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welcome im frank conkling of panda consulting and this is the panic consulting deep dive workshop and today were going to talk about cleaning up your data so this is even though it is a deep dive workshop were going to cover most of the things that that pandas does when were were cleaning up data but its not going to be as as exclusive as or or as comprehensive as it might be theres things we just cant cover in in an hour even an hour and a half but were going to talk about it is just sort of what could you consider dirty data and this doesnt have to necessarily do with parcel fabric this could just be any regular gis data and were going to break it down into three different groupings the first grouping is going to be the geometries what do you consider dirty data as it relates to geometries and well show you a couple tools that you can use and well demonstrate them and and show you how to utilize them the second grouping is attribution and were going to go over a couple