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Here is a flat version of my datamodel. It is sensor readings for various data acquisition equipment.

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https://i1295.photobucket.com/albums/b628/colnewman26/Work%20Screen%20Shots/RobinDataModel_zpsdfc40151.png~original

Here is my Relational Database model. Does this make sense.

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https://i1295.photobucket.com/albums/b628/colnewman26/RobinDataModel_zps847d94b5.png~original

If not what you suggest?

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    Looks good to me. But it really depends on how well it maps to your requirements matrix.
    – Robert Harvey
    Aug 14, 2014 at 15:54
  • as per @RobertHarvey, what are you going to do with the data in the relational model? If you're usually/only going to reconstruct/manipulate the measurements table from the first image, then a table of events with a lot of fields would suffice. If you're going to be doing time-series analysis on discrete event/measurement types, you might want to consider a simpler representation of quantities and measurements (e.g. see Analysis Patterns, by Martin Fowler)
    – Steven A. Lowe
    Aug 15, 2014 at 1:28
  • Well it's mostly just used for graphing for reports, and finding highs and lows etc. Each test instance will have a different number of channels for each type of sensor, and I also need to ability to add new types of tests in the future.
    – TheColonel26
    Aug 15, 2014 at 1:59

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Seems to me you may have over normalized this based on the original table design. Unless you are certain that you will need an indeterminate number of factors, you pay a pretty high penalty in insertion and retrieval of data with that schema. Having worked with high data volume sensors (GPS readings) I found that performance considerations pay a heavy role as you start viewing trending data as the data volume grows.

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