Troubleshooting Data Discrepancies in NFL and NHL Player Records

The State Changers were discussing a potential issue with a player database they were working with. They discovered that the count function they created earlier appeared to be the problem, resulting in inaccurate counts for various sports. To investigate, they used filtering and queries to inspect the data, particularly in relation to player headshots and related records. They navigated through the data extraction and queried all records where the headshot metadata was not null, using a season ID as part of the filter.

They also reviewed their debugging processes, looking at variables leading up to the inaccurate counts and cross-referencing these against database information. They explored issues around null values and attempted to understand discrepancies. They also discussed using "stop and debug" in their process for tracking variables and potential issues. In their debugging process, they utilized object constructs to create a comparison of the available player counts, resulting in a revelation that they were trying to find the delta (difference) rather than the total count, giving their investigation a new perspective. The meeting concluded with them planning to investigate further. The specific technologies or services mentioned in the meeting include Xano and open debugging methods, which may interest those dealing with similar data management issues or those interested in using Xano for their projects.

(Source: Office Hours 11/9 )

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