Relevant bibliographies by topics / Business intelligence; data warehouse

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Business intelligence; data warehouse'

Author: Grafiati
Published: 4 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Business intelligence; data warehouse"

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

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Data warehouses are the most valuable assets of an organization and are basically used for critical business and decision-making purposes. Data from different sources is integrated into the data warehouse. Thus, security issues arise as data is moved from one place to another. Data warehouse security addresses the methodologies that can be used to secure the data warehouse by protecting information from being accessed by unauthorized users for maintaining the reliability of the data warehouse. A data warehouse invariably contains information which needs to be considered extremely sensitive and
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Spruit, Marco, and Catalina Sacu. "DWCMM: The Data Warehouse Capability Maturity Model." JUCS - Journal of Universal Computer Science 21, no. (11) (2015): 1508–34. https://doi.org/10.3217/jucs-021-11-1508.

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Data Warehouses and Business Intelligence have become popular fields of research in recent years. Unfortunately, in daily practice many Data Warehouse and Business Intelligence solutions still fail to help organizations make better decisions and increase their profitability, due to intransparent complexities and project interdependencies. In addition, emerging application domains such as Mobile Learning & Analytics heavily depend on a well-structured data foundation with a longitudinally prepared architecture. Therefore, this research presents the Data Warehouse Capability Maturity Model (
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Aljuwaiber, Abobakr. "Data Warehousing as Knowledge Pool : A Vital Component of Business Intelligence." International Journal of Computer Science, Engineering and Information Technology 12, no. 4 (2022): 21–26. http://dx.doi.org/10.5121/ijcseit.2022.12402.

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Increasing amounts of information and diverse formats have forced organizations to create large data repositories in response to the information explosion in the 21st century. As a result, the model of a data warehouse has been introduced to define a large data repository. The purpose of this article is to describe the principles of data warehousing in business and how it can enhance the generation of new knowledge throughout the organization. Definitions of data warehousing are considered and include methods of its use, namely query and data simulation. The steps required prior to transformin
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Rudy, Rudy. "Konsolidasi Data Warehouse untuk Aplikasi Business Intelligence." ComTech: Computer, Mathematics and Engineering Applications 3, no. 2 (2012): 841. http://dx.doi.org/10.21512/comtech.v3i2.2313.

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As the business competition is getting strong, corporate leaders need complete data that as a basis for determining future business strategies. Similarly with management of company "A", a pharmaceutical company which has three distribution companies. Each distribution company already has a data warehouse to generate reports for each of them. For business operational and corporate strategies, chairman PT "A" requires an integrated report, so analysis of data owned by the three distribution companies can be done in a full report to answer the problems faced by the managemet. Thus, data warehouse
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Gunduz, Derya, M. Ergul Azizler, and Emel Arslan. "Implementation Scenarios of Reporting from Data Warehouse for Business Intelligence." International Journal of Modeling and Optimization 5, no. 3 (2015): 211–15. http://dx.doi.org/10.7763/ijmo.2015.v5.464.

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Patrick, N. Nwinyokpugi, and Dumnamene Lah Fiito. "Business Intelligence Applications; sustaining Retail Businesses in Rivers State, Nigeria." International Journal of Multidisciplinary Research and Analysis 04, no. 03 (2021): 304–15. https://doi.org/10.47191/ijmra/v4-i3-13.

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The contemporary retail outlets are no more run by manual practices given the electronic nature of company to customers (C-C); customers to customers (C-C) transactions globally. The application of business intelligence has given an edge to retail outlets operation. This study therefore, strives to examine the relationship between business intelligence application and retail business sustainability in Rivers State, Nigeria. The study used descriptive research technique through the adoption of cross- sectional survey design. Nine judgmentally sampled retail outlets especially large scale malls
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Tešendić, Danijela, and Danijela Boberić Krstićev. "Business Intelligence in the Service of Libraries." Information Technology and Libraries 38, no. 4 (2019): 98–113. http://dx.doi.org/10.6017/ital.v38i4.10599.

