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Journal articles on the topic 'Online Analytical Processing (OLAP)'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Sharma, Pitambar, and Piyush Girdhar. "Online Analytical Processing (OLAP)." Journal of Advance Research in Computer Science & Engineering (ISSN: 2456-3552) 1, no. 3 (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 th

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Wijaya, Andri, Mutia Maharani, and Meilinda. "IMPLEMENTASI PENDEKATAN AGILE UNTUK PENGEMBANGAN OLAP DATA PENJUALAN." ZONAsi: Jurnal Sistem Informasi 6, no. 1 (2024): 222–31. http://dx.doi.org/10.31849/zn.v6i1.17337.

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Sales data in large quantities are difficult to process and report using Microsoft Excel, which takes a long time. The proposed solution is to use Online Analytical Processing, a method that allows for faster decision-making through multidimensional data manipulation. In developing Online Analytical Processing for sales data, an agile approach is applied. With Online Analytical Processing, access to and display of transactional data becomes more efficient, improving analysis quality and supporting management decisions. Research results show that the prototype accelerates sales reports with a r

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Aldisa, Rima Tamara. "Penerapan Online Analytical Processing (OLAP) dalam Pengelolaan Data Karyawan." JURIKOM (Jurnal Riset Komputer) 9, no. 1 (2022): 55. http://dx.doi.org/10.30865/jurikom.v9i1.3832.

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At this time many companies manage employee data manually from the process of recording employee data, employee absences which can result in data errors. Because of several things, it is necessary to have a system that can record every incoming data as well as a method that can control it so as not to experience excess or deficiency. The method used is the Online Analytical Processing (OLAP) method. The Online Analytical Processing (OLAP) method is an approach method to provide answers to requests for dimensional analysis processes quickly, the result to be achieved is to be able to design app

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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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Budianto, Galih. "Data Warehouse Modeling Using Online Analytical Processing Approach." Jurnal Ilmiah Informatika dan Ilmu Komputer (JIMA-ILKOM) 1, no. 1 (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

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Nabibayova, Gulnara. "Expanding the intellectual capabilities of OLAP technology using neural networks." Problems of Information Society 15, no. 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 strat

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Chou, Chung-Hsien, Masahiro Hayakawa, Atsushi Kitazawa, and Phillip Sheu. "GOLAP: Graph-Based Online Analytical Processing." International Journal of Semantic Computing 12, no. 04 (2018): 595–608. http://dx.doi.org/10.1142/s1793351x18500071.

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Graph-based Online Analytical Processing (GOLAP) extends Online Analytical Processing (OLAP) to address graph-based problems that involve object attributes. Based on graph data, GOLAP can answer user queries related to combinatorial optimization, structural analytics, and influence analytics. Besides, since a GOLAP system is an online interactive system that requires fast response time, the execution time for graph-problem queries is essentially critical. Thus, how to speed up the execution time of specific graph problems becomes a challenge in GOLAP. In this paper, we show several methods to

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Saputra, Eko. "Permodelan Data Warehouse Untuk Penjualan Ban Menggunakan Online Analytical Processing (OLAP)." Jurnal Ilmiah Informatika dan Ilmu Komputer (JIMA-ILKOM) 2, no. 1 (2023): 12–18. http://dx.doi.org/10.58602/jima-ilkom.v2i1.13.

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Data warehouse akan memungkinkan integrasi data dari berbagai macam aplikasi atau sistem yang dapat menjamin akses yang lebih cepat bagi manajemen untuk memperoleh informasi dan menganalisanya sebagai bahan informasi. Penggunaan Teknologi OLAP dapat memudahkan para stakeholder dalam mengambil keputusan. Tujuan penelitian ini adalah merancang data warehouse untuk transaksi penjualan agar mendukung proses analisa bagi para pihak eksekutif dalam pengambilan keputusan. Data warehouse Penjualan dirancangan dengan menggunakan Nine Step Methodology data warehouse sehingga menghasilkan desain data war

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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 (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 dieks

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Camilleri, Carl, Joseph G. Vella, and Vitezslav Nezval. "HTAP With Reactive Streaming ETL." Journal of Cases on Information Technology 23, no. 4 (2021): 1–19. http://dx.doi.org/10.4018/jcit.20211001.oa10.

