How about finding all changes for all people in a large record set?
See the follwoing:
David
1 Tom Sales 1990
2 Tom Sales 1991
3 Tom Sales 1991
4 Tom Management 1992
5 Tom Management 1992
6 Tim finance 1982
7 Tim finance 1983
8 Tim management 1984
9 Tim management 1985
On Fri, 9 Dec 2022 at 13:06, Marcos Pegoraro <marcos@f10.com.br> wrote:
Data
Staff_ID Name Department Year
1 Tom Sales 1990
2 Tom Sales 1991
3 Tom Sales 1991
4 Tom Management 1992
4 Tom Management 1992
select *, coalesce(lag(department) over(order by year), department) <> department Changed from (Values (1, 'Tom', 'Sales', 1990),(2, 'Tom', 'Sales', 1991),(3, 'Tom', 'Sales', 1991),(4, 'Tom', 'Management', 1992),(4, 'Tom', 'Management', 1992)) as x(Staff_ID, Name, Department, Year);
staff_id | name | department | year | changed ----------+------+------------+------+--------- 1 | Tom | Sales | 1990 | f 2 | Tom | Sales | 1991 | f 3 | Tom | Sales | 1991 | f 4 | Tom | Management | 1992 | t 4 | Tom | Management | 1992 | f (5 rows)