access basis for analysing it and taking correct decisions at the right time. Centralisation can be achieved with data warehouse technology. On-line analytical processing (OLAP) is used for analysis. Technologies using graphics and maps in data presentation can be exploited for an overall view of a company and helping to take better decisions. Geographic information systems (GIS) are useful for spatially locating information and representing it using maps. Data warehouses are generally implemented with a multidimensional data model to make OLAP analysis easier. A fundamental point in this model is the definition of measurements and dimensions; geography lies within such dimensions. Many researchers have concluded that the geographic dimension is another attribute for describing data in current analysis systems but without having an in-depth study of its spatial feature and without locating them on a map, like GIS does. Seen this way, interoperability is necessary between GIS and OLAP (called spatial OLAP or SOLAP) and several entities are currently researching this. This document summarises the current status of such research.

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Bensalloua, Charef Abdallah, and Djamila Hamdadou. "Spatial OLAP and Multicriteria Integrated Approach for Decision Support System." International Journal of Decision Support System Technology 10, no. 3 (July 2018): 1–26. http://dx.doi.org/10.4018/ijdsst.2018070101.

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This article describes how Spatial On-Line Analytical Processing, such a decisional technology, offers the possibilities of spatial and multidimensional analysis of data stored in multidimensional structure namely spatial data warehouse. However, this technology is limited in the quality aspect of the decision related to the multicriteria consideration. In the current article, the objective is to propose a Spatial Decision Support System namely “Silvicultura” for facilitating decision making in complex situations. This approach is based on integrating multicriteria analysis with SOLAP in order to enrich the spatial and multidimensional analysis with the contribution of MCA tools for mitigating conflict situations. The authors have based their proposal modeling on Unified Modeling language, since it is a well-known standard modeling language and can be easily extended for multidimensional modeling. Finally, in order to validate their proposal, the authors present a case study to show how to use it in the agroforestry management.

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Wisnubhadra, Irya, Safiza Kamal Baharin, Nurul A. Emran, and Djoko Budiyanto Setyohadi. "QB4MobOLAP: A Vocabulary Extension for Mobility OLAP on the Semantic Web." Algorithms 14, no. 9 (September 13, 2021): 265. http://dx.doi.org/10.3390/a14090265.

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The accessibility of devices that track the positions of moving objects has attracted many researchers in Mobility Online Analytical Processing (Mobility OLAP). Mobility OLAP makes use of trajectory data warehousing techniques, which typically include a path of moving objects at a particular point in time. The Semantic Web (SW) users have published a large number of moving object datasets that include spatial and non-spatial data. These data are available as open data and require advanced analysis to aid in decision making. However, current SW technologies support advanced analysis only for multidimensional data warehouses and Online Analytical Processing (OLAP) over static spatial and non-spatial SW data. The existing technology does not support the modeling of moving object facts, the creation of basic mobility analytical queries, or the definition of fundamental operators and functions for moving object types. This article introduces the QB4MobOLAP vocabulary, which enables the analysis of mobility data stored in RDF cubes. This article defines Mobility OLAP operators and SPARQL user-defined functions. As a result, QB4MobOLAP vocabulary and the Mobility OLAP operators are evaluated by applying them to a practical use case of transportation analysis involving 8826 triples consisting of approximately 7000 fact triples. Each triple contains nearly 1000 temporal data points (equivalent to 7 million records in conventional databases). The execution of six pertinent spatiotemporal analytics query samples results in a practical, simple model with expressive performance for the enabling of executive decisions on transportation analysis.

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Xu, Mao Li, and Xiu Ying Li. "Construction of the Library Management System Based on Data Warehouse and OLAP." Applied Mechanics and Materials 380-384 (August 2013): 4796–99. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.4796.

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Along with the evolvement of data warehouse technology, the establishment of the decision support system for libraries is becoming more and more important. This paper provides the architecture of the data warehouse-based library decision support system and focuses on discussing the model design and implementation technology of data warehouse building.

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Yakuba, E. S., V. S. Tynchenko, V. V. Bukhtoyarov, and V. V. Tynchenko. "THE SYSTEM FOR GOVERNMENT TENDERS DOCUMENTS ANALYSIS ON THE BASIS OF OLAP TECHNOLOGY." Scientific and Technical Volga region Bulletin 6, no. 3 (June 2016): 154–57. http://dx.doi.org/10.24153/2079-5920-2016-6-3-154-157.