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In database management systems (DBMSs), query workloads can be classified as online transactional processing (OLTP) or online analytical processing (OLAP). These often run within separate DBMSs. In hybrid transactional and analytical processing (HTAP), both workloads may execute within the same DBMS. This article shows that it is possible to run separate OLTP and OLAP DBMSs, and still support timely business decisions from analytical queries running off fresh transactional data. Several setups to manage OLTP and OLAP workloads are analysed. Then, benchmarks on two industry standard DBMSs empir

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Jing, Changhong, Wenjie Liu, Jintao Gao, and Ouya Pei. "Research and implementation of HTAP for distributed database." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 39, no. 2 (2021): 430–38. http://dx.doi.org/10.1051/jnwpu/20213920430.

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Data processing can be roughly divided into two categories, online transaction processing OLTP(on-line transaction processing) and online analytical processing OLAP(on-line analytical processing). OLTP is the main application of traditional relational databases, and it is some basic daily transaction processing, such as bank pipeline transactions and so on. OLAP is the main application of the data warehouse system, it supports some more complex data analysis operations, focuses on decision support, and provides popular and intuitive analysis results. As the amount of data processed by enterpri

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Martinez-Mosquera, Diana, Rosa Navarrete, Sergio Luján-Mora, Lorena Recalde, and Andres Andrade-Cabrera. "Integrating OLAP with NoSQL Databases in Big Data Environments: Systematic Mapping." Big Data and Cognitive Computing 8, no. 6 (2024): 64. http://dx.doi.org/10.3390/bdcc8060064.

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The growing importance of data analytics is leading to a shift in data management strategy at many companies, moving away from simple data storage towards adopting Online Analytical Processing (OLAP) query analysis. Concurrently, NoSQL databases are gaining ground as the preferred choice for storing and querying analytical data. This article presents a comprehensive, systematic mapping, aiming to consolidate research efforts related to the integration of OLAP with NoSQL databases in Big Data environments. After identifying 1646 initial research studies from scientific digital repositories, a t

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Martinez-Mosquera, Diana, Rosa Navarrete, Sergio Luján-Mora, Lorena Recalde, and Andres Andrade-Cabrera. "Integrating OLAP with NoSQL Databases in Big Data Environments: Systematic Mapping." Big Data and Cognitive Computing 8, no. 6 (2024): 1–29. https://doi.org/10.3390/bdcc8060064.

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The growing importance of data analytics is leading to a shift in data management strategy at many companies, moving away from simple data storage towards adopting Online Analytical Processing (OLAP) query analysis. Concurrently, NoSQL databases are gaining ground as the preferred choice for storing and querying analytical data. This article presents a comprehensive, systematic mapping, aiming to consolidate research efforts related to the integration of OLAP with NoSQL databases in Big Data environments. After identifying 1646 initial research studies from scientific digital repositories, a t

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Liliana, Lydia, Henny Hartono, and Devi Yurisca Bernanda. "INTEGRASI DATA MINING DAN ONLINE ANALYTICAL PROCESSING (OLAP) PADA DATA PERFORMA SISWA." Jurnal Sisfokom (Sistem Informasi dan Komputer) 9, no. 3 (2020): 400–406. http://dx.doi.org/10.32736/sisfokom.v9i3.1022.

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Pertumbuhan teknologi membawa dampak terhadap peningkatan data untuk digunakan bagi setiap orang. Akumulasi data tersebut telah menciptakan pola data yang semakin banyak, namun perolehan informasi dari data tersebut masih minim. Oleh karena itu, saat ini diperlukan suatu teknik analisa data dalam mencari pola dari kumpulan data tersebut, salah satunya adalah data mining. Data mining merupakan proses pencarian informasi baru dari kumpulan data yang besar untuk menemukan informasi baru sebagai bahan pertimbangan dalam pengambilan keputusan di berbagai bidang, seperti bidang pendidikan. Dalam bid

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Sulianta, Feri, and Philothra Clarissa Raina. "Kelola Kubikal Data Transaksional Sistem Informasi Rumah Sakit Dengan Teknik Online Analytical Processing." MIND Journal 1, no. 1 (2018): 1. http://dx.doi.org/10.26760/mindjournal.v1i1.1.

