Related
I'm facing an issue with the following query. It gave me this error [SELECT list expression references column integration_start_date which is neither grouped nor aggregated at [34:63]]. In particular, it points to the first 'when' in the result table, which I don't know how to fix. This is on BigQuery if that helps. I see everything is written correctly or I could be wrong. Seeking for help.
with plan_data as (
select format_date("%Y-%m-%d",last_day(date(a.basis_date))) as invoice_date,
a.sponsor_id as sponsor_id,
b.company_name as sponsor_name,
REPLACE(SUBSTR(d.meta,STRPOS(d.meta,'merchant_id')+12,13),'"','') as merchant_id,
a.state as plan_state,
date(c.start_date) as plan_start_date,
a.employee_id as square_employee_id,
date(
(select min(date)
from glproductionview.stats_sponsors
where sponsor_id = a.sponsor_id and sponsor_payroll_provider_identifier = 'square' and date >= c.start_date) )
as integration_start_date,
count(distinct a.employee_id) as eligible_pts_count, --pts that are in active plan and have payroll activities (payroll deductions) in the reporting month
from glproductionview.payroll_activities as a
left join glproductionview.sponsors as b
on a.sponsor_id = b.id
left join glproductionview.dc_plans as c
on a.plan_id = c.id
left join glproductionview.payroll_connections as d
on a.sponsor_id = d.sponsor_id and d.provider_identifier = 'rocket' and a.company_id = d.payroll_id
where a.payroll_provider_identifier = 'rocket'
and format_date("%Y-%m",date(a.basis_date)) = '2021-07'
and a.amount_cents > 0
group by 1,2,3,4,5,6,7,8
order by 2 asc
)
select invoice_date,
sponsor_id,
sponsor_name,
eligible_pts_count,
case
when eligible_pts_count <= 5 and date_diff(current_date(),integration_start_date, month) <= 12 then 20
when eligible_pts_count <= 5 and date_diff(current_date(),integration_start_date, month) > 12 then 15
when eligible_pts_count > 5 and date_diff(current_date(),integration_start_date, month) <= 12 then count(distinct square_employee_id)*4
when eligible_pts_count > 5 and date_diff(current_date(),integration_start_date, month) > 12 then count(distinct square_employee_id)*3
else 0
end as fees
from plan_data
group by 1,2,3,4;
I have two tables – activity and purchase
Activity table:
user_id date videos_watched
1 2020-01-02 3
1 2020-01-04 5
1 2020-01-07 5
Purchase table:
user_id purchase_date
1 2020-01-01
2 2020-02-02
What I would like to do is to get a 30 day rolling average since purchase on how many videos has been watched.
The base query is like this:
SELECT
DATEDIFF(DAY, p.purchase_date, a.date) AS day_since_purchase,
AVG(A.VIDEOS_VIEWED)
FROM PURCHASE P
LEFT OUTER JOIN ACTIVITY A ON P.USER_ID = A.USER_ID AND
A.DATE >= P.PURCHASE_DATE AND A.DATE <= DATEADD(DAY, 30, P.PURCHASE_DATE)
GROUP BY 1;
However, the Activity table only has records for each day a video has been logged. I would like to fill in the blanks for days a video has not been viewed.
I have started to look into using a CTE like this:
WITH cte AS (
SELECT date('2020-01-01') as fdate
UNION ALL
SELECT CAST(DATEADD(day,1,fdate) as date)
FROM cte
WHERE fdate < date('2020-04-01')
) select * from cte
cross join purchases p
left outer join activity a
on p.user id = a.user_id
and a.fdate = p.purchase_date
and a.date >= p.purchase_date and a.date <= dateadd(day, 30, p.purchase_date)
The end goal is to have something like this:
days_since_purchase videos_watched
1 3
2 0 --CTE coalesce inserted value
3 0
4 5
Been trying for the last couple of hours to get it right, but still can't really get the hang of it.
