Relevant bibliographies by topics / Data Warehousing and Online Analytical Processing

Academic literature on the topic 'Data Warehousing and Online Analytical Processing'

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Published: 27 July 2024
Last updated: 29 July 2024

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Journal articles on the topic "Data Warehousing and Online Analytical Processing"

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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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Song, Yanan, and Xiaolong Hua. "Implementation of Data Mining Technology in Bonded Warehouse Inbound and Outbound Goods Trade." Journal of Organizational and End User Computing 34, no. 3 (May 2022): 1–18. http://dx.doi.org/10.4018/joeuc.291511.

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For the taxed goods, the actual freight is generally determined by multiplying the allocated freight for each KG and actual outgoing weight based on the outgoing order number on the outgoing bill. Considering the conventional logistics is insufficient to cope with the rapid response of e-commerce orders to logistics requirements, this work discussed the implementation of data mining technology in bonded warehouse inbound and outbound goods trade. Specifically, a bonded warehouse decision-making system with data warehouse, conceptual model, online analytical processing system, human-computer interaction module and WEB data sharing platform was developed. The statistical query module can be used to perform statistics and queries on warehousing operations. After the optimization of the whole warehousing business process, it only takes 19.1 hours to get the actual freight, which is nearly one third less than the time before optimization. This study could create a better environment for the development of China's processing trade.
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Salman, Ban, Nada M. Alhakkak, and Mustafa Musa Jaber. "Football Player Decision Support System Baghdad-City as a Case Study." International Journal of Engineering & Technology 7, no. 3.20 (September 1, 2018): 406. http://dx.doi.org/10.14419/ijet.v7i3.20.20582.

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Decision support system (DSS) is an area of information systems (IS) discipline which focuses on supporting decision-making. DSS includes personal decision support systems, executive information systems, online analytical processing systems, data warehousing, business intelligence, and group support systems. This paper introduced the implementation of a DSS related to football players with a case study.
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Fong, Joseph, Qing Li, and Shi-Ming Huang. "Universal Data Warehousing Based on a Meta-Data Modeling Approach." International Journal of Cooperative Information Systems 12, no. 03 (September 2003): 325–63. http://dx.doi.org/10.1142/s0218843003000772.

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Data warehouse contains vast amount of data to support complex queries of various Decision Support Systems (DSSs). It needs to store materialized views of data, which must be available consistently and instantaneously. Using a frame metadata model, this paper presents an architecture of a universal data warehousing with different data models. The frame metadata model represents the metadata of a data warehouse, which structures an application domain into classes, and integrates schemas of heterogeneous databases by capturing their semantics. A star schema is derived from user requirements based on the integrated schema, catalogued in the metadata, which stores the schema of relational database (RDB) and object-oriented database (OODB). Data materialization between RDB and OODB is achieved by unloading source database into sequential file and reloading into target database, through which an object relational view can be defined so as to allow the users to obtain the same warehouse view in different data models simultaneously. We describe our procedures of building the relational view of star schema by multidimensional SQL query, and the object oriented view of the data warehouse by Online Analytical Processing (OLAP) through method call, derived from the integrated schema. To validate our work, an application prototype system has been developed in a product sales data warehousing domain based on this approach.
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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 and query reporting. The information in the form of chart reporting consists of the load distribution chart based on the repetition of time, distribution chart on the area, the substation region chart and the electric load usage chart. The results of the OLAP process show the development of electric load distribution, as well as the analysis of information on the load of electric power consumption and become an alternative in presenting information related to peak load.
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Bhukya, Raghuram. "Generalization Driven Fuzzy Classification Rules Extraction using OLAM Data Cubes." International Journal of Engineering and Computer Science 9, no. 2 (February 28, 2020): 24962–69. http://dx.doi.org/10.18535/ijecs/v9i2.4444.

