The Joe Reis Show
Freestyle Fridays - The Cult of Scrum, or Why Not Everything Needs to be a Sprint
Feb 28, 2025
Many data professionals are stressed from pressure to deliver quickly instead of taking time to think deeply. There’s a discussion on the clash between agile practices and effective data modeling, emphasizing the need for a solid foundation. The importance of distinguishing between Deep Work and Delivery Work is highlighted. Finally, the conversation encourages a balanced approach to project planning that respects both speed and depth in complex workflows, rather than forcing everything into short sprints.
21:12
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Quick takeaways
- The podcast emphasizes that different work types, like deep work and delivery tasks, require fundamentally different approaches for optimal results.
- Prioritizing speed and short sprints can jeopardize data architecture quality, leading to long-term tech debt and architectural flaws.
Deep dives
Agility and Data Modeling
The concept of agility is examined in relation to data modeling, highlighting the tension between speed of delivery and the need for thoughtful design. In fast-paced environments, such as startups, there's often a reliance on quick iterations to gain customer traction, which can lead to compromised quality in data architecture. This approach results in teams continuously adding 'bubble wrap' to existing systems rather than addressing foundational issues. The consequence of prioritizing speed over thorough design can lead to significant architectural flaws that may not become apparent until much later in the development process.
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