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This paper describes implementation of business intelligence tools in the libraries. A complete procedure for building a data warehouse is described on the case study of the BISIS library management system. During development of a data warehouse model, user requirements about reporting are detected and structure of already existing transactional databases in the BISIS system is analysed. Based on this analysis, three data warehouse models have been proposed that would satisfy the requirements for analytical processing of data. The paper presents the usage of one OLAP tool, but the proposed dat
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Trninic, Jelica, Jovica Durkovic, and Lazar Rakovic. "Business intelligence as support to knowledge management." Perspectives of Innovations, Economics and Business 8, no. 2 (2011): 35–40. https://doi.org/10.15208/pieb.2011.26.

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  Knowledge management is becoming an increasingly important business resource not only in the development and innovation process, but also in securing an organization’s competitiveness and survival in the environment. In view of the fact that there is no full consent as regards adopting a universal definition, knowledge management can be regarded as a concept encompassing methods of simplifying, enhancing, sharing, distributing and creating knowledge within an organization. The dominant approach of contemporary business operations is based on business intelligence, which, including
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Nur Fauziah, Mia, Rudi Hartono, and Agus Supriatman. "PENGEMBANGAN DATA WAREHOUSE PADA APOTEK X UNTUK KEBUTUHAN BUSINESS INTELLIGENCE." JATI (Jurnal Mahasiswa Teknik Informatika) 8, no. 4 (2024): 8075–82. http://dx.doi.org/10.36040/jati.v8i4.10646.

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Perkembangan teknologi informasi ini menghasilkan data yang begitu melimpah. Informasi memiliki peran penting untuk sebuah perusahaan. Apotek X mengelola data transaksi dalam jumlah yang cukup banyak dalam kurun waktu lima tahun. Data transaksi penjualan yang begitu besar sehingga membutuhkan penyimpanan yang besar dan memiliki kesulitan dalam mengolah data untuk menjadikan sebuah laporan yang digunakan manajemen dalam proses pengambilan keputusan. Pengolahan laporan membutuhkan waktu yang lama karena masih menggunakan bantuan aplikasi pengolah data. Dari berbagai informasi data transaksi penj
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Anshari, Said Fadlan, and Sujacka Retno. "Penerapan Metode Nine-Step Kimball Dalam Pengolahan Data History Menggunakan Data Warehouse dan Business Intelligence." Jurnal Ilmu Komputer 16, no. 1 (2023): 69. http://dx.doi.org/10.24843/jik.2023.v16.i01.p07.

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Data warehouse dan business intelligence merupakan perpaduan teknologi informasi yang dapat dimanfaatkan oleh banyak perusahaan yang memiliki data histori dan data transaksi yang cukup besar untuk bisa selanjutnya diolah, seperti yang dimiliki oleh beberapa perusahaan waralaba. Dengan menggunakan metode nine-step Kimball sebagai metode pengembangan data warehouse-nya, seta aplikasi Tableau sebagai media visuailsasi dari hasil business intelligence-nya, perusahaan dapat melihat hasil pengolahan data histori dan data transaksi yang telah dihasilkan, yang berkaitan dengan fungsi bisnis penjualan
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Dissertations / Theses on the topic "Business intelligence; data warehouse"

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Tashakor, Ghazal. "Delivering Business Intelligence Performance by Data Warehouse and ETL Tuning." Thesis, Mittuniversitetet, Institutionen för informationsteknologi och medier, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-20062.

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Abstract The aim of this thesis is to show how numerous organizations such as CGI Consultant attempt to introduce BI-Solutions through IT and other operational methods in order to deal with large companies, which want to make their competitive market position stronger. This aim is achieved by Gap Analyzing in the BI roadmap and available Data Warehouses based on one of the company projects which were handed over to CGI from Lithuania. The fundamentals in achieving the BI-Solutions through IT, which has built the thesis methodology by research are, data warehousing, content analytics and perfor
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Šídlo, Petr. "Návrh projektu business intelligence." Master's thesis, Vysoká škola ekonomická v Praze, 2007. http://www.nusl.cz/ntk/nusl-15865.