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An fuzzy classification rules extraction model for online analytical mining (OLAM) was explained in this article. The efficient integration of the concept of data warehousing, online analytical processing (OLAP) and data mining systems converges to OLAM results in an efficient decision support system. Even after associative classification proved as most efficient classification technique there is a lack of associative classification proposals in field of OLAM. While most of existing data cube models claims their superiority over other the fuzzy multidimensional data cubes proved to be more intuitive in user perspective and effectively manage data imprecision. Considering these factors, in this paper we propose an associative classification model which can perform classification over fuzzy data cubes. Our method aimed to improve accuracy and intuitive ness of classification model using fuzzy concepts and hierarchical relations. We also proposed a generalization-based criterion for ranking associative classification rules to improve classifier accuracy. The model accuracy tested on UCI standard database.
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Camilovic, Dragana, Dragana Becejski-Vujaklija, and Natasa Gospic. "A call detail records data mart: Data modeling and OLAP analysis." Computer Science and Information Systems 6, no. 2 (2009): 87–110. http://dx.doi.org/10.2298/csis0902087c.

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In order to succeed in the market, telecommunications companies are not competing solely on price. They have to expand their services based on their knowledge of customers' needs gained through the use of call detail records (CDR) and customer demographics. All the data should be stored together in the CDR data mart. The paper covers the topic of its design and development in detail and especially focuses on the conceptual/logical/physical trilogy. Some other design problems are also discussed. An important area is the problem involving time. This is why the implication of time in data warehousing is carefully considered. The CDR data mart provides the platform for Online Analytical Processing (OLAP) analysis. As it is presented in this paper, an OLAP system can help the telecommunications company to get better insight into its customers' behavior and improve its marketing campaigns and pricing strategies.
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Liu, Dun Nan, Xin Fan Jiang, and Si Yuan Zhang. "Operating Analysis and Data Mining System for Power Grid Dispatching." Advanced Materials Research 787 (September 2013): 611–17. http://dx.doi.org/10.4028/www.scientific.net/amr.787.611.

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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, but at present there is no special method for the management of operating data resource. This paper introduces the operating analysis and data mining system for power grid dispatching. The technique of data warehousing online analytical processing has been used to manage and analysis the great capacity of data. This analysis system is based on the real-time data of the power grid, to dig out the potential rule of the power grid operating. This system also provides a research platform for the dispatchers, help to improve the JIT (Just in Time) management of power system.
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Oukid, Lamia, Omar Boussaid, Nadjia Benblidia, and Fadila Bentayeb. "TLabel." International Journal of Data Warehousing and Mining 12, no. 4 (October 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 (TLabel), based on text categorization. Their operator aggregates textual data in several classes of documents. Each class is associated with a label that represents the semantic content of the textual data of the class. TLabel is founded on a tailoring of text mining techniques to OLAP. To validate their operator, the authors perform an experimental study and the preliminary results show the interest of their approach for Text OLAP.
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Venkatakrishnan, Ramesh. "Design, Implementation, and Assessment of Innovative Data Warehousing; Extract, Transformation, and Load(ETL); and Online Analytical Processing(OLAP) on BI." International Journal of Database Management Systems 12, no. 3 (June 30, 2020): 1–6. http://dx.doi.org/10.5121/ijdms.2020.12301.

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Dissertations / Theses on the topic "Data Warehousing and Online Analytical Processing"

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Koylu, Caglar. "A Case Study In Weather Pattern Searching Using A Spatial Data Warehouse Model." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/2/12609573/index.pdf.

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Data warehousing and Online Analytical Processing (OLAP) technology has been used to access, visualize and analyze multidimensional, aggregated, and summarized data. Large part of data contains spatial components. Thus, these spatial components convey valuable information and must be included in exploration and analysis phases of a spatial decision support system (SDSS). On the other hand, Geographic Information Systems (GISs) provide a wide range of tools to analyze spatial phenomena and therefore must be included in the analysis phases of a decision support system (DSS). In this regard, this study aims to search for answers to the problem how to design a spatially enabled data warehouse architecture in order to support spatio-temporal data analysis and exploration of multidimensional data. Consequently, in this study, the concepts of OLAP and GISs are synthesized in an integrated fashion to maximize the benefits generated from the strengths of both systems by building a spatial data warehouse model. In this context, a multidimensional spatio-temporal data model is proposed as a result of this synthesis. This model addresses the integration problem of spatial, non-spatial and temporal data and facilitates spatial data exploration and analysis. The model is evaluated by implementing a case study in weather pattern searching.
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Reil, Michael J., T. George Bartlett, and Kevin Henry. "REAL TIME DATA WAREHOUSING AND ON LINE ANALYTICAL PROCESSING AT ABERDEEN TEST CENTER." International Foundation for Telemetering, 2006. http://hdl.handle.net/10150/604257.