If you want to fill in the gaps in the result set, then I think you should be generating integers rather than dates:
WITH cte AS (
SELECT 1 as day_since_purchase
UNION ALL
SELECT 1 + day_since_purchase
FROM cte
WHERE day_since_purchase < 4
)
SELECT cte.day_since_purchase, COALESCE(avg_videos_viewed, 0)
FROM cte LEFT JOIN
(SELECT DATEDIFF(DAY, p.purchase_date, a.date) AS day_since_purchase,
AVG(A.VIDEOS_VIEWED) as avg_videos_viewed
FROM purchases p JOIN
activity a
ON p.user id = a.user_id AND
a.fdate = p.purchase_date AND
a.date >= p.purchase_date AND
a.date <= dateadd(day, 30, p.purchase_date)
GROUP BY 1
) pa
ON pa.day_since_purchase = cte.day_since_purchase;
You can use a recursive query to generate the 30 days following each purchase, then bring the activity table:
with cte as (
select
purchase_date,
client_id,
0 days_since_purchase,
purchase_date dt
from purchases
union all
select
purchase_date,
client_id,
days_since_purchase + 1
dateadd(day, days_since_purchase + 1, purchase_date)
from cte
where days_since_purchase < 30
)
select
c.days_since_purchase,
avg(colaesce(a. videos_watch, 0)) avg_ videos_watch
from cte c
left join activity a
on a.client_id = c.client_id
and a.fdate = c.purchase_date
and a.date = c.dt
group by c.days_since_purchase
Your question is unclear on whether you have a column in the activity table that stores the purchase date each row relates to. Your query has column fdate but not your sample data. I used that column in the query (without such column, you might end up counting the same activity in different purchases).
I have seen something similar but I can't get this to work:
SELECT
CNTRSINTDATA.DIM_CNTRS_DATE_ENTITY.CALENDAR_MONTH
, CNTRSINTDATA.FACT_QUICKBOOKS_TRANS_TSI.TSI_NOMINAL_CODE
, CNTRSINTDATA.DIM_CNTRS_TSI_COA.TSI_NOMINAL_ACC
, CNTRSINTDATA.DIM_CNTRS_DATE_ENTITY.CNTRS_FIN_YEAR
, SUM (CNTRSINTDATA.FACT_QUICKBOOKS_TRANS_TSI.QB_TRANS_AMOUNT) AS CNTRS_ACC_BUDGET
FROM
CNTRSINTDATA.FACT_QUICKBOOKS_TRANS_TSI
, CNTRSINTDATA.DIM_CNTRS_DATE_ENTITY
, CNTRSINTDATA.DIM_CNTRS_TSI_COA
WHERE
CNTRSINTDATA.FACT_QUICKBOOKS_TRANS_TSI.QB_TRANS_DATE = CNTRSINTDATA.DIM_CNTRS_DATE_ENTITY.CALENDAR_DATE
AND CNTRSINTDATA.DIM_CNTRS_DATE_ENTITY.CNTRS_FIN_YEAR LIKE '2017'
AND CNTRSINTDATA.FACT_QUICKBOOKS_TRANS_TSI.TSI_NOMINAL_CODE = CNTRSINTDATA.DIM_CNTRS_TSI_COA.TSI_NOMINAL_CODE
AND CNTRSINTDATA.FACT_QUICKBOOKS_TRANS_TSI.TSI_NOMINAL_CODE = '6598'
GROUP BY
CNTRSINTDATA.FACT_QUICKBOOKS_TRANS_TSI.TSI_NOMINAL_CODE
, CNTRSINTDATA.DIM_CNTRS_TSI_COA.TSI_NOMINAL_ACC
, CNTRSINTDATA.DIM_CNTRS_DATE_ENTITY.CALENDAR_MONTH
, CNTRSINTDATA.DIM_CNTRS_DATE_ENTITY.CNTRS_FIN_YEAR;`
The above query returns results for:
Feb-17 250
Jul-17 400
Jun-17 654
May-17 654
Oct-17 150
Nov-17 250
Aug-17 250
Sep-17
I need the rest of the months to also come back with zero's as there no transactions on the account that month.
Jan-17 0
Feb-17 250
Mar-17 0
Apr-17 0
Jul-17 400
Jun-17 654
May-17 654
Oct-17 150
Nov-17 250
Aug-17 250
Sep-17 0
Dec-17 0
There is a date table that has all the months as VARCHAR2 against date. Just cant get the right syntax. Can anyone help please?
Let's break that down and make it more manageable.