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This dissertation titled Designing Project Business Intelligence focuses on data warehouse in a medium-sized company. The theoretical portion of the thesis describes the topic of data warehouse and dimensional modeling. In the first theoretical chapter, I compare and contrast two approaches to datawarehouse building - Bill Inmon's and Ralph Kimball's. Then, basic terminology used in the field, principles of dimensional modeling and various approaches of database use will be described. Furthermore, the thesis illustrates the role of the Mondrian system as a mediator between the relational datab
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Havránek, Denis. "Business Intelligence v pojišťovnictví." Master's thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-74868.

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The thesis focuses on the application of Business Intelligence technologies in the insurance area, aiming concretely at their use in insurance companies. The aim is to introduce and summarize the various processes and information needs that are part of an insurance company and the ways that business intelligence tools can support and improve those processes. To achieve this goal I describe and present the internal functioning of the main processes in insurance companies emphasizing on data examples and the concrete use of BI. Furthermore, I point out two specific examples of Business Intellige
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Issa, Carla Mounir. "Data warehouse applications in modern day business." CSUSB ScholarWorks, 2002. https://scholarworks.lib.csusb.edu/etd-project/2148.

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Data warehousing provides organizations with strategic tools to achieve the competitive advantage that organazations are constantly seeking. The use of tools such as data mining, indexing and summaries enables management to retrieve information and perform thorough analysis, planning and forcasting to meet the changes in the market environment. in addition, The data warehouse is providing security measures that, if properly implemented and planned, are helping organizations ensure that their data quality and validity remain intact.
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Černý, Lukáš. "Implementace Business intelligence řešení v podniku." Master's thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-72480.

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Since 1989, there rose many branches. One of them the company grounds with their work scope as ICT services, ICT trainings and system development. The households had started to use in huge the PCs and round 1992 joined WEB. The companies did start to ask for applications which would have been able to be in connection with the other branch offices and had been looking for such solutions that would have brought the new added value. There had been rising new bank systems, telecommunication, insurance, energy, industrial systems and the like. Today, we are dating 2011 and it is more than 20 year;
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Correia, André Ramos Jorge. "Dados, informação, conhecimento, o business intelligence e as suas motivações." Master's thesis, Faculdade de Ciências e Tecnologia, 2011. http://hdl.handle.net/10362/6286.

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática<br>O objectivo deste relatório é dar a conhecer, um possível percurso de carreira para um aluno que na entrada no mundo profissional, se interessou por sistemas de suporte à decisão. Descrevi a minha experiência profissional desde a entrada no curso de Engenharia Informática e as opções que fui tomando durante e depois do curso, que demonstram o interesse e tendência para esta área dentro das TI. Assim, o facto de após terminar o curso, ter trabalhado em diversas áreas nas três empresas que integrei, desde o desenvolviment
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Filipčík, Zdeněk. "Nástroje Business Intelligence jako Open Source." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-150123.

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This master's thesis focuses on the issues of selecting the Business Intelligence tools distributed under open source licenses. The main objective of this work is to compare the different instruments in all layers of the Business Intelligence architecture. The first part is focused on the definition of key concepts of the main topic. Provides necessary theoretical basis for understanding the context used in the practical part, which is dedicated to comparison tools realized according to the established methodology. These tools are selected and compared with predetermined criteria. Then each to
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Huňáček, Tomáš. "Návrh agilní metodiky pro Business Intelligence projekty." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-206981.