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Data transaksional rumah sakit dapat diberdayakan lebih lanjut untuk ragam keperluan dan bukan hanya sebagai arsip riwayat pasien perseorangan saja. Berbagai informasi berharga dapat diungkapkan dari data transkasional rumah sakit yang dihasilkan dari sistem rekam medis.Dalam kasus ini untuk mendapatkan kejelasan yang melibatkan informasi menyeluruh yang juga melibatkan ragam sudut pandang dapat disolusikan dengan teknik Online Analytical Processing (OLAP). Teknik ini mampu mengakomodasi kelengkapan data yang nantinya menjadi framework untuk dianalisa secara seksama Mengacu pada data rekam med

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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 (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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Liu, Bin, Zhengyu Yang, Jiaqing Wu, and Jie Gu. "OLAP analysis of user energy consumption based on multitemporal distribution characteristics." Journal of Physics: Conference Series 2290, no. 1 (2022): 012045. http://dx.doi.org/10.1088/1742-6596/2290/1/012045.

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Abstract With the development of databases, online transaction processing (OLTP) can no longer meet the needs of end users for database query and analysis, and the simple query of large databases by SQL can not meet the requirements of end user analysis. Therefore, online analytical processing (OLAP) is proposed. concept. On the one hand, we explained the basic knowledge of OLAP, including OLAP multidimensional data concept, multidimensional data structure, multidimensional data analysis, characteristics, etc. On the other hand, we established an OLAP analysis model of the multi-temporal and s

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Alkharouf, Nadim W., D. Curtis Jamison, and Benjamin F. Matthews. "Online Analytical Processing (OLAP): A Fast and Effective Data Mining Tool for Gene Expression Databases." Journal of Biomedicine and Biotechnology 2005, no. 2 (2005): 181–88. http://dx.doi.org/10.1155/jbb.2005.181.

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Gene expression databases contain a wealth of information, but current data mining tools are limited in their speed and effectiveness in extracting meaningful biological knowledge from them. Online analytical processing (OLAP) can be used as a supplement to cluster analysis for fast and effective data mining of gene expression databases. We used Analysis Services 2000, a product that ships with SQLServer2000, to construct an OLAP cube that was used to mine a time series experiment designed to identify genes associated with resistance of soybean to the soybean cyst nematode, a devastating pest

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DEHURI, S., and R. MALL. "PARALLEL PROCESSING OF OLAP QUERIES USING A CLUSTER OF WORKSTATIONS." International Journal of Information Technology & Decision Making 06, no. 02 (2007): 279–99. http://dx.doi.org/10.1142/s0219622007002484.

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Online analytical processing (OLAP) queries normally incur enormous processing overheads due to the huge size of data warehouses. This results in unacceptable response times. Parallel processing using a cluster of workstations has of late emerged as a practical solution to many compute and data intensive problems. In this article, we present parallel algorithms for some of the OLAP operators. We have implemented these parallel solutions for a data warehouse implemented on Oracle hosted in a cluster of workstations. Our performance studies show that encouraging speedups are achieved.

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Angelya, Tasya, Abdul Rahman, and Iis Pradesan. "Perancangan Data Warehouse Online Analytical Processing (OLAP) Data Hasil Kerja PT. ABC." MDP Student Conference 2, no. 1 (2023): 656–64. http://dx.doi.org/10.35957/mdp-sc.v2i1.4241.

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PT. ABC merupakan salah satu perusahaan jasa yang bergerak dibidang Hutan Tanaman Industri. Perusahaan ini memiliki banyak tim yang tersebar di semua lokasi kerja sehingga data yang masuk semakin banyak pula, data-data tersebut tentunya perlu disimpan, diolah, dan dianalisis untuk menghasilkan suatu informasi yang berguna bagi perusahaan, dan dilaporkan kepada manajer untuk mengetahui keadaan perusahaan pada periode waktu tertentu. Dengan demikian dibutuhkanlah Data Warehouse yang digunakan untuk mendukung data yang dapat dimanfaatkan sebagai sumber informasi ketika menganalisis data. Perancan

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Honda, Masayuki, and Takehiro Matsumoto. "System Replacement to a New HIS and Data Warehouse." Journal of Advanced Computational Intelligence and Intelligent Informatics 16, no. 1 (2012): 38–41. http://dx.doi.org/10.20965/jaciii.2012.p0038.