Firstly, translate that to SQL-92 join syntax and add some aliases
SELECT
dcde.CALENDAR_MONTH
, fqtt.TSI_NOMINAL_CODE
, dctc.TSI_NOMINAL_ACC
, dcde.CNTRS_FIN_YEAR
, SUM (fqtt.QB_TRANS_AMOUNT) AS CNTRS_ACC_BUDGET
FROM
CNTRSINTDATA.FACT_QUICKBOOKS_TRANS_TSI fqtt
INNER JOIN CNTRSINTDATA.DIM_CNTRS_DATE_ENTITY dcde
ON fqtt.QB_TRANS_DATE = dcde.CALENDAR_DATE
INNER JOIN CNTRSINTDATA.DIM_CNTRS_TSI_COA dctc
ON AND fqtt.TSI_NOMINAL_CODE = dctc.TSI_NOMINAL_CODE
WHERE
dcde.CNTRS_FIN_YEAR LIKE '2017'
AND
fqtt.TSI_NOMINAL_CODE = '6598'
GROUP BY
fqtt.TSI_NOMINAL_CODE
, dctc.TSI_NOMINAL_ACC
, dcde.CALENDAR_MONTH
, dcde.CNTRS_FIN_YEAR;
Next, you said that there exists a date record (presumably in CNTRSINTDATA.DIM_CNTRS_DATE_ENTITY), so swap that around
SELECT
dcde.CALENDAR_MONTH
, fqtt.TSI_NOMINAL_CODE
, dctc.TSI_NOMINAL_ACC
, dcde.CNTRS_FIN_YEAR
, SUM (fqtt.QB_TRANS_AMOUNT) AS CNTRS_ACC_BUDGET
FROM
CNTRSINTDATA.DIM_CNTRS_DATE_ENTITY dcde
INNER JOIN CNTRSINTDATA.FACT_QUICKBOOKS_TRANS_TSI fqtt
ON fqtt.QB_TRANS_DATE = dcde.CALENDAR_DATE
INNER JOIN CNTRSINTDATA.DIM_CNTRS_TSI_COA dctc
ON AND fqtt.TSI_NOMINAL_CODE = dctc.TSI_NOMINAL_CODE
WHERE
dcde.CNTRS_FIN_YEAR LIKE '2017'
AND
fqtt.TSI_NOMINAL_CODE = '6598'
GROUP BY
fqtt.TSI_NOMINAL_CODE
, dctc.TSI_NOMINAL_ACC
, dcde.CALENDAR_MONTH
, dcde.CNTRS_FIN_YEAR;
Finally, you don't actually want inner joins because that eliminates tuples where there is no match. In this case, you want a left join because you want to have the left value even if no value exists on the right. You also need to coalesce your sum expression to 0 because (for reasons I cannot fathom), the SQL standard defines the sum of a bunch records only containing null as null.
SELECT
dcde.CALENDAR_MONTH
, fqtt.TSI_NOMINAL_CODE
, dctc.TSI_NOMINAL_ACC
, dcde.CNTRS_FIN_YEAR
, COALESCE(SUM (fqtt.QB_TRANS_AMOUNT), 0) AS CNTRS_ACC_BUDGET
FROM
CNTRSINTDATA.DIM_CNTRS_DATE_ENTITY dcde
LEFT JOIN CNTRSINTDATA.FACT_QUICKBOOKS_TRANS_TSI fqtt
ON fqtt.QB_TRANS_DATE = dcde.CALENDAR_DATE
LEFT JOIN CNTRSINTDATA.DIM_CNTRS_TSI_COA dctc
ON AND fqtt.TSI_NOMINAL_CODE = dctc.TSI_NOMINAL_CODE
WHERE
dcde.CNTRS_FIN_YEAR LIKE '2017'
AND
fqtt.TSI_NOMINAL_CODE = '6598'
GROUP BY
fqtt.TSI_NOMINAL_CODE
, dctc.TSI_NOMINAL_ACC
, dcde.CALENDAR_MONTH
, dcde.CNTRS_FIN_YEAR;
Give that a try and see if it is what you want
#Adam G,
Thank you for your suggestion. I actually got an idea from your commentry and instead created a select statement to get all the months I needed first. After that I joined to a select statement picking up the transactions where months matched and it worked. See below (come table names have changed)
SELECT DISTINCT
CNTRS_DATE_ENTITY.CALENDAR_MONTH
, CNTRS_DATE_ENTITY.CNTRS_FIN_MONTH_POS
, COALESCE (TRANS_DATA.TRANS_AMOUNT,0) AS TRANS_AMOUNT
FROM
CNTRSINTDATA.DIM_CNTRS_DATE_ENTITY CNTRS_DATE_ENTITY
LEFT JOIN
(
SELECT
QBS_TRANS_TSI.QB_NOMINAL_CODE
, TO_CHAR(QBS_TRANS_TSI.QB_TRANS_DATE, 'Mon-YY') AS TRANS_MONTH
, COALESCE (SUM(QBS_TRANS_TSI.QB_TRANS_AMOUNT),0) AS TRANS _AMOUNT
FROM
CNTRSINTDATA.FACT_QBS_TRANS_TSI QBS_TRANS_TSI
WHERE
QBS_TRANS_TSI.TSI_NOMINAL_CODE = '6598'
GROUP BY
QBS_TRANS_TSI.QB_NOMINAL_CODE
, TO_CHAR(QBS_TRANS_TSI.QB_TRANS_DATE, 'Mon-YY')
) TRANS_DATA
ON TRANS_DATA.TRANS_MONTH = CNTRS_DATE_ENTITY.CALENDAR_MONTH
WHERE
CNTRS_DATE_ENTITY.CNTRS_FIN_YEAR LIKE '2017'
ORDER BY
CNTRS_DATE_ENTITY.CNTRS_FIN_MONTH_POS
However the results have all the months but have blanks in the entity columns where the sum is zero. Any ideas on a remedy for this?
