Referencias

Armbrust, Michael, Tathagata Das, Liwen Sun, et al. 2020. “Delta Lake: High-Performance ACID Table Storage over Cloud Object Stores.” Proceedings of the VLDB Endowment 13 (12): 3411–24.
Armbrust, Michael, Ali Ghodsi, Reynold Xin, and Matei Zaharia. 2021. “Lakehouse: A New Generation of Open Platforms That Unify Data Warehousing and Advanced Analytics.” 11th Conference on Innovative Data Systems Research (CIDR).
Breck, Eric, Neoklis Polyzotis, Sudip Roy, Steven Euijong Whang, and Martin Zinkevich. 2019. “Data Validation for Machine Learning.” Proceedings of Machine Learning and Systems (MLSys) 1: 334–47.
Codd, Edgar F. 1970. “A Relational Model of Data for Large Shared Data Banks.” Communications of the ACM 13 (6): 377–87.
Date, C. J., Hugh Darwen, and Nikos A. Lorentzos. 2002. Temporal Data and the Relational Model. Morgan Kaufmann.
Dean, Jeffrey, and Sanjay Ghemawat. 2004. “MapReduce: Simplified Data Processing on Large Clusters.” 6th Symposium on Operating Systems Design and Implementation (OSDI), 137–50.
Dehghani, Zhamak. 2022. Data Mesh: Delivering Data-Driven Value at Scale. O’Reilly Media.
DuckDB Labs. 2025. DuckLake: SQL as a Lakehouse Format. Https://ducklake.select/manifesto/.
Elsamadisi, Ahmed. 2021. Activity Schema Specification. Https://www.activityschema.com/.
Ghemawat, Sanjay, Howard Gobioff, and Shun-Tak Leung. 2003. “The Google File System.” Proceedings of the 19th ACM Symposium on Operating Systems Principles (SOSP), 29–43.
Halpin, Terry, and Tony Morgan. 2008. Information Modeling and Relational Databases. 2nd ed. Morgan Kaufmann.
Hultgren, Hans. 2012. Modeling the Agile Data Warehouse with Data Vault. New Hamilton.
Inmon, William H. 2005. Building the Data Warehouse. 4th ed. Wiley.
Inmon, William H., and Francesco Puppini. 2020. The Unified Star Schema: An Agile and Resilient Approach to Data Warehouse and Analytics Design. Technics Publications.
Kimball, Ralph, and Margy Ross. 2013. The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling. 3rd ed. Wiley.
Kimball, Ralph, Margy Ross, Warren Thornthwaite, Joy Mundy, and Bob Becker. 2008. The Data Warehouse Lifecycle Toolkit. 2nd ed. Wiley.
Kleppmann, Martin. 2017. Designing Data-Intensive Applications. O’Reilly Media.
Linstedt, Daniel, and Michael Olschimke. 2015. Building a Scalable Data Warehouse with Data Vault 2.0. Morgan Kaufmann.
Melnik, Sergey, Andrey Gubarev, Jing Jing Long, et al. 2010. “Dremel: Interactive Analysis of Web-Scale Datasets.” Proceedings of the VLDB Endowment 3 (1-2): 330–39.
Raasveldt, Mark, and Hannes Mühleisen. 2019. “DuckDB: An Embeddable Analytical Database.” Proceedings of the 2019 International Conference on Management of Data (SIGMOD), 1981–84.
Reis, Joe, and Matt Housley. 2022. Fundamentals of Data Engineering. O’Reilly Media.
Rönnbäck, Lars, Olle Regardt, Maria Bergholtz, Paul Johannesson, and Petia Wohed. 2010. “Anchor Modeling: Agile Information Modeling in Evolving Data Environments.” Data & Knowledge Engineering 69 (12): 1229–53.
Sculley, D., Gary Holt, Daniel Golovin, et al. 2015. “Hidden Technical Debt in Machine Learning Systems.” Advances in Neural Information Processing Systems (NeurIPS) 28: 2503–11.
Shiran, Tomer, Jason Hughes, Alex Merced, and Dipankar Mazumdar. 2024. Apache Iceberg: The Definitive Guide. O’Reilly Media.
Snodgrass, Richard T. 1999. Developing Time-Oriented Database Applications in SQL. Morgan Kaufmann.
Stonebraker, Michael, Daniel J. Abadi, Adam Batkin, et al. 2005. “C-Store: A Column-Oriented DBMS.” Proceedings of the 31st International Conference on Very Large Data Bases (VLDB), 553–64.
Stonebraker, Michael, and Andrew Pavlo. 2024. “What Goes Around Comes Around... And Around...” ACM SIGMOD Record 53 (2): 21–37.
Zaharia, Matei, Mosharaf Chowdhury, Tathagata Das, et al. 2012. “Resilient Distributed Datasets: A Fault-Tolerant Abstraction for in-Memory Cluster Computing.” 9th USENIX Symposium on Networked Systems Design and Implementation (NSDI), 15–28.
Zaharia, Matei, Reynold S. Xin, Patrick Wendell, et al. 2016. “Apache Spark: A Unified Engine for Big Data Processing.” Communications of the ACM 59 (11): 56–65.