Snowflake - How to create summary table containing unique records - snowflake-cloud-data-platform

Question

I'm looking for some Snowflake syntax assistance in how to generate a summary table or view from an existing table. My summary table should have 1 row per unique id from the existing table along with boolean values indicating if the various milestones (as per the summary column names) have been hit. Any help is appreciated as I am a Snowflake novice. Thanks.
Existing Table
Desired Summary Table/View

Answer 1

So using Himanshu's data, thank you:
WITH fake_data(id, updated, pipeline_id, stage_id) AS (
SELECT column1, to_date(column2,'mm/dd/yyyy hh:mm:ss'), column3, column4
FROM VALUES
(1111, '02/01/2022 09:01:00', 'A', '1' ),
(1111, '02/01/2022 10:01:00', 'A', '2' ),
(1111, '02/01/2022 11:01:00', 'B', '5' ),
(2222, '02/02/2022 13:01:00', 'A', '1' ),
(2222, '02/03/2022 18:01:00', 'B', '5' ),
(2222, '02/04/2022 07:01:00', 'B', '6' ),
(3333, '02/02/2022 14:01:00', 'A', '1' ),
(3333, '02/03/2022 18:01:00', 'A', '2' ),
(3333, '02/03/2022 07:01:00', 'C', '7' ),
(3333, '02/03/2022 21:01:00', 'C', '8' ),
(3333, '02/05/2022 17:01:00', 'C', '9' )
)
we are doing an aggregation across each id and we want to use COUNT_IF to see how many row meet out criteria, and if it is >0 we are happy
SELECT
id,
count_if(pipeline_id='A')>0 AS hit_stage_a,
count_if(pipeline_id='B')>0 AS hit_stage_b,
count_if(pipeline_id='C')>0 AS hit_stage_c,
count_if(stage_id='4')>0 AS hit_stage_4,
count_if(stage_id='5')>0 AS hit_stage_5,
count_if(stage_id='6')>0 AS hit_stage_6
FROM fake_data
GROUP BY 1
ORDER BY 1;
gives:
ID
HIT_STAGE_A
HIT_STAGE_B
HIT_STAGE_C
HIT_STAGE_4
HIT_STAGE_5
HIT_STAGE_6
1111
TRUE
TRUE
FALSE
FALSE
TRUE
FALSE
2222
TRUE
TRUE
FALSE
FALSE
TRUE
TRUE
3333
TRUE
FALSE
TRUE
FALSE
FALSE
FALSE

Answer 2

try this and see if this helps to get what you want.
SELECT ID, decode(HIT_PIPELINE_A, NULL,FALSE,TRUE) ,
decode(HIT_PIPELINE_B, NULL,FALSE,TRUE),
decode(HIT_PIPELINE_C, NULL,FALSE,TRUE),
decode(HIT_STAGE_4, NULL,FALSE,TRUE),
decode(HIT_STAGE_5, NULL,FALSE,TRUE),
decode(HIT_STAGE_6, NULL,FALSE,TRUE) FROM
(
SELECT * from tab1
PIVOT(MAx(PIPELINE_ID) FOR stage_id IN ('1','2','3','4','5','6'))
AS P(ID,DT,HIT_PIPELINE_A,HIT_PIPELINE_B,HIT_PIPELINE_C,HIT_STAGE_4,HIT_STAGE_5,HIT_STAGE_6)
) order by ID;
create or replace table Tab1 (ID varchar2(100), updated date, pipeline_id varchar2(100), stage_id varchar2(10));
insert into tab1 values(1111, to_date('02/01/2022 09:01:00','mm/dd/yyyy hh:mm:ss'), 'A', '1' );
insert into tab1 values(1111, to_date('02/01/2022 10:01:00','mm/dd/yyyy hh:mm:ss'), 'A', '2' );
insert into tab1 values(1111, to_date('02/01/2022 11:01:00','mm/dd/yyyy hh:mm:ss'), 'B', '5' );
insert into tab1 values(2222, to_date('02/02/2022 13:01:00','mm/dd/yyyy hh:mm:ss'), 'A', '1' );
insert into tab1 values(2222, to_date('02/03/2022 18:01:00','mm/dd/yyyy hh:mm:ss'), 'B', '5' );
insert into tab1 values(2222, to_date('02/04/2022 07:01:00','mm/dd/yyyy hh:mm:ss'), 'B', '6' );
insert into tab1 values(3333, to_date('02/02/2022 14:01:00','mm/dd/yyyy hh:mm:ss'), 'A', '1' );
insert into tab1 values(3333, to_date('02/03/2022 18:01:00','mm/dd/yyyy hh:mm:ss'), 'A', '2' );
insert into tab1 values(3333, to_date('02/03/2022 07:01:00','mm/dd/yyyy hh:mm:ss'), 'C', '7' );
insert into tab1 values(3333, to_date('02/03/2022 21:01:00','mm/dd/yyyy hh:mm:ss'), 'C', '8' );
insert into tab1 values(3333, to_date('02/05/2022 17:01:00','mm/dd/yyyy hh:mm:ss'), 'C', '9' );