Database Systems Journal, Vol. XV, 2024
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1. Automating the Generation of Microservice Architectures in Web Applications (p. 1-9)Pavel-Cristian CRACIUN, The Bucharest University of Economic Studies, Romania |
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The advent of microservice designs, which prioritizes enhancing deployment timelines, scalability, and flexibility, marks an advancement period in software development. This article presents a tool designed to accelerate the construction of microservice architectures. Using an intuitive interface, the solution allows users to create fundamental code and graphically construct structures, which streamlines the typically laborious first coding process. Through the automation of project documentation and scaffolding, the solution reduces resource consumption and speeds up development. The proposed solution's complete approach is demonstrated by a comparison with Spring Initializr, which provides a straight path from conceptual design to deployable code. This highlights the potential of the proposed tool to revolutionize software project development. Keywords: Microservices, Software Development Efficiency, Automated Code Generation, Architectural Planning |
2. Automation in Financial Reporting: A Case Study (p. 10-22)Oana-Alexandra DRAGOMIRESCU, The Bucharest University of Economic Studies, RomaniaAdriana-Teodora PARSCHIVOIU, The Bucharest University of Economic Studies, Romania Andreea VINES, The Bucharest University of Economic Studies, Romania Andrei NICA, The Bucharest University of Economic Studies, Romania |
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Financial Reporting is the key in understanding the financial information of an organisation in a clear and organised way. With the advent of Artificial Intelligence (AI), there has been a significant shift towards automation due to its numerous benefits, including improved data quality and integration, cost and time savings, scalability, flexibility, and enhanced operational efficiency. Financial reporting is one area that has particularly embraced these advancements.
This article explores the necessity of automation in financial reporting, focusing on the use of the automation tool Alteryx with the AnaCredit dataset. It examines the outcomes of incorporating automation into daily financial reporting practices, demonstrating the tangible benefits and improvements achieved through this technological integration. Keywords: business process automation, financial reporting, Alteryx automation |
3. Mapping Business Process Modeling with the Business Models of Several Energy Community Members (p. 23-37)Anca Ioana ANDREESCU, The Bucharest University of Economic Studies, RomaniaSimona-Vasilica OPREA, The Bucharest University of Economic Studies, Romania Adela BARA, The Bucharest University of Economic Studies, Romania Alin Gabriel VADUVA, The Bucharest University of Economic Studies, Romania Andreea-Mihaela NICULAE, The Bucharest University of Economic Studies, Romania |
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Energy communities (ECs) play a major role in energy systems by enabling decentralized production and distribution of renewable energy. This article applies business process modeling to enhance and align the business models of various EC members. Using Business Process Model and Notation (BPMN), it maps the operational workflows of key participants, including prosumers, storage owners, EV charging stations, aggregators, and entities involved in Local Energy Markets (LEM) and Local Flexibility Markets (LFM). Proposed BPMN models provide a structured perspective on essential tasks, decision points, and interactions within the energy market, capturing processes such as energy forecasting, trading, flexibility transactions and daily operations. Through process visualization, the models offer valuable insights for optimizing energy usage, enhancing grid stability and maximizing economic benefits. This approach highlights BPMN’s capability to support more efficient, sustainable, and resilient ECs within decentralized systems. Keywords: energy communities, business models, business process models, BPMN |
4. The role of Big Data in Climate research (p. 38-47)Andreea-Mihaela NICULAE, The Bucharest University of Economic Studies, RomaniaAlin Gabriel VADUVA, The Bucharest University of Economic Studies, Romania |
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This study explores the growing impact of Big Data in climate change research through a novel approach that combines Big Data analytics with text mining, natural language processing (NLP), and Latent Dirichlet Allocation (LDA). We analysed 7,145 open-access publications from 2011 to 2022 sourced from the Web of Science. Our work highlighted key themes such as urban health, smart technologies, and algorithmic modelling. We observed substantial growth in the use of Big Data in climate research up until 2022, followed by a surprising decline in 2023 that calls for further investigation. Sentiment analysis of the abstracts showed mostly neutral tones, although some exceptions revealed diverse perspectives. This research offers valuable insights into current trends, demonstrating the strength of an integrated analytical approach and the evolving role of Big Data in climate change research. The unexpected downturn in 2023 suggests a shift in research priorities, warranting further exploration. Keywords: Big Data, Climate-Change, Bibliometrics, Latent Dirichlet Allocation |