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ITC/USA 2006 Conference Proceedings / The Forty-Second Annual International Telemetering Conference and Technical Exhibition / October 23-26, 2006 / Town and Country Resort & Convention Center, San Diego, California
This paper is a follow on to a paper presented at the 2005 International Telemetry Conference by Dr. Samuel Harley et. al., titled Data, Information, and Knowledge Management. This paper will describe new techniques and provide further detail into the inner workings of the VISION (Versatile Information System – Integrated, Online) Engineering Performance Data Mart.
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Leonardi, Luca <1983&gt. "A framework for trajectory data warehousing and visual OLAP analysis." Doctoral thesis, Università Ca' Foscari Venezia, 2012. http://hdl.handle.net/10579/1237.

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Questo lavoro di tesi vuole definire un framework per un data warehouse di traiettorie, ovvero un data warehouse capace di contenere informazioni aggregate relative a traiettorie di oggetti, e che offra operazioni OLAP visuali per la loro analisi. Il modello include sia una dimensione temporale che una spaziale, che ne assicurano flessibilità, rendendolo in grado di gestire sia oggetti che si muovono liberamente o seguendo dei vincoli. Queste dimensioni, e le gerarchie associate, riflettono la struttura degli oggetti stessi e dell’ambiente in cui si muovono. Il framework proposto include anche una interfaccia visuale che permette di navigare in modo semplice tra le misure aggregate attraverso query OLAP a differenti granularità. Per evidenziare l’utilità del sistema proposto, proporremo due casi di studio, che si differenziano per il tipo di oggetti studiati, le informazioni disponibili su di loro e al tipo di vincoli sui loro movimenti.
This thesis is aimed at designing a formal framework for modelling a Trajectory Data Warehouse, namely a data warehouse able to store aggregate information related to trajectories of moving objects, which also offers visual OLAP operations for data analysis. The TDW model includes both a temporal and a spatial dimensions, that ensure flexibility, making our model general enough to deal with objects that are either completely free or constrained in their movements. This dimensions and associated hierarchies reflect the structure of the objects and of the environment in which they travel. Our framework also includes a visual interface for easily navigating aggregate measures obtained from OLAP queries at different granularities. To highlight the usefulness of the framework, we propose two different case studies, differing for the type of the observed moving objects, the available information about the objects, and their movement constraints.
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Ives, Zachary G. "Efficient query processing for data integration /." Thesis, Connect to this title online; UW restricted, 2002. http://hdl.handle.net/1773/6864.

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Marquardt, Justus. "Metadatendesign zur Integration von Online Analytical Processing in das Wissensmanagement /." Hamburg : Kovač, 2008. http://www.verlagdrkovac.de/978-3-8300-3598-5.htm.

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Marquardt, Justus. "Metadatendesign zur Integration von online analytical processing in das Wissensmanagement." Hamburg Kovač, 2007. http://www.verlagdrkovac.de/978-3-8300-3598-5.htm.

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Schwarz, Holger. "Integration von Data-Mining und online analytical processing : eine Analyse von Datenschemata, Systemarchitekturen und Optimierungsstrategien /." [S.l. : s.n.], 2003. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB10720634.

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Westerlund, Elisabeth, and Hanna Persson. "Implementation of Business Intelligence Systems : A study of possibilities and difficulties in small IT-enterprises." Thesis, Uppsala universitet, Företagsekonomiska institutionen, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-255915.

