There isn't any function to directly get denormalize data from normalized data. As data and scaled version of data have same normalized values you can't get exact data from only normalized values. 
Proof:
Consider data of N values of form  and a scaled version of it by a constant k which will be of form
 and a scaled version of it by a constant k which will be of form  .
 . 
After normalising,
an ith element in non scaled version will be 
 an ith element in scaled version wiil be  , removing
, removing  out of square root in denominator its cancels k in numerator and we are left with
out of square root in denominator its cancels k in numerator and we are left with  .
.  
Hence we can say scaled version of a vector has same normalized values. So, we can't deduce the original data unless we know the euclidean norm of original data. 
In case of 2-norm we need 2-norm of column to get denormalized values:
Normalized values are calculate by dividing each element with 2-norm of the column vector i.e, dividing a element with square root of sum of squares of all values in column. Hence by multiplying this to normalized values you can get denormalized values. 
Here is an example of how to do it:
DT = table(L1, L2, L3, L4, L5, L6, L7)
DT = 
    L1     L2    L3    L4    L5    L6    L7
    ___    __    __    __    __    __    __
    "X"    1     2     3      4     5     6
    "Y"    7     8     9     10    11    12
DN = normalize(DT,"norm",...
    "DataVariables",["L2", "L3", "L4", "L5", "L6", "L7"])
DN = 
    L1       L2         L3         L4         L5         L6         L7   
    ___    _______    _______    _______    _______    _______    _______
    "X"    0.14142    0.24254    0.31623    0.37139     0.4138    0.44721
    "Y"    0.98995    0.97014    0.94868    0.92848    0.91037    0.89443
DA.L2 = norm(DT.L2, 2) * DA.L2;
DA.L3 = norm(DT.L3, 2) * DA.L3;
DA.L4 = norm(DT.L4, 2) * DA.L4;
DA.L5 = norm(DT.L5, 2) * DA.L5;
DA.L6 = norm(DT.L6, 2) * DA.L6;
DA.L7 = norm(DT.L7, 2) * DA.L7;
disp(DA)
    L1     L2    L3    L4    L5    L6    L7
    ___    __    __    __    __    __    __
    "X"    1     2     3      4     5     6
    "Y"    7     8     9     10    11    12
For your case, I think this should work fine but I can't run this since I don't have DT.xlsx file so I tried this method in above example:
DT = readtable("DT.xlsx");
DN = normalize(DT,"norm",...
    "DataVariables",["Tb","DH","DN","EB","GH","Z"]) ;
DA.Tb = norm(DT.Tb, 2) * DA.Tb;
DA.DH = norm(DT.DH, 2) * DA.DH;
DA.DN = norm(DT.DN, 2) * DA.DN;
DA.EB = norm(DT.EB, 2) * DA.EB;
DA.GH = norm(DT.GH, 2) * DA.GH;
DA.Z = norm(DT.Z, 2) * DA.Z;