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This master's thesis deals with the topic of designing an agile methodology for Business Intelligence projects. The thesis presents the topic of Business Intelligence, methodologies for managing projects and methodologies for data warehouse development. It presents Scrum, BEAM* and Data Vault methodologies as well as approaches like pomodoro, Action Centered Leadership and a 40-hour work week. Based on synthesis of presented methodologies and approaches this thesis defines the methodology for managing Business Intelligence projects. The newly designed methodology HooBI is a minimal methodology
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Brandão, Filipe Ferreira. "Estágio TAP/Megasys - Data Warehouse & Reporting." Master's thesis, Instituto Superior de Economia e Gestão, 2014. http://hdl.handle.net/10400.5/12024.

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Mestrado em Gestão de Sistemas de Informação<br>A atividade de uma companhia aérea, envolvendo várias áreas operacionais, por vezes várias empresas, dá origem a diferentes sistemas de informação, consequentemente gerando um volume grande de dados. A análise desses dados é fundamental para maximizar a informação disponível e apoiar o processo de tomada de decisão. O Business Intelligence (BI) disponibiliza aos decisores, de maneira rápida e eficiente, a informação proveniente desses sistemas. A Megasis/TAP Portugal utiliza ferramentas da MicroStrategy que permitem o acesso, criação e partilha
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Beránková, Kateřina. "Návrh řešení Business Intelligence pro autodopravu." Master's thesis, Vysoká škola ekonomická v Praze, 2013. http://www.nusl.cz/ntk/nusl-197486.

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This thesis is focused on the design of Business Intelligence solution to the logistics sector. Its main goal is to enable the unnamed central-bohemian company, which deals with truck road transportation, to follow up and evaluate its data better. The theoretical part is focused on the basic principles of Business Intelligence and on the analysis of current market situation. The next section is dedicated to the specifics of this problematic in the logistics field. The practical part deals with the design of Business Intelligence solution to the concrete company. The analysis of company prepare
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Books on the topic "Business intelligence; data warehouse"

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Laberge, Robert. The data warehouse mentor: Practical data warehouse and business intelligence insights. McGraw-Hill, 2011.

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International Business Machines Corporation. International Technical Support Organization., ed. Leveraging DB2 data warehouse edition for business intelligence. IBM, 2006.

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Corporation, International Business Machines, ed. InfoSphere Warehouse: A robust infrastructure for business intelligence. IBM?, 2010.

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Peter, Jones. SAP® Business Information Warehouse Reporting. McGraw-Hill, 2008.

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Kimball, Ralph. The data warehouse toolkit: Practical techniques for building dimensional data warehouses. John Wiley & Sons, 1996.

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International Business Machines Corporation. International Technical Support Organization, ed. Infrastructure solutions: Design, manage, and optimize a 60 TB SAP NetWeaver business intelligence data warehouse. IBM, International Technical Support Organization, 2008.

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International Business Machines Corporation. International Technical Support Organization., ed. Infrastructure solution: Design, manage, and optimize a 60 TB SAP NetWeaver BI data warehouse. IBM, 2008.

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Mundy, Joy. The Microsoft data warehouse toolkit: With SQL Server 2005 and the Microsoft Business Intelligence toolset. Wiley Pub., 2006.

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Mundy, Joy. The Microsoft data warehouse toolkit: With SQL server 2008 R2 and the Microsoft Business intelligence toolset. 2nd ed. Wiley Pub., 2011.

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Schmidt-Volkmar, Pascal. Betriebswirtschaftliche Analyse auf operationalen Daten. Gabler, 2008.

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Book chapters on the topic "Business intelligence; data warehouse"

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Pirk, Kay, and Volkhard Wolf. "Business Intelligence von IBM." In Data Warehouse Managementhandbuch. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56847-3_11.

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Wrembel, Robert. "Data Warehouse Performance: Selected Techniques and Data Structures." In Business Intelligence. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27358-2_2.

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Kumar, Anjani, Abhishek Mishra, and Sanjeev Kumar. "Business Intelligence." In Architecting a Modern Data Warehouse for Large Enterprises. Apress, 2023. http://dx.doi.org/10.1007/979-8-8688-0029-0_7.