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This thesis is written at the department of Business Studies at Uppsala University. The study addresses the differences in possibilities and difficulties of implementing business intelligence (BI)-systems among small IT-enterprises. BI-systems support enterprises in decision-making. To answer the aim of this thesis, theories regarding organizational factors determining a successful implementation of a BI-system were used. Theories regarding components of BI- systems, data warehouse (DW) and online analytical processing (OLAP) were also used. These components enable the decision-support provided by a BI-system. A qualitative study was performed, at four different IT-enterprises, to gather the empirical material. Interviews were performed with CEOs and additional employees at the enterprises. After the empirical material was gathered an analysis was performed to draw conclusion regarding the research topic. The study has concluded that there are differences in possibilities and difficulties of implementing BI-systems among small IT-enterprises. A difference among the enterprises is the perceived ability to finance an implementation. Another difference is in the managerial- and organizational support of an implementation, but also in the business need of using a BI- system in decision-making. There are also differences in how the enterprises use a DW. Not all enterprises benefits from the ability of a DW to manage complex and large amounts of data, neither from the advanced analysis performed by OLAP. The enterprises thus need to examine further if the use of a BI-system is beneficial and would be used successfully in their company.
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Techaplahetvanich, Kesaraporn. "A visualization framework for exploring correlations among atributes of a large dataset and its applications in data mining." University of Western Australia. School of Computer Science and Software Engineering, 2007. http://theses.library.uwa.edu.au/adt-WU2007.0216.

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[Truncated abstract] Many databases in scientific and business applications have grown exponentially in size in recent years. Accessing and using databases is no longer a specialized activity as more and more ordinary users without any specialized knowledge are trying to gain information from databases. Both expert and ordinary users face significant challenges in understanding the information stored in databases. The databases are so large in most cases that it is impossible to gain useful information by inspecting data tables, which are the most common form of storing data in relational databases. Visualization has emerged as one of the most important techniques for exploring data stored in large databases. Appropriate visualization techniques can reveal trends, correlations and associations in data that are very difficult to understand from a textual representation of the data. This thesis presents several new frameworks for data visualization and visual data mining. The first technique, VisEx, is useful for visual exploration of large multi-attribute datasets and especially for exploring the correlations among the attributes in such datasets. Most previous visualization techniques can display correlations among two or three attributes at a time without excessive screen clutter. ... Although many algorithms for mining association rules have been researched extensively, they do not incorporate users in the process and most of them generate a large number of association rules. It is quite often difficult for the user to analyze a large number of rules to identify a small subset of rules that is of importance to the user. In this thesis I present a framework for the user to interactively mine association rules visually. Another challenging task in data mining is to understand the correlations among the mined association rules. It is often difficult to identify a relevant subset of association rules from a large number of mined rules. A further contribution of this thesis is a simple framework in the VisAR system that allows the user to explore a large number of association rules visually. A variety of businesses have adopted new technologies for storing large amounts of data. Analysis of historical data quite often offers new insights into business processes that may increase productivity and profit. On-line analytical processing (OLAP) has become a powerful tool for business analysts to explore historical data. Effective visualization techniques are very important for supporting OLAP technology. A new technique for the visual exploration of OLAP data cubes is also presented in this thesis.
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Jakawat, Wararat. "Graphs enriched by Cubes (GreC) : a new approach for OLAP on information networks." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSE2087/document.

