Rolling up monthly data to quarterly - sql

Question

I have monthly data for each company and it's associated MRR (Monthly Revenue) as of the month end date. I am trying to build a quarterly report which shows the progression of the company within the quarter. Following is the reproducible sample dataset with quarter end dates:
WITH
quarter_end_date AS
(
SELECT '2021-04-30' q_end_date
UNION ALL
SELECT '2021-07-31' q_end_date
UNION ALL
SELECT '2021-10-31' q_end_date
UNION ALL
SELECT '2022-01-31' q_end_date
),
data AS
(
SELECT '2020-05-31' as_of_date, 'A' company_id, '100' mrr,'new' category
UNION ALL
SELECT '2020-06-30' as_of_date, 'A' company_id, '100' mrr,'no change' category
UNION ALL
SELECT '2020-07-31' as_of_date, 'A' company_id, '100' mrr,'no change' category
UNION ALL
SELECT '2020-08-31' as_of_date, 'A' company_id, '100' mrr,'no change' category
UNION ALL
SELECT '2020-09-30' as_of_date, 'A' company_id, '0' mrr,'churn' category
UNION ALL
SELECT '2020-10-31' as_of_date, 'A' company_id, '100' mrr,'new' category
UNION ALL
SELECT '2020-11-30' as_of_date, 'A' company_id, '100' mrr,'no change' category
UNION ALL
SELECT '2020-12-31' as_of_date, 'A' company_id, '0' mrr,'churn' category
UNION ALL
SELECT '2021-01-31' as_of_date, 'A' company_id, '0' mrr,'new' category
UNION ALL
SELECT '2021-02-28' as_of_date, 'A' company_id, '100' mrr,'no change' category
UNION ALL
SELECT '2021-03-31' as_of_date, 'A' company_id, '100' mrr,'no change' category
UNION ALL
SELECT '2021-04-30' as_of_date, 'A' company_id, '120' mrr,'expansion' category
UNION ALL
SELECT '2021-05-31' as_of_date, 'A' company_id, '90' mrr,'contraction' category
UNION ALL
SELECT '2021-06-30' as_of_date, 'A' company_id, '70' mrr,'contraction' category
UNION ALL
SELECT '2021-07-31' as_of_date, 'A' company_id, '100' mrr,'expansion' category
UNION ALL
SELECT '2021-08-31' as_of_date, 'A' company_id, '100' mrr,'no change' category
UNION ALL
SELECT '2021-09-30' as_of_date, 'A' company_id, '120' mrr,'expansion' category
UNION ALL
SELECT '2021-10-31' as_of_date, 'A' company_id, '90' mrr,'contraction' category
UNION ALL
SELECT '2021-11-30' as_of_date, 'A' company_id, '0' mrr, 'churn' category
),
The MRR dataset (above CTE data) doesn’t store company info once it churns (stops paying subscription or cancels the service). The approach I'm using is capable of capturing any churn which happens in the start of the quarter or the end of quarter but it doesn’t if churn happens within the quarter. My SQL:
step_1
AS(
SELECT *,
LAG(mrr,1) OVER (PARTITION BY company_id ORDER BY as_of_date) prev_m1_mrr,
LAG(mrr,2) OVER (PARTITION BY company_id ORDER BY as_of_date) prev_m2_mrr,
LAG(mrr,3) OVER (PARTITION BY company_id ORDER BY as_of_date) quarter_start_mrr,
FROM data
)
SELECT *
FROM step_1
CROSS JOIN quarter_end_date q
WHERE q.q_end_date = step_1.as_of_date
ORDER BY q.q_end_date DESC
Output:
q_end_date
Company_id
mrr
category
prev_m1_mrr
prev_m2_mrr
quarter_start_mrr
2021-10-31
A
90
contraction
120
100
100
2021-07-31
A
100
expansion
70
90
120
2021-04-30
A
120
expansion
100
100
null
Expected Output:
q_end_date
Company_id
mrr
category
prev_m1_mrr
prev_m2_mrr
quarter_start_mrr
2022-01-31
A
null
churn
0
0
90
2021-10-31
A
90
contraction
120
100
100
2021-07-31
A
100
expansion
70
90
120
2021-04-30
A
120
expansion
100
100
null

Answer 1

I am assuming that data of all companies are in the same table, otherwise the query will be straightforward. I added a few values with a second company ‘B’. The query works, but it will give ‘Churn’ as the category whenever data is not present in the entire quarter for that company.That also includes the period when the company did not even start using the service. That can be filtered out later with simple queries based on start date if needed.
Second thing is I added another CTE for the list of companies.
WITH
quarter_end_date AS
(
SELECT '2021-04-30' q_end_date
UNION ALL
SELECT '2021-07-31' q_end_date
UNION ALL
SELECT '2021-10-31' q_end_date
UNION ALL
SELECT '2022-01-31' q_end_date
),
companies as
(SELECT 'A'as company_id
union all
SELECT 'B'as company_id
),
data AS
(
SELECT '2021-02-28' as_of_date, 'A' company_id, '100' mrr,'new' category
UNION ALL
SELECT '2021-03-31' as_of_date, 'A' company_id, '100' mrr,'no change' category
UNION ALL
SELECT '2021-04-30' as_of_date, 'A' company_id, '120' mrr,'expansion' category
UNION ALL
SELECT '2021-05-31' as_of_date, 'A' company_id, '90' mrr,'contraction' category
UNION ALL
SELECT '2021-06-30' as_of_date, 'A' company_id, '70' mrr,'contraction' category
UNION ALL
SELECT '2021-07-31' as_of_date, 'A' company_id, '100' mrr,'expansion' category
UNION ALL
SELECT '2021-08-31' as_of_date, 'A' company_id, '100' mrr,'no change' category
UNION ALL
SELECT '2021-09-30' as_of_date, 'A' company_id, '120' mrr,'expansion' category
UNION ALL
SELECT '2021-10-31' as_of_date, 'A' company_id, '90' mrr,'contraction' category
UNION ALL
SELECT '2021-11-30' as_of_date, 'A' company_id, '0' mrr, 'churn' category
union all
SELECT '2021-10-31' as_of_date, 'B' company_id, '100' mrr,'no change' category
UNION ALL
SELECT '2021-11-30' as_of_date, 'B' company_id, '120' mrr,'expansion' category
UNION ALL
SELECT '2021-12-31' as_of_date, 'B' company_id, '90' mrr,'contraction' category
UNION ALL
SELECT '2022-01-31' as_of_date, 'B' company_id, '100' mrr, 'expansion' category
),
step_1
AS(
SELECT *,
LAG(mrr,1) OVER (PARTITION BY company_id ORDER BY as_of_date) prev_m1_mrr,
LAG(mrr,2) OVER (PARTITION BY company_id ORDER BY as_of_date) prev_m2_mrr,
LAG(mrr,3) OVER (PARTITION BY company_id ORDER BY as_of_date) quarter_start_mrr,
FROM data
)
SELECT q_end_date,c.company_id,
mrr,IFNULL(category,'churn') as category,IFNULL(prev_m1_mrr,'0') as prev_m1_mrr, IFNULL(prev_m2_mrr,'0') as prev_m2_mrr,IFNULL(quarter_start_mrr,lead(mrr) over (partition by c.company_id order by q_end_date desc)) as quarter_start_mrr
FROM companies c cross join quarter_end_date q left join step_1 s on q.q_end_date = s.as_of_date and c.company_id=s.company_id
ORDER BY company_id,q.q_end_date DESC
Output: