Separating values from columns where there are multiple attribute values in a single column

If I can assume that the Log Headers are the same from log to log then you code do something like this...

let
    Source = Table.FromRows(Json.Document(Binary.Decompress(Binary.FromText("nVJdb4IwFP0rjXt1fBk18lbaOtikkK4YjfGBaDdIiBDA/f65vfQya4wjhNx7OLfn3tuz240olmy0H+9Gvx/X9mzP8aYaQToUGUdPOt1snjc/j5EbiyEVsCiIY1V8le25M55xN+Q4Br3Lc3tS7Ri91gr0rD4sFNZdY2ksyJu+7HoUqrzqi0cEaRLoxHHty+suZos/cjHVwFt5+jQvky0tlPFIaohRIzPiy8Q3/pHblEGeZGKJSbSK5FbDWHKwb0KSrbkfwJKZ4Ew8sJcUy4hxMErKaISliAjY3VrYaVnVvYbe40iGxgOTvlDt/0whGY6BKgbjCrKmiORVBQzv+Y6DYAW87rJr8v5QALo/uckW6nBlNRK8BPcaZtQOVVU2+RF4a+a7jpl9autzr4bUye2GoBnTNj8WZ+hBcuVBcO24bS3042ggNvcn7jAF2lQ1hoKpM0ynVwoHWLDw3TkwLJNhAkbAcZCtMCcX3++/AQ==", BinaryEncoding.Base64), Compression.Deflate)), let _t = ((type nullable text) meta [Serialized.Text = true]) in type table [Column1 = _t]),
    header_list = {"DATE", "DX", "EF. HOSP.", "REF. MD", "ATN", "DVR/PILOT", "RCVD CALL", "ED/HELIPAD", "ARR. REF.", "RUN #", "NAME", "DOB", "REF. UNIT", "RN", "OTHER", "DISPATCH", "ENROUTE", "DEP. REF.", "MR #", "INFO:", "REC. HOSP.", "REC. MD", "TYPE", "PATIENT", "TEAM", "REC. UNIT", "ARR. REC.", "METHOD", "REF. HOSP."},
    remove_blank_rows = Table.SelectRows(Source, each ([Column1] <> "" and [Column1] <> " ")),
    add_isHeader_column = Table.AddColumn(remove_blank_rows, "isHeader", each if List.Contains(header_list, [Column1], Comparer.OrdinalIgnoreCase) then [Column1] else null, type text),
    fill_down_isHeader = Table.FillDown(add_isHeader_column,{"isHeader"}),
    group_by_isHeader = Table.Group(fill_down_isHeader, {"isHeader"}, {{"All Rows", each _, type table [Column1=nullable text, isHeader=text]}}),
    select_nested_table_values = Table.TransformColumns(group_by_isHeader, {{"All Rows", each Table.SelectColumns(Table.SelectRows(_, each [Column1] <> [isHeader]), {"Column1"})}}),
    add_nested_index = Table.TransformColumns(select_nested_table_values, {{"All Rows", each Table.AddIndexColumn(_, "Index", 1, 1)}}),
    expand_nested_table = Table.ExpandTableColumn(add_nested_index, "All Rows", {"Column1", "Index"}),
    pivot_table = Table.Pivot(expand_nested_table, List.Distinct(expand_nested_table[isHeader]), "isHeader", "Column1"),
    remove_null_index = Table.SelectRows(pivot_table, each ([Index] <> null)),
    remove_index_column = Table.RemoveColumns(remove_null_index,{"Index"}),
    set_data_types = Table.TransformColumnTypes(remove_index_column,{{"DATE", type date}, {"RUN #", type text}, {"MR #", type text}, {"DX", type text}, {"NAME", type text}, {"Ref. Hosp.", type text}, {"DOB", type date}, {"Ref. MD", type text}, {"REF. UNIT", type text}, {"INFO:", type any}, {"TYPE", type text}, {"ATN", type text}, {"RN", type text}, {"PATIENT", type text}, {"DVR/Pilot", type text}, {"Other", type any}, {"TEAM", type text}, {"RCVD Call", type time}, {"Dispatch", type time}, {"Rec. Hosp.", type text}, {"ED/Helipad", type time}, {"Enroute", type time}, {"Rec. MD", type text}, {"REC. UNIT", type text}, {"Arr. Ref.", type time}, {"Dep. Ref.", type time}, {"Arr. Rec.", type time}, {"METHOD", type text}})
in
    set_data_types

The basic idea is to set a list of the headers, compare the existing column to the header list, group by header names, select the coresponding values, pivot the table to end up with...

Hope this helps.