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Nešić, Zoran, Miroslav Radojičić, Jasmina Vesić-Vasović, and Nebojša Denić. "Some considerations on the implementation of OLAP technology in small and middle companies." IMK-14 - Istrazivanje i razvoj 22, no. 4 (2016): 37–41. http://dx.doi.org/10.5937/imk1602037n.

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Rahadi, Putu Suta Adya Dharma, Putu Widiadnyana, and Nengah Sweden. "Designing Data Warehouse in Finance Company Study at PT ABC." International Journal of Engineering and Emerging Technology 2, no. 1 (September 23, 2017): 58. http://dx.doi.org/10.24843/ijeet.2017.v02.i01.p12.

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Along with the development of technology and business needs that are more advanced, the more effective and efficient uses of Information Systems is an important thing for companies to continue competing in the era of globalization. Every company wants an appropriate Information System to run business activities smoothly. Using data warehouses can help PT ABC's problems in accommodating large amounts of data with its OLTP system which can then be processed in determining future strategies through OLAP systems. So as to get the reports needed in maintaining the consistency and improve the performance of the company.

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Rybakova, Angelina. "Formation of data of the modular building infor-mation model in olap format." Construction and Architecture 11, no. 1 (March 24, 2023): 21. http://dx.doi.org/10.29039/2308-0191-2022-11-1-21-21.

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The article provides an analysis of the use of OLAP technology in the design of modular objects based on information modeling technologies, presents the classification and systematization of information models of modular elements of maximum readiness. The purpose of this study is to develop and analyze a data model for the most effective data management of an information model of a capital construction object both at the design stage and at subsequent stages of the life cycle. In order to achieve this goal, it is necessary to take into account not only the features and attributes of information models, but also the key characteristics of modular design, including elements of the MEG within the existing tools for systematization of digital data. As a result, the impact of using OLAP cubes to represent a modular object at all stages of the life cycle is considered. New possibilities and advantages of using the OLAP data management model of the information model of the capital construction object are presented. The directions of further research are formulated.

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Kuang, Ye, and Chao Xie. "Research on an Economic Monitor and Decision Support System Based on Data Warehouse Technology." Applied Mechanics and Materials 416-417 (September 2013): 2016–19. http://dx.doi.org/10.4028/www.scientific.net/amm.416-417.2016.

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Data warehouse technology is a new international pioneering research method which is developed by the urgent demands to adequately apply IT resources including Data Warehouse (DW), Data Mining (DM) and OLAP. The architecture and realization methods of an economic monitor and decision support system (DSS) based on DW are presented in this article.

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DELGADO, MIGUEL, CARLOS MOLINA, LÁZARO RODRÍGUEZ-ARIZA, DANIEL SÁNCHEZ, and M. AMPARO VILA. "F-CUBE FACTORY: A FUZZY OLAP SYSTEM FOR SUPPORTING IMPRECISION." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 15, supp01 (February 2007): 59–81. http://dx.doi.org/10.1142/s0218488507004467.

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The special needs of the OLAP technology were the main cause of the use of a multidimensional view of the data. Crisp models are not suitable to model complex or non well defined domains. They also fail to integrate data from semi/non-structured sources (e.g. Internet) or with incompatibilities in their schemata. In these situations, as a result of the modelling and/or integration, imprecision appears. So, we need a model able to manage imprecision in the structures and data. If we want to use expert's knowledge in the analysis, we have to keep in mind that expert users are more comfortable when they use linguistic expressions instead of exact values. In this paper we present an extension of a fuzzy multidimensional model to support the use of linguistic labels in the definition of the hierarchies and the OLAP system that implements this model.

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Davardoost, Farnaz, Amin Babazadeh Sangar, and Kambiz Majidzadeh. "An Innovative Model for Extracting OLAP Cubes from NOSQL Database Based on Scalable Naïve Bayes Classifier." Mathematical Problems in Engineering 2022 (April 11, 2022): 1–11. http://dx.doi.org/10.1155/2022/2860735.

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Due to unstructured and large amounts of data, relational databases are no longer suitable for data management. As a result, new databases known as NOSQL have been introduced. The issue is that such a database is difficult to analyze. Online analytical processing (OLAP) is the foundational technology for data analysis in business intelligence. Because these technologies were designed primarily for relational database systems, performing OLAP in NOSQL is difficult. We present a model for extracting OLAP cubes from a document-oriented NOSQL database in this article. A scalable Naïve Bayes classifier method was used for this purpose. The proposed solution is divided into three stages of preparation, Naïve Bayes, and NBMR. Our proposed algorithm, NBMR, is based on the Naïve Bayes classifier (NBC) and the MapReduce (MR) programming model. Each NOSQL database document with nearly the same attribute will belong to the same class, and as a result, OLAP cubes can be used to perform data analysis. Because the proposed model allows for distributed and parallel Naïve Bayes Classifier computing, it is appropriate and suitable for large-scale data sets. Our proposed model is a proper and efficient approach when considering the speed and reduced the number of required comparisons.

