Freestyle Fridays - Old School vs. New School Data Modeling
Feb 7, 2025
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Discover the fascinating intersection of tradition and innovation in sports and data modeling. The speaker shares personal insights from their return to Brazilian jiu-jitsu, reflecting on its evolution. Dive into the debate between old school and new school techniques in data modeling, emphasizing the value of mastering conventional methods before embracing modern approaches. Plus, learn about engaging community events and workshops aimed at fostering growth in the ever-evolving field of data engineering!
Practicing Brazilian jiu-jitsu has evolved significantly, illustrating the importance of balancing foundational customs with modern techniques in martial arts and data modeling.
Familiarity with traditional data modeling methods enables teams to effectively communicate and make informed decisions while remaining open to innovative approaches.
Deep dives
Returning to Brazilian Jiu-Jitsu
Practicing Brazilian jiu-jitsu provides a humbling experience that highlights the evolution of the sport over time. As the speaker returns to jiu-jitsu after years of participating in other martial arts, he notes significant changes in techniques, competitions, and training practices, which make him feel like a beginner again. These changes emphasize the need to adapt while still understanding the foundational customs and orthodox practices established by the Gracie family, such as bowing and respecting traditional forms. The speaker draws parallels between this evolution in martial arts and the advancements in technology, particularly in data modeling and AI, where traditional methods can be both relevant and adaptable.
The Importance of Understanding Convention
Understanding conventional methods in fields like data modeling is crucial for ensuring effective communication and execution among team members. The speaker emphasizes that familiarizing oneself with established techniques, such as the relational model, provides a foundation to build upon when exploring new methodologies. Techniques like normalization help avoid redundancies and make data management clearer, fostering a shared vocabulary amongst teams. By grasping these conventions, teams can better recognize the implications of any deviations they choose to make in their practices, ensuring they are informed and purposeful in their decisions.
Balancing Tradition and Innovation
The tension between adhering to traditional methods and embracing new techniques can significantly impact the effectiveness of data modeling practices. While the speaker acknowledges the value of established conventions, he warns against becoming too rigid and suggests staying open to innovative approaches that can enhance workflows. His experience with data modeling indicates that many teams mismanage data by neglecting foundational principles for the sake of speed or simplicity, leading to long-term complications. Ultimately, understanding the established rules empowers practitioners to selectively break them when the context demands, fostering an environment that values both tradition and innovation.
In data modeling - and pretty much anything else - do you choose "old school" or "new school"? In other words, do you move slow and methodically or fast?
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