def METHOD_NAME(database):
    """Creates MSSQL tables for testing that mimic a Mosaiq DB.
    Pulls data from the *.csv files and types_map.toml file within this
    same directory and loads them into an MSSQL database.
    """
    # https://github.com/pymssql/pymssql/issues/504#issuecomment-449746112
    pymssql.Binary = bytearray
    sql_types_map = _get_sqlalchemy_types_map()
    tables, types_map = _load_csv_and_toml()
    column_types_to_use = [sql_types_map[item] for item in COLUMN_TYPES_TO_USE]
    type_casting = {
        sql_types_map[key]: sql_types_map[item] for key, item in TYPE_CASTING.items()
    }
    for table_name, table in tables.items():
        logging.debug("Creating mimic table for %s", table_name)
        column_types = types_map[table_name]
        for column_name, a_type in column_types.items():
            try:
                column_types[column_name] = type_casting[a_type]
            except KeyError:
                pass
        index_label = table.columns[0]
        table = table.set_index(index_label)
        for column_name, a_type in column_types.items():
            if not a_type in column_types_to_use:
                table = table.drop(columns=[column_name])
                continue
            if a_type == sql_types_map["largebinary"]:
                table[column_name] = table[column_name].apply(
                    lambda x: base64.decodebytes(x.encode("utf-8"))
                )
                continue
        mocks.dataframe_to_sql(
            table,
            table_name,
            index_label=index_label,
            dtype=column_types,
            database=database,
            if_exists="replace",
        )