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CISeD - Artigo em ata de evento científico internacional

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http://hdl.handle.net/10400.19/5718

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Percorrer CISeD - Artigo em ata de evento científico internacional por autor "ANTUNES VAZ, PAULO JOAQUIM"

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  • Enhancing Organizational Data Integrity and Efficiency through Effective Data Lineage
    Publication . Silva, Carlos; Abbasi, Maryam; Martins, Pedro; Silva, José; ANTUNES VAZ, PAULO JOAQUIM; Mota, David
    In the era of exponential data growth and the growing reliance of organizations on data-driven decision-making, understanding the origin, transformation, processing, and destination of data has become crucial. Unfortunately, data arriving at organizations is often incorrect or structured differently, leading to analytical errors and compromising data integrity. Without well-documented data mapping and lineage, organizations risk making strategic decisions based on flawed or inaccurate data. Consequently, the implementation of a robust Data Lineage solution has emerged as a vital component for organizational success. Such a solution not only enables error identification, but also facilitates cost reduction by pinpointing inefficient data processing points and driving efficiency improvements. However, finding the right Data Lineage solution tailored to an organization’s specific requirements remains a challenge. Therefore, it is imperative to select and implement a suitable solution that aligns with each organization’s needs.
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  • Performance Comparison of Redis, Memcached, MySQL, and PostgreSQL: A Study on Key-Value and Relational Databases
    Publication . Almeida, Dany; Lopes, Maria; Saraiva, Luzia; Abbasi, Maryam; Martins, Pedro; Silva, José; ANTUNES VAZ, PAULO JOAQUIM
    This paper investigates and compares the performance of relational databases (MySQL and PostgreSQL) and key-value databases (Memcached and Redis) under various test loads. The study utilizes the Yahoo! Cloud Serving Benchmark to simulate diverse workloads and measure the behavior of these databases in different scenarios. The primary focus is on evaluating run time, throughput, and average latency metrics to understand how each database type handles varying thread levels and workload intensity. The outcomes of this research provide valuable insights into the scalability and efficiency aspects of relational databases. By conducting a comprehensive performance comparison, the study aims to assist database designers and developers in selecting the most suitable database option based on specific requirements. The findings contribute to informed decision-making regarding the choice between key-value and relational databases in various data storage scenarios.
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