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Large-scale hospital information systems (HIS) generally consist of (i) online transaction processing (OLTP) and (ii) online analytical processing (OLAP) systems. Electronic medical records (EMR) are a major OLTP element. The data warehouse (DWH) assumes many important OLAP roles and maintains an institution’s medical care at a high level by providing EMR with the best practice cases available. This article focuses mainly on why OLTP and OLAP are needed and what roles the DWH plays, which means that the DWH has its own utilities and supplementary merits. The background of this discussion is cl

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Anam, Khaerul, and Lasimin Lasimin. "Business Intelligence pada Sistem Manajemen Aset Unugha dengan Metode Online Analytical Processing (Olap)." Jurnal Inovasi Global 2, no. 10 (2024): 1505–16. http://dx.doi.org/10.58344/jig.v2i10.186.

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Pengolahan data penting untuk memperoleh informasi yang memengaruhi keputusan dan kemajuan operasional perusahaan atau instansi. Universitas Nadlatul Ulama Al Ghazali Cilacap (UNUGHA) menggunakan teknologi komputer untuk penyimpanan data, tetapi pengelolaan data produk masih kurang optimal, sehingga informasi yang dihasilkan tidak membantu administrator. Salah satu cara mengatasi permasalahan tersebut adalah dengan menerapkan Business Intelligence pada Manajemen Aset UNUGHA (MAU), dengan menggunakan Online Analytical Processing (OLAP) untuk memudahkan pengguna dalam menampilkan data multidimen

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Tri Susilo, Andri Anto. "PENERAPAN METODE OLAP PADA PROSES PENILAIAN KINERJA GURU (STUDI KASUS : SMA BINASATRIA KOTA LUBUKLINGGAU)." JUTIM (Jurnal Teknik Informatika Musirawas) 3, no. 2 (2018): 65–73. http://dx.doi.org/10.32767/jutim.v3i2.357.

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AbstrakPenilaian atas kinerja guru sangat dibutuhkan sebagai bahan evaluasi untuk meningkatkan mutu dan kualitas dalam hal belajar dan mengajar. Adapun kriteria penilaian tersebut adalah Pedagogik, Kepribadian, Sosial, Profesial. Penilaian kinerja guru di SMA Bina Satria masih menggunakan cara manual yaitu pegawai tata usaha harus memeriksa data guru dengan mencari berkas terlebih dahulu. Yang menjadi kendala adalah proses penilaian ini sangat rumit, misalnya mencari data atau berkas guru dan proses penghitungan nilai yang panjang serta rumit jika dilakukan secara manual memerlukan waktu yang

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Azizah, Qonita, Masriah Masriah, and Wahyu Tisno Atmojo. "Perancangan Data Warehouse Sistem Penerimaan Siswa Baru Menggunakan Online Analytical Processing (OLAP) di TK IT Mutiara." Dirgamaya: Jurnal Manajemen dan Sistem Informasi 2, no. 2 (2022): 35–47. http://dx.doi.org/10.35969/dirgamaya.v2i2.273.

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Peningkatan jumlah siswa pada TK IT Mutiara membuat sekolah kesulitan dalam melakukan pengelolaan data pendaftaran sehingga harus membutuhkan waktu untuk mendapatkan informasi. Pembuatan aplikasi OnLine Analytical Processing (OLAP) Data Warehouse dapat membantu mengekstrak dan memudahkan dalam mencari informasi penting dari beberapa sistem informasi yang berbeda. Metode penelitian yang dilakukan adalah kualitatif dengan teknik perolehan data wawancara dengan seorang narasumber di TK IT Mutiara dan studi pustaka melalui jurnal yang relevan dengan topik penulis dan juga menggunakan metode nine s

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Samsinar, Riza, Jatmiko Endro Suseno, and Catur Edi Widodo. "Power Distribution Analysis For Electrical Usage In Province Area Using Olap (Online Analytical Processing)." E3S Web of Conferences 31 (2018): 11010. http://dx.doi.org/10.1051/e3sconf/20183111010.

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The distribution network is the closest power grid to the customer Electric service providers such as PT. PLN. The dispatching center of power grid companies is also the data center of the power grid where gathers great amount of operating information. The valuable information contained in these data means a lot for power grid operating management. The technique of data warehousing online analytical processing has been used to manage and analysis the great capacity of data. Specific methods for online analytics information systems resulting from data warehouse processing with OLAP are chart an

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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 (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 mu

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Mohammed Omer Shakeel Ahmed. "Enhancing CRM Decision-Making with HTAP: Leveraging Real-Time Analytics for Competitive Advantage." Journal of Information Systems Engineering and Management 10, no. 23s (2025): 50–57. https://doi.org/10.52783/jisem.v10i23s.3675.