Here is one possible solution:
Generate fake empty transactions for the target period
for example using CTE:
declare #StartDate datetime = '20170101'
declare #EndDate datetime = '20171231'
;
with dt as
(
select #StartDate As 'thedate'
union all
select dateadd(month, 1, thedate) from dt where thedate < dateadd(month, -1, #EndDate)
)
select
dt.thedate 'row date',
datename(month,dt.thedate) 'Month',
YEAR(dt.thedate) 'Year',
0 'Amount '
from dt
Now you can add them to the transaction table (like union all) or you can do a left join with filtering on the result of your query.
I hope it helps! 🙂
I have a requirement where I supposed to roll customer data in the prior period of 365 days.
Table:
CREATE TABLE orders (
persistent_key_str character varying,
ord_id character varying(50),
ord_submitted_date date,
item_sku_id character varying(50),
item_extended_actual_price_amt numeric(18,2)
);
Sample data:
INSERT INTO orders VALUES
('01120736182','ORD6266073' ,'2010-12-08','100856-01',39.90),
('01120736182','ORD33997609' ,'2011-11-23','100265-01',49.99),
('01120736182','ORD33997609' ,'2011-11-23','200020-01',29.99),
('01120736182','ORD33997609' ,'2011-11-23','100817-01',44.99),
('01120736182','ORD89267964' ,'2012-12-05','200251-01',79.99),
('01120736182','ORD89267964' ,'2012-12-05','200269-01',59.99),
('01011679971','ORD89332495' ,'2012-12-05','200102-01',169.99),
('01120736182','ORD89267964' ,'2012-12-05','100907-01',89.99),
('01120736182','ORD89267964' ,'2012-12-05','200840-01',129.99),
('01120736182','ORD125155068','2013-07-27','201443-01',199.99),
('01120736182','ORD167230815','2014-06-05','200141-01',59.99),
('01011679971','ORD174927624','2014-08-16','201395-01',89.99),
('01000217334','ORD92524479' ,'2012-12-20','200021-01',29.99),
('01000217334','ORD95698491' ,'2013-01-08','200021-01',19.99),
('01000217334','ORD90683621' ,'2012-12-12','200021-01',29.990),
('01000217334','ORD92524479' ,'2012-12-20','200560-01',29.99),
('01000217334','ORD145035525','2013-12-09','200972-01',49.99),
('01000217334','ORD145035525','2013-12-09','100436-01',39.99),
('01000217334','ORD90683374' ,'2012-12-12','200284-01',39.99),
('01000217334','ORD139437285','2013-11-07','201794-01',134.99),
('01000827006','W02238550001','2010-06-11','HL 101077',349.000),
('01000827006','W01738200001','2009-12-10','EL 100310 BLK',119.96),
('01000954259','P00444170001','2009-12-03','PC 100455 BRN',389.99),
('01002319116','W02242430001','2010-06-12','TR 100966',35.99),
('01002319116','W02242430002','2010-06-12','EL 100985',99.99),
('01002319116','P00532470001','2010-05-04','HO 100482',49.99);
Using the query below I am trying to get the number of distinct customers by order_submitted_date:
select
g.order_date as "Ordered",
count(distinct o.persistent_key_str) as "customers"
from
generate_series(
(select min(ord_submitted_date) from orders),
(select max(ord_submitted_date) from orders),
'1 day'
) g (order_date)
left join
orders o on o.ord_submitted_date between g.order_date - interval '364 days'
and g.order_date
WHERE extract(year from ord_submitted_date) <= 2009
group by 1
order by 1
This is the output I expected.