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L'analyse en ligne OLAP (Online Analytical Processing) est une des technologies les plus importantes dans les entrepôts de données, elle permet l'analyse multidimensionnelle de données. Cela correspond à un outil d'analyse puissant, tout en étant flexible en terme d'utilisation pour naviguer dans les données, plus ou moins en profondeur. OLAP a été le sujet de différentes améliorations et extensions, avec sans cesse de nouveaux problèmes en lien avec le domaine et les données, par exemple le multimedia, les données spatiales, les données séquentielles, etc. A l'origine, OLAP a été introduit pour analyser des données structurées que l'on peut qualifier de classiques. Cependant, l'émergence des réseaux d'information induit alors un nouveau domaine intéressant qu'il convient d'explorer. Extraire des connaissances à partir de larges réseaux constitue une tâche complexe et non évidente. Ainsi, l'analyse OLAP peut être une bonne alternative pour observer les données avec certains points de vue. Différents types de réseaux d'information peuvent aider les utilisateurs dans différentes activités, en fonction de différents domaines. Ici, nous focalisons notre attention sur les réseaux d'informations bibliographiques construits à partir des bases de données bibliographiques. Ces données permettent d'analyser non seulement la production scientifique, mais également les collaborations entre auteurs. Il existe différents travaux qui proposent d'avoir recours aux technologies OLAP pour les réseaux d'information, nommé ``graph OLAP". Beaucoup de techniques se basent sur ce qu'on peut appeler cube de graphes. Dans cette thèse, nous proposons une nouvelle approche de “graph OLAP” que nous appelons “Graphes enrichis par des Cubes” (GreC). Notre proposition consiste à enrichir les graphes avec des cubes plutôt que de construire des cubes de graphes. En effet, les noeuds et/ou les arêtes du réseau considéré sont décrits par des cubes de données. Cela permet des analyses intéressantes pour l'utilisateur qui peut naviguer au sein d'un graphe enrichi de cubes selon différents niveaux d'analyse, avec des opérateurs dédiés. En outre, notons quatre principaux aspects dans GreC. Premièrement, GreC considère la structure du réseau afin de permettre des opérations OLAP topologiques, et pas seulement des opérations OLAP classiques et informationnelles. Deuxièmement, GreC propose une vision globale du graphe avec des informations multidimensionnelles. Troisièmement, le problème de dimension à évolution lente est pris en charge dans le cadre de l'exploration du réseau. Quatrièmement, et dernièrement, GreC permet l'analyse de données avec une évolution du réseau parce que notre approche permet d'observer la dynamique à travers la dimension temporelle qui peut être présente dans les cubes pour la description des noeuds et/ou arêtes. Pour évaluer GreC, nous avons implémenté notre approche et mené une étude expérimentale sur des jeux de données réelles pour montrer l'intérêt de notre approche. L'approche GreC comprend différents algorithmes. Nous avons validé de manière expérimentale la pertinence de nos algorithmes et montrons leurs performances
Online Analytical Processing (OLAP) is one of the most important technologies in data warehouse systems, which enables multidimensional analysis of data. It represents a very powerful and flexible analysis tool to manage within the data deeply by operating computation. OLAP has been the subject of improvements and extensions across the board with every new problem concerning domain and data; for instance, multimedia, spatial data, sequence data and etc. Basically, OLAP was introduced to analyze classical structured data. However, information networks are yet another interesting domain. Extracting knowledge inside large networks is a complex task and too big to be comprehensive. Therefore, OLAP analysis could be a good idea to look at a more compressed view. Many kinds of information networks can help users with various activities according to different domains. In this scenario, we further consider bibliographic networks formed on the bibliographic databases. This data allows analyzing not only the productions but also the collaborations between authors. There are research works and proposals that try to use OLAP technologies for information networks and it is called Graph OLAP. Many Graph OLAP techniques are based on a cube of graphs.In this thesis, we propose a new approach for Graph OLAP that is graphs enriched by cubes (GreC). In a different and complementary way, our proposal consists in enriching graphs with cubes. Indeed, the nodes or/and edges of the considered network are described by a cube. It allows interesting analyzes for the user who can navigate within a graph enriched by cubes according to different granularity levels, with dedicated operators. In addition, there are four main aspects in GreC. First, GreC takes into account the structure of network in order to do topological OLAP operations and not only classical or informational OLAP operations. Second, GreC has a global view of a network considered with multidimensional information. Third, the slowly changing dimension problem is taken into account in order to explore a network. Lastly, GreC allows data analysis for the evolution of a network because our approach allows observing the evolution through the time dimensions in the cubes.To evaluate GreC, we implemented our approach and performed an experimental study on a real bibliographic dataset to show the interest of our proposal. GreC approach includes different algorithms. Therefore, we also validated the relevance and the performances of our algorithms experimentally
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Books on the topic "Data Warehousing and Online Analytical Processing"

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ACM, International Workshop on Data Warehousing and OLAP (1st 1998 Washington D. C. ). DOLAP '98: ACM First International Workshop on Data Warehousing and OLAP in conjunction with the Seventh International Conference on Information and Knowledge Management (CIKM '98), Nov. 7, 1998, Washington, D.C., USA. New York: ACM Press, 1999.

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Preserving Privacy in On-Line Analytical Processing (OLAP) (Advances in Information Security). Springer, 2006.

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Jarke, Matthias, Maurizio Lenzerini, Yannis Vassiliou, and Panos Vassiliadis. Fundamentals of Data Warehouses. Springer London, Limited, 2013.