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Customer Relationship Management (CRM) systems traditionally separate transactional and analytical data into distinct layers, with transactional databases optimized for fast writes and analytical data warehouses for read-heavy queries. This separation introduces delays in analytics, hindering real-time insights and timely decision-making. Hybrid Transactional/Analytical Processing (HTAP) offers a unified solution by integrating Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) in a single system. This paper explores the feasibility of applying HTAP in CRM systems, hi

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Darman, Ridho. "ANALISIS DATA KEJADIAN BENCANA ANGIN PUTING BELIUNG DENGAN METODE ONLINE ANALYTICAL PROCESSING (OLAP)." SINTECH (Science and Information Technology) Journal 2, no. 1 (2019): 18–23. http://dx.doi.org/10.31598/sintechjournal.v2i1.298.

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A whirlwind is a natural disaster with a relatively high incidence. In improving whirlwinddisaster mitigation preparedness, analysis of historical data of events is needed to minimize the possibility of losses. In this study, data analysis was carried out using the Online Analytical Processing (OLAP) method with the Zoho Reports application so that it can be known to the region prone to whirlwind and the time of occurrence to help those who have an importance in decision making. The results of the analysis are in the form of information displayed in graphical form from data on the occurrence o

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RMS, Anita Sindar. "Implementasi OLAP Menggunakan Dashboard Holistics Software Pada LPPM STMIK Pelita Nusantara." Jurnal Teknologi dan Ilmu Komputer Prima (JUTIKOMP) 2, no. 1 (2019): 55–59. http://dx.doi.org/10.34012/jutikomp.v2i1.457.

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Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) merupakan lembaga institusi penting dari sebuah perguruan tinggi, wadah para dosen melaporkan kewajiban penelitian dan pengabdian sekaligus untuk penilaian Tri Dharma dosen. Rancangan OLAP bertujuan untuk mempermudah para stockholder tertarik melihat laporan berdasarkan issue, judul artikel, jumlah pengutipan dari setiap dosen, membantu pengambil keputusan dalam review kinerja para dosen dalam melaksanakan Tri Dharma Perguruan Tinggi. Teknik Online Analytical Processing (OLAP) yaitu digunakan untuk meningkatkan analisis bisnis, dilakukan oleh

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Amalia, Syahfitri Suendri. "Penerapan Business Intelligence pada Jenis Bisnis Peluang Usaha UMKM di Desa Silenduk Menggunakan Teknologi Online Analytical Processing." TEKNIKA 19, no. 1 (2024): 315–26. https://doi.org/10.5281/zenodo.14279613.

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UMKM di Desa Silenduk menghadapi berbagai tantangan, seperti keterbatasan akses informasi, manajemen stok yang tidak efisien, pemasaran yang tidak tepat sasaran, dan keterbatasan kapasitas analisis. Penelitian ini bertujuan untuk menganalisis penerapan Business Intelligence (BI) menggunakan teknologi Online Analytical Processing (OLAP) sebagai solusi untuk mengatasi masalah tersebut. Metode penelitian mencakup pengumpulan dan integrasi data, analisis prediktif, serta pengambilan keputusan berbasis data untuk mendukung optimalisasi operasional. Hasil penelitian menunjukkan bahwa penerapan BI da

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Yu, Dongjin, Yiyu Wu, Jingchao Sun, et al. "Mining Hidden Interests from Twitter Based on Word Similarity and Social Relationship for OLAP." International Journal of Software Engineering and Knowledge Engineering 27, no. 09n10 (2017): 1567–78. http://dx.doi.org/10.1142/s0218194017400113.

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Online Analytical Processing, or OLAP, is an approach to answering multidimensional analytical (MDA) queries in an interactive way. However, the traditional OLAP approaches can only deal with structured data, but not unstructured textual data like tweets. To address this problem, we propose a Latent Dirichlet Allocation (LDA)-based model, called Multilayered Semantic LDA (MS-LDA), which detects the hidden layered interests from Twitter data based on LDA. The layered dimension of interests can be further used to apply OLAP techniques to Twitter data. Furthermore, MS-LDA employs the semantic sim

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Et.al, Anjana Yadav. "Improving the Performance of Multidimensional Clinical Data for OLAP using an Optimized Data Clustering approach." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (2021): 3269–75. http://dx.doi.org/10.17762/turcomat.v12i3.1575.

