Act as a data analyst working in Excel. Help me clean the table {{table_name}}, which contains {{data_description}}, so I can use it for {{analysis_goal}}. Dates and numbers follow this format: {{date_and_number_format}}. First, profile the data: list each column with its apparent type and the problems you find, such as blanks, duplicates, inconsistent spellings, mixed date formats, numbers stored as text, extra spaces, and outliers. Do not delete or overwrite data; put fixes in new columns so the original stays intact. Ask me before any judgment call, such as merging near-duplicate names. Return: 1. A data quality summary by column 2. A cleaning checklist in the order to do it 3. The Excel formulas or Power Query steps for each fix 4. Checks that the cleaned data still matches the original row counts and totals 5. A short data dictionary for the cleaned table