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Behme, Wolfgang. "Business-Intelligence als Baustein des Geschäftserfolgs." In Das Data-Warehouse-Konzept. Gabler Verlag, 1996. http://dx.doi.org/10.1007/978-3-663-13657-6_2.

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Jones, Ken. "Populating the Accounting Data Warehouse." In Business Intelligence Techniques. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24700-5_3.

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Becker, Dietmar H., and Dirk U. Proff. "Data Warehousing: Ausgewählte Business Intelligence-Lösungen für die Versicherungswirtschaft." In Data Warehouse-gestützte Anwendungen. Gabler Verlag, 2001. http://dx.doi.org/10.1007/978-3-322-90222-1_11.

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Bellatreche, Ladjel, Amine Roukh, and Selma Bouarar. "Step by Step Towards Energy-Aware Data Warehouse Design." In Business Intelligence. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61164-8_5.

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Vaisman, Alejandro, and Esteban Zimányi. "Data Warehouses: Next Challenges." In Business Intelligence. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27358-2_1.

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Jeusfeld, Manfred A., and Samsethy Thoun. "Key Performance Indicators in Data Warehouses." In Business Intelligence. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39243-1_5.

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Büsch, Sebastian. "Grundlagen von Business Intelligence und Data-Warehouse-Systemen." In Forschung zur Digitalisierung der Wirtschaft | Advanced Studies in Business Digitization. Springer Fachmedien Wiesbaden, 2023. http://dx.doi.org/10.1007/978-3-658-40304-1_2.

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Conference papers on the topic "Business intelligence; data warehouse"

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Chengyi, LU, ZHANG Ruijun, DUAN Jiawen, XIAO Lingling, and ZHANG Zexi. "Application of Business and Data Based Access Control Model in Warehouse Management." In The 14th International Conference on Logistics and Systems Engineering. Aussino Academic Publishing House, 2025. https://doi.org/10.52202/078960-0022.

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Jwala, V. Ch, Bhavesh Joshi, Pavan Mishra, Aahana Saha, Shweta Goyal, and Bandla Ramesh. "Transforming Business Intelligence using Data Analytics and Artificial Intelligence." In 2024 Second International Conference Computational and Characterization Techniques in Engineering & Sciences (IC3TES). IEEE, 2024. https://doi.org/10.1109/ic3tes62412.2024.10877547.

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Garani, Georgia, Andrey Chernov, Ilias Savvas, and Maria Butakova. "A Data Warehouse Approach for Business Intelligence." In 2019 IEEE 28th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE). IEEE, 2019. http://dx.doi.org/10.1109/wetice.2019.00022.

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Bagambiki, Erika. "Enterprise Data warehouse and Business Intelligence Solution." In ICEGOV '18: 11th International Conference on Theory and Practice of Electronic Governance. ACM, 2018. http://dx.doi.org/10.1145/3209415.3209420.

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Minh, Quang Tran, Do Thanh Thai, Bui Tien Duc, and Nguyen Huu Phat. "Designing a Data Warehouse Framework for Business Intelligence." In 2022 International Conference on Data Analytics for Business and Industry (ICDABI). IEEE, 2022. http://dx.doi.org/10.1109/icdabi56818.2022.10041706.

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Ul Hassan, Ch Anwar, Rizwana Irfan, and Munam Ali Shah. "Integrated Architecture of Data Warehouse with Business Intelligence Technologies." In 2018 24th International Conference on Automation and Computing (ICAC). IEEE, 2018. http://dx.doi.org/10.23919/iconac.2018.8749017.

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Struss, Peter, Vikas Shivashankar, and Mohamed Zahoor. "Debugging Support for Data Warehouse Applications." In Annual International Academic Conference on Business Intelligence and Data Warehousing. Global Science and Technology Forum, 2010. http://dx.doi.org/10.5176/978-981-08-6308-1_30.