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Medicine is a fresh way to utilize for curing, analyzing and detecting the diseases through data clustering with OLAP (Online Analytical Processing). The large amount of multidimensional clinical data is reduced the efficiency of OLAP query processing by enhancing the query accessing time. Hence, the performance of OLAP model is improved by using data clustering in which huge data is divided into several groups (clusters) with cluster heads to achieve fast query processing in least time. In this paper, a Dragon Fly Optimization based Clustering (DFOC) approach is proposed to enhance the effici

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Jin, Jennifer, and Masahiro Hayakawa. "Network analysis and GOLAP." Encyclopedia with Semantic Computing and Robotic Intelligence 02, no. 02 (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

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Sadek, Menaceur, Makhlouf Derdour, and Bouramoul Abdelkrim. "Personalized Online Analytical Processing in Big Data Context Using User Profile and Search Context." International Journal of Strategic Information Technology and Applications 8, no. 4 (2017): 67–80. http://dx.doi.org/10.4018/ijsita.2017100106.

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This article is part of the field of analysis and personalization of large data sets (Big Data). This aspect of analysis and customization has become a major issue that has generated a lot of questions in recent years. Indeed, it is difficult for inexperienced or casual users to extract relevant information in a Big Data context, for volume, the velocity and the variability of data make it difficult for the user to capture, manage and process data by methods and traditional tools. In this article, the authors propose a new approach for personalizing OLAP analysis in a Big Data context by using

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Subrahmanyam, Prabhakar. "High-Fidelity Aerothermal Engineering Analysis for Planetary Probes Using DOTNET Framework and OLAP Cubes Database." International Journal of Aerospace Engineering 2009 (2009): 1–21. http://dx.doi.org/10.1155/2009/326102.

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This publication presents the architecture integration and implementation of various modules inSpartaframework.Spartais a trajectory engine that is hooked to an Online Analytical Processing (OLAP) database for Multi-dimensional analysis capability. OLAP is an Online Analytical Processing database that has a comprehensive list of atmospheric entry probes and their vehicle dimensions, trajectory data, aero-thermal data and material properties like Carbon, Silicon and Carbon-Phenolic based Ablators. An approach is presented for dynamic TPS design. OLAP has the capability to run in one simulation

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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 (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 usin

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Rapolu, Naresh Kumar. "MIGRATION OF LEGACY DATABASE ORACLE/MS SQL TO HANA DATABASE TO IMPROVE REAL-TIME ONLINE ANALYTICAL PROCESSING AND ONLINE TRANSACTION PROCESSING FROM ONE DATA MODEL." International Scientific Journal of Engineering and Management 02, no. 03 (2023): 1–7. https://doi.org/10.55041/isjem00215.

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The following research project has explored the vitality of the migration of legacy databases, specifically Oracle with MS SQL to the HANA database. This has been effective to improve the possibilities of real-time online analytical and transaction processing. It has emerged to be ethical to migrate the challenges faced while migrating to the HANA database with efficient approaches like the development of a migration plan and proposing a comprehensive assessment of existing data structures. This has paved the path for transitioning HANA databases for streamlining data management of data models

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Liao, Yung-Cheng, and Mei-Su Chen. "The Project-Based Learning Study of Insurance Information Courses to Simulate the Application of Online Analytical Processing." Applied System Innovation 6, no. 2 (2023): 47. http://dx.doi.org/10.3390/asi6020047.

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The use of data warehouses combined with online analytical processing (OLAP) platforms has become popular in Taiwan’s insurance market. However, most schools do not have an insurance data warehouse and OLAP platform for student learning in Taiwan. The researched courses are insurance information system courses for two university classes. Based on the teacher’s experience and innovativeness, those courses are integrated using the guided project-based learning approach. Students need to build a customer micro-database, analyze customer figures through pivot analysis charts, and plan marketing ca

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Gaffney, Kevin P., Martin Prammer, Larry Brasfield, D. Richard Hipp, Dan Kennedy, and Jignesh M. Patel. "SQLite." Proceedings of the VLDB Endowment 15, no. 12 (2022): 3535–47. http://dx.doi.org/10.14778/3554821.3554842.

