OPTIMIZING FUNNEL ANALYSIS IN MODERN DATA WAREHOUSES
DOI:
https://doi.org/10.5281/zenodo.13310800Keywords:
Funnel Analysis, Data Warehouses, Query Optimization, User Journey, Product PerformanceAbstract
This article explores the implementation of funnel analysis in modern data warehouses, focusing on its importance for product managers in understanding and optimizing user journeys. It delves into the mechanics of funnel analysis, discussing two primary approaches: the Join Sequence and Stacked Window Functions methods. The article examines various query optimization techniques modern data warehouses employ, including common subexpression elimination, aggregate pushdown, and efficient handling of window functions. Additionally, it addresses performance considerations for both approaches, highlighting the benefits of pre-computed join indices and table clustering. Throughout, the article emphasizes the critical role of funnel analysis in driving data-driven decision-making and product success in today's competitive business landscape.
References
G. S. Day, "The capabilities of market-driven organizations," Journal of Marketing, vol. 58, no. 4, pp. 37-52, 1994. Available: https://doi.org/10.1177/002224299405800404
A. J. Alvarez, "Data-Driven Product Management: How to Use Data to Develop, Launch and Grow Your Products," O'Reilly Media, Inc., 2022. Available: https://www.oreilly.com/library/view/data-driven-product-management/9781098141325/
D. T. Bourgeois and T. Bourgeois, "Information Systems for Business and Beyond," Pressbooks, 2019. Available: https://bus206.pressbooks.com/chapter/chapter-2-information-systems-for-business-and-beyond/
A. Kohavi, A. Tang, and Y. Xu, "Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing," Cambridge University Press, 2020. Available: https://experimentguide.com/
M. Kleppmann, "Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems," O'Reilly Media, 2017. Available: https://www.oreilly.com/library/view/designing-data-intensive-applications/9781491903063/
J. M. Hellerstein, M. Stonebraker, and J. Hamilton, "Architecture of a Database System," Foundations and Trends in Databases, vol. 1, no. 2, pp. 141-259, 2007. Available: https://dl.acm.org/doi/10.1561/1900000002
S. Chaudhuri, "An Overview of Query Optimization in Relational Systems," in Proceedings of the Seventeenth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, 1998, pp. 34-43. Available: https://dl.acm.org/doi/10.1145/275487.275492
A. Thusoo et al., "Hive: A Warehousing Solution Over a Map-Reduce Framework," Proceedings of the VLDB Endowment, vol. 2, no. 2, pp. 1626-1629, 2009. Available: https://dl.acm.org/doi/10.14778/1687553.1687609
P. O'Neil and D. Quass, "Improved Query Performance with Variant Indexes," in Proceedings of the 1997 ACM SIGMOD International Conference on Management of Data, 1997, pp. 38-49. Available: https://dl.acm.org/doi/10.1145/253260.253268
D. Abadi, P. Boncz, S. Harizopoulos, S. Idreos and S. Madden, "The Design and Implementation of Modern Column-Oriented Database Systems," Foundations and Trends in Databases, vol. 5, no. 3, pp. 197-280, 2013. Available: https://doi.org/10.1561/1900000024
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Satyam Shekhar (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