Ordered Customers
2009-12-03 1
2009-12-10 1
When I execute the query above I get incorrect results.
How can I make this right?
To get your expected output ("the number of distinct customers") - only days with actual orders 2009:
SELECT ord_submitted_date, count(DISTINCT persistent_key_str) AS customers
FROM orders
WHERE ord_submitted_date >= '2009-1-1'
AND ord_submitted_date < '2010-1-1'
GROUP BY 1
ORDER BY 1;
Formulate the WHERE conditions this way to make the query sargable, and input easy.
If you want one row per day (from the earliest entry up to the latest in orders) - within 2009:
SELECT ord_submitted_date AS ordered
, count(DISTINCT o.persistent_key_str) AS customers
FROM (SELECT generate_series(min(ord_submitted_date) -- single query ...
, max(ord_submitted_date) -- ... to get min / max
, '1d')::date FROM orders) g (ord_submitted_date)
LEFT join orders o USING (ord_submitted_date)
WHERE ord_submitted_date >= '2009-1-1'
AND ord_submitted_date < '2010-1-1'
GROUP BY 1
ORDER BY 1;
SQL Fiddle.
Distinct customers per year
SELECT extract(year from ord_submitted_date) AS year
, count(DISTINCT persistent_key_str) AS customers
FROM orders
GROUP BY 1
ORDER BY 1;
SQL Fiddle.
A "Case" in CRM has a field called "Status" with four options.
I'm trying to
build a report in CRM that fills a table with every week of the year (each row is a different week), and then counts the number of cases that have each Status option (the columns would be each of the Status options).
The table would look like this
Status 1 Status 2 Status 3
Week 1 3 55 4
Week 2 5 23 5
Week 3 14 11 33
So far I have the following:
SELECT
SUM(case WHEN status = 1 then 1 else 0 end) Status1,
SUM(case WHEN status = 2 then 1 else 0 end) Status2,
SUM(case WHEN status = 3 then 1 else 0 end) Status3,
SUM(case WHEN status = 4 then 1 else 0 end) Status4,
SUM(case WHEN status = 5 then 1 else 0 end) Status5
FROM [DB].[dbo].[Contact]
Which gives me the following:
Status 1 Status 2 Status 3
2 43 53
Now I need to somehow split this into 52 rows for the past year and filter these results by date (columns in the Contact table). I'm a bit new to SQL queries and CRM - any help here would be much appreciated.
Here is a SQLFiddle with my progress and sample data: http://sqlfiddle.com/#!2/85b19/1
Sounds like you want to group by a range. The trick is to create a new field that represents each range (for you one per year) and group by that.
Since it also seems like you want an infinite range of dates, marc_s has a good summary for how to do the group by trick with dates in a generic way: SQL group by frequency within a date range
So, let's break this down:
You want to make a report that shows, for each contact, a breakdown, week by week, of the number of cases registered to that contact, which is divided into three columns, one for each StateCode.
If this is the case, then you would need to have 52 date records (or so) for each contact. For calendar like requests, it's always good to have a separate calendar table that lets you query from it. Dan Guzman has a blog entry that creates a useful calendar table which I'll use in the query.
WITH WeekNumbers AS
(
SELECT
FirstDateOfWeek,
-- order by first date of week, grouping calendar year to produce week numbers
WeekNumber = row_number() OVER (PARTITION BY CalendarYear ORDER BY FirstDateOfWeek)
FROM
master.dbo.Calendar -- created from script
GROUP BY
FirstDateOfWeek,
CalendarYear
), Calendar AS
(
SELECT
WeekNumber =
(
SELECT
WeekNumber
FROM
WeekNumbers WN
WHERE
C.FirstDateOfWeek = WN.FirstDateOfWeek
),
*
FROM
master.dbo.Calendar C
WHERE
CalendarDate BETWEEN '1/1/2012' AND getutcdate()
)
SELECT
C.FullName,
----include the below if the data is necessary
--Cl.WeekNumber,
--Cl.CalendarYear,
--Cl.FirstDateOfWeek,
--Cl.LastDateOfWeek,
'Week: ' + CAST(Cl.WeekNumber AS VARCHAR(20))
+ ', Year: ' + CAST(Cl.CalendarYear AS VARCHAR(20)) WeekNumber
FROM
CRM.dbo.Contact C
-- use a cartesian join to produce a table list
CROSS JOIN
(
SELECT
DISTINCT WeekNumber,
CalendarYear,
FirstDateOfWeek,
LastDateOfWeek
FROM
Calendar
) Cl
ORDER BY
C.FullName,
Cl.WeekNumber
This is different from the solution Ben linked to because Marc's query only returns weeks where there is a matching value, whereas you may or may not want to see even the weeks where there is no activity.