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In the two decades following its initial release, SQLite has become the most widely deployed database engine in existence. Today, SQLite is found in nearly every smartphone, computer, web browser, television, and automobile. Several factors are likely responsible for its ubiquity, including its in-process design, standalone codebase, extensive test suite, and cross-platform file format. While it supports complex analytical queries, SQLite is primarily designed for fast online transaction processing (OLTP), employing row-oriented execution and a B-tree storage format. However, fueled by the ris

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Barros, Francisca, Beatriz Rodrigues, José Vieira, and Filipe Portela. "Pervasive Real-Time Analytical Framework—A Case Study on Car Parking Monitoring." Information 14, no. 11 (2023): 584. http://dx.doi.org/10.3390/info14110584.

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Due to the amount of data emerging, it is necessary to use an online analytical processing (OLAP) framework capable of responding to the needs of industries. Processes such as drill-down, roll-up, three-dimensional analysis, and data filtering are fundamental for the perception of information. This article demonstrates the OLAP framework developed as a valuable and effective solution in decision making. To develop an OLAP framework, it was necessary to create the extract, transform and load the (ETL) process, build a data warehouse, and develop the OLAP via cube.js. Finally, it was essential t

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Ali, Ben, and Samar Mouakket. "Integrating OLAP/SOLAP in E-Business Domains." Information Resources Management Journal 24, no. 3 (2011): 45–60. http://dx.doi.org/10.4018/irmj.2011070104.

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E-business domains have been considered killer domains for different data analysis techniques. Most researchers have examined data mining (DM) techniques to analyze the databases behind E-business websites. DM has shown interesting results, but this technique presents some restrictions concerning the content of the database and the level of expertise of the users interpreting the results. In this paper, the authors show that successful and more sophisticated results can be obtained using other analysis techniques, such as Online Analytical Processing (OLAP) and Spatial OLAP (SOLAP). Thus, the

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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 (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 produ

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Jala Aghazada. "ARRANGEMENT AND MODULATION OF ETL PROCESS IN THE STORAGE." Science Review, no. 1(28) (January 31, 2020): 3–8. http://dx.doi.org/10.31435/rsglobal_sr/31012020/6866.

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    Data warehouse (DW) is the basis of systems for operational data analysis (OLAP-Online Analytical Processing). Data extracted from different sources transforms and load in DW. Proper organization of this process, which is called ETL (Extract, Transform, Load) has important significance in creation of DW and analytical data processing. Forms of organization, methods of realization and modeling of ETL processes are considered in this paper.   

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Oukid, Lamia, Omar Boussaid, Nadjia Benblidia, and Fadila Bentayeb. "TLabel." International Journal of Data Warehousing and Mining 12, no. 4 (2016): 54–74. http://dx.doi.org/10.4018/ijdwm.2016100103.

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Data Warehousing technologies and On-Line Analytical Processing (OLAP) feature a wide range of techniques for the analysis of structured data. However, these techniques are inadequate when it comes to analyzing textual data. Indeed, classical aggregation operators have earned their spurs in the online analysis of numerical data, but are unsuitable for the analysis of textual data. To alleviate this shortcoming, on-line analytical processing in text cubes requires new analysis operators adapted to textual data. In this paper, the authors propose a new aggregation operator named Text Label (TLab

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ZHU, YOUWEN, LIUSHENG HUANG, TSUYOSHI TAKAGI, and MINGWU ZHANG. "PRIVACY-PRESERVING OLAP FOR ACCURATE ANSWER." Journal of Circuits, Systems and Computers 21, no. 01 (2012): 1250009. http://dx.doi.org/10.1142/s0218126612500090.

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Recently, growing privacy concerns have received more and more attention and it becomes a significant topic on how to preserve private-sensitive information from being violated in distributed cooperative computation. In this paper, we first propose a novel-general privacy-preserving online analytical processing model based on secure multiparty computation. Then, based on the new model, two schemes to privacy-preserving count aggregate query over both horizontally partitioned data and vertically partitioned data are proposed. Additionally, we also propose several efficient subprotocols that ser

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Akbar, Ricky, Elsha Yuliani, Qisty Mawaddah, and Fikri Ardhana. "Analisis Data Penjualan Perusahaan Detergen XYZ dengan Aplikasi Zoho Reporting Menggunakan Metode OLAP (Online Analytycal Processing)." Jurnal Edukasi dan Penelitian Informatika (JEPIN) 3, no. 1 (2017): 71. http://dx.doi.org/10.26418/jp.v3i1.20200.