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Jarke, Matthias, Maurizio Lenzerini, Yannis Vassiliou, and Panos Vassiliadis. Fundamentals of Data Warehouses. 2nd ed. Springer, 2003.

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“Data Mining Concepts & Techniques”. 3rd ed. Morgan Kaufmann Publishers, 2011.

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Wang, Lingyu, Sushil Jajodia, and Duminda Wijesekera. Preserving Privacy in on-Line Analytical Processing (OLAP). Springer London, Limited, 2007.

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Wang, Lingyu, Sushil Jajodia, and Duminda Wijesekera. Preserving Privacy in On-Line Analytical Processing. Springer, 2010.

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Bibliographic post-processing with the TIS intelligent gateway: Analytical and communication capabilities. [Alexandria, Va.]: DTIC, 1986.

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HBase: The Definitive Guide. 2nd ed. O'Reilly Media, 2020.

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HBase: The Definitive Guide. O'Reilly Media, 2011.

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Book chapters on the topic "Data Warehousing and Online Analytical Processing"

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Maedche, Alexander, Andreas Hotho, and Markus Wiese. "Enhancing Preprocessing in Data-Intensive Domains using Online-Analytical Processing." In Data Warehousing and Knowledge Discovery, 258–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-44466-1_25.

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Kehlenbeck, Matthias, and Michael H. Breitner. "Ontology-Based Exchange and Immediate Application of Business Calculation Definitions for Online Analytical Processing." In Data Warehousing and Knowledge Discovery, 298–311. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03730-6_24.

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Taniar, David, and Wenny Rahayu. "Online Analytical Processing (OLAP)." In Data-Centric Systems and Applications, 501–39. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81979-8_19.

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Lehner, Wolfgang. "‘Data Warehouse’ und ‘Online Analytical Processing’." In Multidimensionale Datenbanksysteme, 28–43. Wiesbaden: Vieweg+Teubner Verlag, 1999. http://dx.doi.org/10.1007/978-3-322-86766-7_2.

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Johnson, Diane. "Implementing a Hybrid Online Analytical Processing (HOLAP) Solution." In Data Management, 747–53. 3rd ed. Boca Raton: Auerbach Publications, 2021. http://dx.doi.org/10.1201/9780429114878-69.

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Hughes, Robert C. "Online Analytical Processing and the OLAP Cube Multidimensional Database." In Human Capital Systems, Analytics, and Data Mining, 103–26. Boca Raton : CRC Press, 2018. | Series: Chapman & Hall/CRC data mining & knowledge discovery series ; 46: Chapman and Hall/CRC, 2018. http://dx.doi.org/10.1201/9781315153650-6.

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Kämpgen, Benedikt. "DC Proposal: Online Analytical Processing of Statistical Linked Data." In The Semantic Web – ISWC 2011, 301–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25093-4_22.

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Pei, Jian. "A General Model for Online Analytical Processing of Complex Data." In Conceptual Modeling - ER 2003, 321–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39648-2_26.

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Inoue, Hiroyuki, Toshiyuki Amagasa, and Hiroyuki Kitagawa. "An ETL Framework for Online Analytical Processing of Linked Open Data." In Web-Age Information Management, 111–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38562-9_12.

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Di Martino, Sergio, Sandro Bimonte, Michela Bertolotto, Filomena Ferrucci, and Vincenza Leano. "Spatial OnLine Analytical Processing of Geographic Data through the Google Earth Interface." In Geocomputation, Sustainability and Environmental Planning, 163–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19733-8_10.

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Conference papers on the topic "Data Warehousing and Online Analytical Processing"

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Correia, Jose, Maribel Yasmina Santos, Carlos Costa, and Carina Andrade. "Fast Online Analytical Processing for Big Data Warehousing." In 2018 International Conference on Intelligent Systems (IS). IEEE, 2018. http://dx.doi.org/10.1109/is.2018.8710583.

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Xie, Zhongle, Hongbin Ying, Cong Yue, Meihui Zhang, Gang Chen, and Beng Chin Ooi. "Cool, a COhort OnLine analytical processing system." In 2020 IEEE 36th International Conference on Data Engineering (ICDE). IEEE, 2020. http://dx.doi.org/10.1109/icde48307.2020.00056.

