SQL Server 2022

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select @@version;


(No column name)


Microsoft SQL Server 2022 (RTM) - 16.0.1000.6 (X64) 
 Oct  8 2022 05:58:25 
 Copyright (C) 2022 Microsoft Corporation
 Express Edition (64-bit) on Windows Server 2019 Standard 10.0 <X64> (Build 17763: ) (Hypervisor)



CREATE TABLE mytable(
   DataId   INT  NOT NULL 
  ,Time     DATETIME  NOT NULL
  ,Username VARCHAR(14) NOT NULL
  ,DataA    VARCHAR(9) NOT NULL
  ,DataB    VARCHAR(14) NOT NULL
  ,DataC    VARCHAR(11) NOT NULL
);
INSERT INTO mytable(DataId,Time,Username,DataA,DataB,DataC) VALUES (1,'2023-01-01 12:00:00','User1','Truc','Much','Bazar');
INSERT INTO mytable(DataId,Time,Username,DataA,DataB,DataC) VALUES (1,'2023-01-01 06:00:00','User1','Truc','Much','Bazar2');
INSERT INTO mytable(DataId,Time,Username,DataA,DataB,DataC) VALUES (1,'2023-01-01 00:00:00','User1','Truc','Much2','Bazar2');
3 rows affected

select dataid, time, username, col, lag_val as old_value, val as new_value
from (
    select t.*, v.*,
        lag(val, 1, val) over(partition by dataid, col order by time) lag_val
    from mytable t
    cross apply ( values ('DataA', DataA), ('DataB', DataB), ('DataC', DataC) ) v(col, val)
) t
where val <> lag_val
order by dataid, time


dataid
time
username
col
old_value
new_value


1
2023-01-01 06:00:00.000
User1
DataB
Much2
Much

1
2023-01-01 12:00:00.000
User1
DataC
Bazar2
Bazar

dataid	time	username	col	old_value	new_value
1	2023-01-01 06:00:00.000	User1	DataB	Much2	Much
1	2023-01-01 12:00:00.000	User1	DataC	Bazar2	Bazar