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Soon, Lisa, and Campbell Fraser. "Intranet: How is Business Intelligence Stored in a Data Warehouse?" In Annual International Academic Conference on Business Intelligence and Data Warehousing. Global Science and Technology Forum, 2010. http://dx.doi.org/10.5176/978-981-08-6308-1_26.

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Togatorop, Parmonangan R., Dody Sitorus, Yohana Purba, and Andika M. F. Tarigan. "Twitter Data Warehouse and Business Intelligence Using Dimensional Model and Data Mining." In 2022 IEEE International Conference of Computer Science and Information Technology (ICOSNIKOM). IEEE, 2022. http://dx.doi.org/10.1109/icosnikom56551.2022.10034904.

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Plašić, Jelena, Andrijana Gaborović, and Nenad Stefanović. "UNIFIED BUSINESS INTELLIGENCE IN THE MICROSOFT FABRIC ENVIRONMENT." In Eighth International Scientific Conference Contemporary Issues in Economics, Business and Management [EBM 2024]. Faculty of Economics, Kragujevac, 2025. https://doi.org/10.46793/ebm24.407p.

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Data has become the strategic asset used to transform businesses to uncover new insights. Business Intelligence (BI) has been helping organizations across industries uncover insights from their data and turn them into actionable strategies. However, the world of data and BI is rapidly evolving in ways that are transforming the industry and motivating enterprises to consider new approaches of gaining insights. In this paper, Microsoft Fabric, as an innovative and holistic data analysis platform that integrates advanced business intelligence tools and enable organizations to transform big data i
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Reports on the topic "Business intelligence; data warehouse"

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Amekedzi, Komivi. Using Business Intelligence Tools to Make Data-Driven Decisions. Iowa State University, 2021. http://dx.doi.org/10.31274/cc-20240624-1554.

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Cao, Larry. Handbook of Artificial Intelligence and Big Data Applications in Investments. CFA Institute, 2023. http://dx.doi.org/10.56227/23.1.5.

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Learn how asset managers are leveraging data science to garner investment insights, build more resilient portfolios, make better trading decisions, streamline client services, develop client-centric products, and gather business intelligence.
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Pasupuleti, Murali Krishna. Empathetic AI in Action: Transforming Customer Service with Emotional Intelligence. National Education Services, 2025. https://doi.org/10.62311/nesx/rr725.

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Abstract: This article explores the transformative impact of Emotionally Intelligent AI on customer service, focusing on how AI systems are designed to understand and respond to human emotions with empathy and precision. It delves into the core technologies, such as sentiment analysis, emotion recognition models, and reinforcement learning, that enable AI to provide emotionally aware interactions. Practical applications are discussed, including AI-powered customer support, personalized experiences, and crisis management solutions. The Article also covers the psychological foundations of AI-dri
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Rihm, Alfredo, Carolina Piamonte, Eduardo Antonio Restrepo Lagos, Magda Correal, and Paula Gabriela Guerra Morán. Digital Transformation of Solid Waste Management: Waste Collection Innovation, Business Intelligence, and Digital Technologies to Transition Waste Management Towards Circularity in Latin America and the Caribbean. Edited by Claudia M. Pasquetti. Inter-American Development Bank, 2024. http://dx.doi.org/10.18235/0013169.

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If you are interested in technology and innovation, and have been wondering what are the new trends in technological and digital innovation in the solid waste sector in Latin America and the Caribbean, this publication is for you! The transition to the circular economy, climate action, the fourth industrial revolution bring new challenges to operators in the sector. Key challenges highlighted include the need for robust data and the digitization of waste management systems to meet the objectives of the circular economy. The text details the efforts of organizations such as the IDB to develop d
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Danylchuk, Hanna B., and Serhiy O. Semerikov. Advances in machine learning for the innovation economy: in the shadow of war. Криворізький державний педагогічний університет, 2023. http://dx.doi.org/10.31812/123456789/7732.