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Chen, Chen, Xifeng Yan, Feida Zhu, Jiawei Han, and Philip S. Yu. "Graph OLAP: Towards Online Analytical Processing on Graphs." In 2008 Eighth IEEE International Conference on Data Mining (ICDM). IEEE, 2008. http://dx.doi.org/10.1109/icdm.2008.30.

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Inokuchi, Akihiro, and Koichi Takeda. "A method for online analytical processing of text data." In the sixteenth ACM conference. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1321440.1321506.

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Worth, Aidan, Aris Televantos, Nicos Evmides, Michalis P. Michaelides, and Herodotos Herodotou. "Online Analytical Processing of Port Calls for Decision Support." In 2022 23rd IEEE International Conference on Mobile Data Management (MDM). IEEE, 2022. http://dx.doi.org/10.1109/mdm55031.2022.00095.

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Aggarwal, Charu C., and Philip S. Yu. "LOCUST: An Online Analytical Processing Framework for High Dimensional Classification of Data Streams." In 2008 IEEE 24th International Conference on Data Engineering (ICDE 2008). IEEE, 2008. http://dx.doi.org/10.1109/icde.2008.4497451.

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Freitas, Charles, Roberta Gouveia, and Adenilton Silva. "Online Analytical Processing em Ambientes Virtuais de Aprendizagem da Educação a Distância." In IV Workshop de Desafios da Computação aplicada à Educação. Sociedade Brasileira de Computação - SBC, 2020. http://dx.doi.org/10.5753/desafie.2015.10035.

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Este artigo apresenta o processo Knowledge Discovery in Databases (KDD) aplicado no contexto da Educação a Distância (EaD) e dos ambientes virtuais de aprendizagem. O objetivo consiste em aplicar o processo KDD para traçar o perfil da EaD no Brasil e efetuar uma análise acurada dos cursos realizados em ambientes e-learning, bem como revelar os principais desafios da área. A metodologia consiste em coletar dados abertos governamentais de alta granularidade dos sistemas Universidade Aberta do Brasil (UAB) e e-MEC, em seguida aplicar o processo ETL, organizar e integrar os dados em um Data Warehouse e aplicar as tecnologias OLAP, visando obter uma visão contextualizada e realista da modalidade a distância no âmbito nacional.
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Tsakiridis, Sotirios, Alkiviadis Tsimpiris, Athanasios Angeioplastis, Nikolaos Papaioannou, and Dimitrios Varsamis. "Analytics with Oracle APEX for Enhanced Data Warehouse Management: A Case Study of a Greek Soft Drinks Company." In 43rd International Conference on Organizational Science Development. University of Maribor Press, 2024. http://dx.doi.org/10.18690/um.fov.3.2024.73.

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This research paper examines the strategic deployment of Oracle APEX by a prominent Greek soft drinks manufacturing enterprise for the enhancement of data warehouse management spanning the period from 2018 to 2022. The integration of Oracle APEX, renowned for its low-code application development capabilities, has emerged as a pivotal catalyst in optimizing data processing workflows, elevating analytical functionalities, and cultivating streamlined decision-making processes within the organization's data ecosystem. This article delves into the specific benefits and outcomes derived from the adoption of Oracle APEX in the context of data warehousing, shedding light on the transformative impact on the company's operations.
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Sviridov, Mikhail, Anton Mosin, Sergey Lebedev, and Ron Thompson. "VENDOR-NEUTRAL STOCHASTIC INVERSION OF LWD DEEP AZIMUTHAL RESISTIVITY DATA AS A STEP TOWARD EFFICIENCY STANDARDIZATION OF GEOSTEERING SERVICES." In 2021 SPWLA 62nd Annual Logging Symposium Online. Society of Petrophysicists and Well Log Analysts, 2021. http://dx.doi.org/10.30632/spwla-2021-0103.