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Lamani, Asma, Brahim Erraha, Malika Elkyal, and Abdallah Sair. "Data mining techniques application for prediction in OLAP cube." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 3 (June 1, 2019): 2094. http://dx.doi.org/10.11591/ijece.v9i3.pp2094-2102.

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Data warehouses represent collections of data organized to support a process of decision support, and provide an appropriate solution for managing large volumes of data. OLAP online analytics is a technology that complements data warehouses to make data usable and understandable by users, by providing tools for visualization, exploration, and navigation of data-cubes. On the other hand, data mining allows the extraction of knowledge from data with different methods of description, classification, explanation and prediction. As part of this work, we propose new ways to improve existing approaches in the process of decision support. In the continuity of the work treating the coupling between the online analysis and data mining to integrate prediction into OLAP, an approach based on automatic learning with Clustering is proposed in order to partition an initial data cube into dense sub-cubes that could serve as a learning set to build a prediction model. The technique of data mining by regression trees is then applied for each sub-cube to predict the value of a cell.

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Adamko, Eva, Peter Tamas Szemes, and Mihoko Niitsuma. "INVESTIGATION ON THE HEATING SYSTEM OF THE MECHATRONICS RESEARCH CENTER BUILDING USING OLAP TECHNOLOGY." Environmental Engineering and Management Journal 13, no. 11 (2014): 2733–42. http://dx.doi.org/10.30638/eemj.2014.304.

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Purwanto, Joko, and Renny Renny. "Perancangan Data Warehouse Rumah Sakit Berbasis Online Analytical Processing (OLAP)." Jurnal Teknologi Informasi dan Ilmu Komputer 8, no. 5 (October 21, 2021): 1077. http://dx.doi.org/10.25126/jtiik.2021854232.

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<p class="BodyCxSpFirst">Pemanfaatan teknologi informasi sangat penting bagi rumah sakit, karena berpengaruh pula terhadap kualitas pelayanan kesehatan yang secara manual diubah menjadi digital dengan menggunakan teknologi informasi.Dalam penelitian ini penulis menggunakan metodologi <em>Nine step</em> sebagai acuan dalam merancang suatu <em>data warehouse</em><em>,</em> untuk pemodelan menggunakan skema konstelasi fakta dengan 3 tabel fakta dan 11 tabel dimensi. Perbedaan penelitian ini dengan penelitian sebelumnya terletak pada sumber data yang diekstrak langsung dari <em>database</em> SIMRS yang digunakan rumah sakit, sehingga tidak ada ekstraksi data secara manual.Penelitian ini bertujuan untuk menghasilkan desain data warehouse berbasis Online Analytical Processing (OLAP) sebagai sarana penunjang kualitas pelayanan kesehatan rumah sakit. OLAP yang dihasilkan akan berupa desain data warehouse dengan berbagai dimensi yang akan menghasilkan tampilan informasi berupa Chart maupun Grafik sehingga informasinya mudah dibaca dan dipahami oleh berbagai pihak.</p><p class="BodyCxSpFirst"> </p><p class="BodyCxSpFirst"><em><strong>Abtract</strong></em></p><p class="BodyCxSpFirst"><em>The use of information technology is very important for hospitals, because it also affects the quality of health services, which manualy changed to digital using information technology. In this study, the authors used the Nine step methodology as a reference in designing a data warehouse for modeling using a fact constellation schema with 3 fact tables and 11 dimension tables. the different in this study from previous research is that the data source was taken directly from the SIMRS database used by the hospital, so there is no manual data extraction.</em><em>The aim of this research is to be able to produce a Data Warehouse design based on Online Analytical Processing (OLAP) as a means of supporting the quality of hospital health services. The resulting OLAP will be a data warehouse design with various dimensions will produce the displays information in the form of a graph or chart so that the information is easy to read and understand by various parties.</em></p><p class="BodyCxSpLast"><em> </em></p><p class="BodyCxSpFirst"><em><strong><br /></strong></em></p>

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