Once you have your core tables of contacts split out week by week as in the above (or altered for your specific time period), you can simply add a subquery for each StateCode to see the breakdown in columns as in the final query below.
WITH WeekNumbers AS
(
SELECT
FirstDateOfWeek,
WeekNumber = row_number() OVER (PARTITION BY CalendarYear ORDER BY FirstDateOfWeek)
FROM
master.dbo.Calendar
GROUP BY
FirstDateOfWeek,
CalendarYear
), Calendar AS
(
SELECT
WeekNumber =
(
SELECT
WeekNumber
FROM
WeekNumbers WN
WHERE
C.FirstDateOfWeek = WN.FirstDateOfWeek
),
*
FROM
master.dbo.Calendar C
WHERE
CalendarDate BETWEEN '1/1/2012' AND getutcdate()
)
SELECT
C.FullName,
--Cl.WeekNumber,
--Cl.CalendarYear,
--Cl.FirstDateOfWeek,
--Cl.LastDateOfWeek,
'Week: ' + CAST(Cl.WeekNumber AS VARCHAR(20)) +', Year: ' + CAST(Cl.CalendarYear AS VARCHAR(20)) WeekNumber,
(
SELECT
count(*)
FROM
CRM.dbo.Incident I
INNER JOIN CRM.dbo.StringMap SM ON
I.StateCode = SM.AttributeValue
INNER JOIN
(
SELECT
DISTINCT ME.Name,
ME.ObjectTypeCode
FROM
CRM.MetadataSchema.Entity ME
) E ON
SM.ObjectTypeCode = E.ObjectTypeCode
WHERE
I.ModifiedOn >= Cl.FirstDateOfWeek
AND I.ModifiedOn < dateadd(day, 1, Cl.LastDateOfWeek)
AND E.Name = 'incident'
AND SM.AttributeName = 'statecode'
AND SM.LangId = 1033
AND I.CustomerId = C.ContactId
AND SM.Value = 'Active'
) ActiveCases,
(
SELECT
count(*)
FROM
CRM.dbo.Incident I
INNER JOIN CRM.dbo.StringMap SM ON
I.StateCode = SM.AttributeValue
INNER JOIN
(
SELECT
DISTINCT ME.Name,
ME.ObjectTypeCode
FROM
CRM.MetadataSchema.Entity ME
) E ON
SM.ObjectTypeCode = E.ObjectTypeCode
WHERE
I.ModifiedOn >= Cl.FirstDateOfWeek
AND I.ModifiedOn < dateadd(day, 1, Cl.LastDateOfWeek)
AND E.Name = 'incident'
AND SM.AttributeName = 'statecode'
AND SM.LangId = 1033
AND I.CustomerId = C.ContactId
AND SM.Value = 'Resolved'
) ResolvedCases,
(
SELECT
count(*)
FROM
CRM.dbo.Incident I
INNER JOIN CRM.dbo.StringMap SM ON
I.StateCode = SM.AttributeValue
INNER JOIN
(
SELECT
DISTINCT ME.Name,
ME.ObjectTypeCode
FROM
CRM.MetadataSchema.Entity ME
) E ON
SM.ObjectTypeCode = E.ObjectTypeCode
WHERE
I.ModifiedOn >= Cl.FirstDateOfWeek
AND I.ModifiedOn < dateadd(day, 1, Cl.LastDateOfWeek)
AND E.Name = 'incident'
AND SM.AttributeName = 'statecode'
AND SM.LangId = 1033
AND I.CustomerId = C.ContactId
AND SM.Value = 'Canceled'
) CancelledCases
FROM
CRM.dbo.Contact C
CROSS JOIN
(
SELECT
DISTINCT WeekNumber,
CalendarYear,
FirstDateOfWeek,
LastDateOfWeek
FROM
Calendar
) Cl
ORDER BY
C.FullName,
Cl.WeekNumber