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This preface introduces the selected and revised papers presented at the 10th International Conference on Monitoring, Modeling &amp; Management of Emergent Economy (M3E2 2022), held online in Ukraine, on November 17-18, 2022. The conference aimed to bring together researchers, practitioners, and students from various fields to exchange ideas, share experiences, and discuss challenges and opportunities in applying computational intelligence and data science for the innovation economy. The innovation economy is a term that describes the emerging paradigm of economic development that is driven by
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Ndoye, Aissatou, Mansour Dia, and Khadim Dia. Africa Agriculture Watch Forecasts Brief Series. AKADEMIYA2063, 2023. http://dx.doi.org/10.54067/acpf.105.

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Abstract:
The crop production forecast brief series by AKADEMIYA2063’s Africa Agriculture Watch (AAgWa) aims to provide more accurate and timely data on harvest and yields for nine major crops across nearly 50 African countries. The timeliness, wide availability, and easy access to this type of data will allow stakeholders across the value chain to better plan and execute policy and business actions more efficiently. The data published in the briefs are generated through the Africa Crop Production (AfCP) model, an Artificial Intelligence (AI-based) model applied to remotely sensed geo-biophysical data t
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7

Ndoye, Aissatou, Mansour Dia, and Khadim Dia. Africa Agriculture Watch Forecasts Brief Series. AKADEMIYA2063, 2023. http://dx.doi.org/10.54067/acpf.106.

Full text
Abstract:
The crop production forecast brief series by AKADEMIYA2063’s Africa Agriculture Watch (AAgWa) aims to provide more accurate and timely data on harvest and yields for nine major crops across nearly 50 African countries. The timeliness, wide availability, and easy access to this type of data will allow stakeholders across the value chain to better plan and execute policy and business actions more efficiently. The data published in the briefs are generated through the Africa Crop Production (AfCP) model, an Artificial Intelligence (AI-based) model applied to remotely sensed geo-biophysical data t
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8

Ndoye, Aissatou, Mansour Dia, and Khadim Dia. Africa Agriculture Watch Forecasts Brief Series. AKADEMIYA2063, 2023. http://dx.doi.org/10.54067/acpf.104.

Full text
Abstract:
The crop production forecast brief series by AKADEMIYA2063’s Africa Agriculture Watch (AAgWa) aims to provide more accurate and timely data on harvest and yields for nine major crops across nearly 50 African countries. The timeliness, wide availability, and easy access to this type of data will allow stakeholders across the value chain to better plan and execute policy and business actions more efficiently. The data published in the briefs are generated through the Africa Crop Production (AfCP) model, an Artificial Intelligence (AI-based) model applied to remotely sensed geo-biophysical data t
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9

Stucke, Maurice E. AI, Antitrust & Privacy. Institute for New Economic Thinking Working Paper Series, 2025. https://doi.org/10.36687/inetwp236.

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Generative artificial intelligence (AI) is reshaping how companies profile individuals, create and target ads, and influence behavior—often in ways that undermine privacy, autonomy, and democracy. This article explores a critical but overlooked question: how AI affects the relationship between competition and privacy. Increased competition in the AI supply chain may seem like a solution to Big Tech’s dominance, but when firms are rewarded for surveillance and manipulation, more competition can actually make things worse. Drawing on recent market trends and twenty state privacy laws, the Articl
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Global Microscope on the Microfinance Business Environment 2011. Inter-American Development Bank, 2011. http://dx.doi.org/10.18235/0006457.

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This report outlines the findings of the Economist Intelligence Unit's in-depth analysis of the microfinance business environment in 55 countries. The index that underlies this report allows countries and regions to be compared across two broad categories: Regulatory Framework and Practices, which examines regulatory and market-entry conditions, and Supporting Institutional Framework, which assesses business practices and client interaction. The Microscope was originally developed for countries in the Latin American and Caribbean region in 2007 and was expanded into a global study in 2009. Mos
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