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Sales Channel atau saluran penjualan merupakan salah satu hal yang harus diperhatikan oleh perusahaan. Sales channel yang beragam memungkin perusahaan untuk memperbesar keuntungan mereka, sales channel online misalnya dengan sales channel ini perusahaan dapat memperluas lokasi pemasaran keseluruh negara-negara di dunia. Perusahaan yang memiliki sales channel yang banyak dan memproduksi barang yang biasa digunakan sehari-hari, memiliki data pelanggan yang sangat besar diberbagai belahan dunia. Prediksi jumlah penjualan produk di masing-masing negara berdasarkan sales channel yang digunkan perus

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Qahhariana, Anna, and Imas Sukaesih Sitanggang. "Peningkatan Kinerja Sistem Spatial Online Analytical Processing (SOLAP) Titik Panas Kebakaran Hutan." Jurnal Ilmu Komputer dan Agri-Informatika 5, no. 1 (2018): 21. http://dx.doi.org/10.29244/jika.5.1.21-30.

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Data histori titik panas sebagai salah satu indikator kebakaran hutan dan lahan dapat dikelola dengan teknologi data warehouse dan sistem spatial online analytical processing (SOLAP). Pada penelitian sebelumnya telah dilakukan peningkatan kinerja terhadap sistem tersebut sehingga titik panas yang mampu dihasilkan meningkat menjadi 1500 titik. Penelitian ini bertujuan untuk meningkatkan kinerja sistem SOLAP data titik panas yang telah dibangun dalam penelitian sebelumnya. Peningkatan kinerja meliputi konfigurasi dari sisi perangkat lunak seperti peningkatan Java runtime environment (JRE), penin

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Redouane, Esbai, Hakkou Soufiane, and Achraf Habri Mohamed. "Modeling and automatic generation of data warehouse using model-driven transformation in business intelligence process." Modeling and automatic generation of data warehouse using model-driven transformation in business intelligence process 30, no. 3 (2023): 866–1874. https://doi.org/10.11591/ijeecs.v30.i3.pp1866-1874.

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The work presented in this paper focuses on the modeling and implementation of business intelligence processes, specifically how to apply model-driven architecture (MDA) throughout the entire development process of a data warehouse to automatically generate the multidimensional schema. As a result, this work specifies different rules for automating the process of obtaining an online analytical processing (OLAP) cube and implementing it using a collection of metamodels and automatic transformations. The data warehouse relational and OLAP cube models are then created using a model transformation

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Tremblay, Monica Chiarini, and Alan R. Hevner. "Missing Data in OLAP Cubes." Journal of Database Management 32, no. 3 (2021): 1–28. http://dx.doi.org/10.4018/jdm.2021070101.

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Online analytical processing (OLAP) engines display aggregated data to help business analysts compare data, observe trends, and make decisions. Issues of data quality and, in particular, issues with missing data impact the quality of the information. Key decision-makers who rely on these data typically make decisions based on what they assume to be all the available data. The authors investigate three approaches to dealing with missing data: 1) ignore missing data, 2) show missing data explicitly (e.g., as unknown data values), and 3) design mitigation algorithms for missing data (e.g., alloca

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Salmam, Fatima Zahra, Mohamed Fakir, and Rahhal Errattahi. "Prediction in OLAP Data Cubes." Journal of Information & Knowledge Management 15, no. 02 (2016): 1650022. http://dx.doi.org/10.1142/s0219649216500222.

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Online analytical processing (OLAP) provides tools to explore data cubes in order to extract the interesting information, it refers to techniques used to query, visualise and synthesise the multidimensional data. Nevertheless OLAP is limited on visualisation, structuring and exploring manually the data cubes. On the other side, data mining allows algorithms that offer automatic knowledge extraction, such as classification, explanation and prediction algorithms. However, OLAP is not capable of explaining and predicting events from existing data; therefore, it is possible to make a more efficien

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