Developing a data pipeline solution for big data processing

This paper presents a comprehensive exploration of the concept of big data and its management while highlighting the challenges that arise in the process. The study showcases the development of a data pipeline, designed to facilitate big data collection, integration, and analysis while addressing state-of-the-art challenges, methods, tools, and technologies. Emphasis is placed on pipeline flexibility, with a view towards enabling ease of implementation of architecture changes, seamless integration of new sources, and straightforward implementation of additional transformations in existing pipelines as needed. The pipeline architecture is discussed in detail, with a focus on its design principles, components, and implementation details, as well as the mechanisms used to ensure its reliability, scalability, and performance. Results from a range of experiments demonstrate the pipeline's effectiveness in addressing the challenges of big data management and analysis, as well as its robustness and versatility in accommodating diverse data sources and processing requirements. This study provides insights into the critical role of data pipelines in enabling effective big data management and showcases the importance of flexibility in pipeline design to ensure adaptability to evolving data processing needs.