def quality_check(df, name):
    """
    Count checks on table to ensure completeness of data.
    :param df: spark dataframe to check counts on
    :param name: name of the dataframe
    """

    total_count = df.count()

    if total_count == 0:
        print(f"Data quality check failed for {name} with zero records!")
    else:
        print(f"Data quality check passed for {name} with {total_count} records.")
    return 0