Bibliography

  • [CCT09] James Cheney, Laura Chiticariu, and Wang Chiew Tan. Provenance in databases: Why, how, and where. Found. Trends Databases, 1(4):379–474, 2009.
  • [GGSS21] Stefan Grafberger, Shubha Guha, Julia Stoyanovich, and Sebastian Schelter. MLINSPECT: A data distribution debugger for machine learning pipelines. In Guoliang Li, Zhanhuai Li, Stratos Idreos, and Divesh Srivastava, editors, SIGMOD ’21: International Conference on Management of Data, Virtual Event, China, June 20-25, 2021, pages 2736–2739. ACM, 2021
  • [LFS+23] Raoni Louren ̧co, Juliana Freire, Eric Simon, Gabriel Weber, and Dennis E. Shasha. Bugdoc. VLDB J., 32(1):75–101, 2023.
  • [ZAI19] Nan Zheng, Abdussalam Alawini, and Zachary G. Ives. Fine-grained provenance for matching & ETL. In 35th IEEE International Conference on Data Engineering, ICDE 2019, Macao, China, April 8-11, 2019, pages 184–195. IEEE, 20
Keep in mind that for performing data analytics you are willing to make sense of data and this implies acquiring Data Literacy. Have a look at this reference for background. 

Michel Bowen, Anthony Bartley, The Basics of Data Literacy: making your students (and you!) make sens of data, NST Press, Arlington Virginia