You can use synapse notebook with pandas functionality to combine all of you tables.

Below i am giving an example for 2 tables in you excel file similarly you alter below code for more tables.

df = pd.read_excel("https://vjgsblob.blob.core.windows.net/data/csvs/extracted_data.xlsx?sp=r&st=2024-09-13T07:07:11Z&se=2024-09-13T15:07:11Z&spr=https&sv=2022-11-02&sr=b&sig=2AmroznyDPtH5boSZym8yxpLibsD0X4te18Phj%2BpAxc%3D").dropna(how='all').dropna(axis=1, how='all')
df = df.reset_index(drop=True)
df.columns = [f'col{i}' for i,j in enumerate(df.columns)]

# Getting the column names where table name indicator presents
trialBalancCol = [col for col in df.columns if df[col].str.contains('Trial Balance', na=False).any()][0]
deliquencyReportCol = [col for col in df.columns if df[col].str.contains('Deliquency Report', na=False).any()][0]

# Getting the position, which is used to split them.
trialBalance = df[df[trialBalancCol]=='Trial Balance'].index[0]
deliquencyReport = df[df[deliquencyReportCol]=='Deliquency Report'].index[0]
print(trialBalance,deliquencyReport)

#splitting the tables

dfTrialBalance = df[(df.index>trialBalance) & (df.index<deliquencyReport)].dropna(how='all').dropna(axis=1, how='all')
dfDeliquencyReport = df[df.index>deliquencyReport].dropna(how='all').dropna(axis=1, how='all')

#Removing total row
totalCol = [col for col in dfTrialBalance.columns if dfTrialBalance[col].str.contains('total', na=False).any()][0]
dfTrialBalance = dfTrialBalance[df[totalCol]!='total']
totalCol = [col for col in dfDeliquencyReport.columns if dfDeliquencyReport[col].str.contains('total', na=False).any()][0]
dfDeliquencyReport = dfDeliquencyReport[df[totalCol]!='total']

# Creating the column names
dfTrialBalance.columns =  dfTrialBalance.head(1).values.flatten().tolist()
dfDeliquencyReport.columns =  dfDeliquencyReport.head(1).values.flatten().tolist()

#Removing the column name row and resetting the index
dfTrialBalance = dfTrialBalance.iloc[1:].reset_index(drop=True)
dfDeliquencyReport = dfDeliquencyReport.iloc[1:].reset_index(drop=True)

#Joining the tables
ResTable = pd.merge(dfTrialBalance,dfDeliquencyReport,on='Acc Number',how='left')
ResTable

After executing all above code you save it back to storage account in csv format(ResTable.to_csv(<path>)).

Again, alter this code according to your data.

Input :

Output: