Discussing Best Practices for Creating Unique IDs in Data Management
In this meeting, the State Changers focused on discussing conceptual best practices in creating unique identifiers. A query was raised about knowing when to construct unique identifiers by concatenating variables such as player, stat, and date. The team clarified that unique identifiers are crucial when there's a need to update or retrieve specific data stored. Unique identifiers should have enough uniqueness to single out a specific piece of data. The criteria for creating a unique identifier are guided by how much information is needed to retrieve an exact piece of stored data in the future for updating or modification.
They elaborated on this with a case study about developing a table for updating season averages. They established that factors like the player, season, and stats are essential in creating sufficient uniqueness. One appropriate way to go about this, they suggested, was to think about the uniqueness level needed, then concatenate these unique elements end-to-end without need for coding schemes.
The team also highlighted that understanding the context of the data aids in creating more effective identifiers. It aids in making better choices when deciding the factors that make up a unique identifier. A general advice given was to visualize the process as if it were done manually, and make sure that the unique identifier consists of details enough to single out a specific record across time and seasons.
Unfortunately, none of the expected keywords like Xano, WeWeb, FlutterFlow, Zapier, etc., were touched upon in the meeting.