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While proactive geosteering, special inversion algorithms are used to process the readings of logging-while-drilling resistivity tools in real-time and provide oil field operators with formation models to make informed steering decisions. Currently, there is no industry standard for inversion deliverables and corresponding quality indicators because major tool vendors develop their own device-specific algorithms and use them internally. This paper presents the first implementation of vendor-neutral inversion approach applicable for any induction resistivity tool and enabling operators to standardize the efficiency of various geosteering services. The necessity of such universal inversion approach was inspired by the activity of LWD Deep Azimuthal Resistivity Services Standardization Workgroup initiated by SPWLA Resistivity Special Interest Group in 2016. Proposed inversion algorithm utilizes a 1D layer-cake formation model and is performed interval-by-interval. The following model parameters can be determined: horizontal and vertical resistivities of each layer, positions of layer boundaries, and formation dip. The inversion can support arbitrary deep azimuthal induction resistivity tool with coaxial, tilted, or orthogonal transmitting and receiving antennas. The inversion is purely data-driven; it works in automatic mode and provides fully unbiased results obtained from tool readings only. The algorithm is based on statistical reversible-jump Markov chain Monte Carlo method that does not require any predefined assumptions about the formation structure and enables searching of models explaining the data even if the number of layers in the model is unknown. To globalize search, the algorithm runs several Markov chains capable of exchanging their states between one another to move from the vicinity of local minimum to more perspective domain of model parameter space. While execution, the inversion keeps all models it is dealing with to estimate the resolution accuracy of formation parameters and generate several quality indicators. Eventually, these indicators are delivered together with recovered resistivity models to help operators with the evaluation of inversion results reliability. To ensure high performance of the inversion, a fast and accurate semi-analytical forward solver is employed to compute required responses of a tool with specific geometry and their derivatives with respect to any parameter of multi-layered model. Moreover, the reliance on the simultaneous evolution of multiple Markov chains makes the algorithm suitable for parallel execution that significantly decreases the computational time. Application of the proposed inversion is shown on a series of synthetic examples and field case studies such as navigating the well along the reservoir roof or near the oil-water-contact in oil sands. Inversion results for all scenarios confirm that the proposed algorithm can successfully evaluate formation model complexity, recover model parameters, and quantify their uncertainty within a reasonable computational time. Presented vendor-neutral stochastic approach to data processing leads to the standardization of the inversion output including the resistivity model and its quality indicators that helps operators to better understand capabilities of tools from different vendors and eventually make more confident geosteering decisions.
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Wang, Xinguang, Dong Li, Lei Zhang, Feng Zhang, Wenhao Wang, and Hui Gao. "A NOVEL METHOD FOR FORMATION DENSITY MEASUREMENT IN CASED WELLS." In 2021 SPWLA 62nd Annual Logging Symposium Online. Society of Petrophysicists and Well Log Analysts, 2021. http://dx.doi.org/10.30632/spwla-2021-0065.

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Density logging is a fundamental logging method of open-hole logging series. In cased wells, the formation is usually treated as a cylindrical multiple-layer model including borehole, casing pipe, cement, and original formation, producing more complicated logging response compared to open-hole wells. Several studies have indicated that it is feasible to measure formation density using a density logging tool in cased well under certain conditions, of which the key problem is to determine casing thickness, cement thickness and cement density. This study proposes a novel method to evaluate formation density behind casing using a three-detector density tool. Considering that the backscattered gamma is easily affected by the density behind the casing, especially when the casing thickness is small, a designed ratio of high and low energy window counts of the scattered gamma spectrum is used to calculate casing thickness, which improves the lower limit of the detection. After obtaining casing thickness, the cylindrical multiple-layer model of cased well can be simplified to a cylindrical three-layer model, consisting of cased borehole, cement, and the original formation. Subsequently, the analytical expressions of the thickness of the middle layer (cement) as well as the density of the outer layer (original formation) can be derived based on the logging geometric factor concept, G, which borrowing from electric logging. Consequently, the cement thickness and original formation density could be calculated independently. To demonstrate the feasibility of the proposed method, experimental data are measured in a group of calibration wells. The data processing results show that the proposed analytical model fit well with the experimental data. In addition, the application conditions of the novel method are discussed based on experimental data. Finally, several log examples illustrate that under suitable casing and cement conditions, the formation density calculated with the proposed method in cased borehole is in good agreement with the corresponding open-hole density.
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