Tardío, R., Maté, A., & Trujillo, J. (2020). An iterative methodology for defining big data analytics architectures. IEEE Access, 8,210597-210616. https://doi.org/10.1109/ACCESS.2020.3039455. This journal article provides a step-by-step methodology that leads Big Data architects into creating their Big Data Pipelines for the case at hand.
Balamurugan, C., Narang, S., Priyanka, U., Thakkar, N., Pandey, H., Purohit, A., Satheesha, A. L., Gunasekhar, P., Srinivasan, T. P., Shastry, A. S., & Ramakrishna, B. N. (2021). Data processing, archival and dissemination pipeline for AstroSat: Challenges and strategies. Journal of Astrophysics & Astronomy, 42(2), 1–9. https://doi.org/10.1007/s12036-021-09747-x This journal article outlines an approach for establishing and operating a completely automated pipeline for data processing, archival, and dissemination of astronomical data.
Ponnuswami, G., Kailasam, S., & Dinesh, D. A. (2020). Event-driven data pipeline for network management systems. 2020 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT) (pp. 1-6). IEEE. https://doi.org/10.1109/ICCCNT49239.2020.9225344 This conference paper illustrates the use of a latency and high throughput data pipeline to perform operations such as data cleansing, filtering, aggregations and join of streams on pipeline stages for event-driven machine learning applications.
Tiezzi, J., Tyler, R., & Sharma, S. (2021). Lessons learned: A case study in creating a data pipeline using Twitter’s API. 2020 Systems and Information Engineering Design Symposium (SIEDS) (pp. 1-6). IEEE. https://doi.org/10.1109/SIEDS49339.2020.9106584 This case study illustrates the process of developing a data pipeline for the acquisition and storage of data from multiple sources.
Lucidchart.com (n.d.). How to make a data flow diagram [Tutorial]. This tutorial describes how to create a data flow diagram to show the movement of data throughout an organization’s business processes.