Weeks and Months roll-up in Time dimension

We need to change our Time dimension roll-up ('Total Year' 'Quarter' 'Month') as some users want to see the week level as well. What is the best way to do that? I still want to use the DTS and both need to be Time dimension. Thanks for your reply.

Assuming you have data down to the daily level, another option would be to create an alternate hierarchy in your time dimension. You would use your level zero members (individual days) that are currently rolling up into months and share them. Your Time dimension you would then have two children; "By Months" and "By Weeks".Under months you would have Jan, Feb, Mar, etc. Under Weeks you would have Week 1, Week 2, ... Week 52. The level zero members are the same for both. What I like about this method is it does not add any overhead since you are using shared members, and you don't run into a situation where your total "by months" varies from your total "by weeks". Since your base level data is the same you can have confidence that your data will tie out. Of course the end user needs to decide when they run their report wether they want to run by months or by weeks. My users were more than happy to do this when I explained there was no practical way to have months and weeks in the same hierarchy since weeks will overlap months. I have an outline set this way and I am using DTS effectively. If you want, send me an email and I will send you an OTL file with the Time dimension as I explained.Best Regards;

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hi
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Hi Sandy,
System Performance is always checked by a list of our lovely transactions in BASIS I generally had created one for my self and keep a track of performance..
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X axis to represent Yearin weeks and months ?

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You made two mistakes.
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Please remember to mark the replies as answers if they help and unmark them if they provide no help. If you have feedback for TechNet Subscriber Support, contact [email protected]

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tq

user_exit wrote:
Hi All,
I need to know the daily, weekly and monthly maintainance activities for Oracle EBS 11i .
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Umm yes.
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I have 3 column data like
with tab as
select 'Topshop' brand, '10-JUL-11' deliverydate, '100' qty from dual union all
select 'Topshop' brand, '10-JUL-11' deliverydate, '400' qty from dual union all
select 'NewSita' brand, '11-JUL-11' deliverydate, '200' qty from dual union all
select 'LaGress' brand, '12-JUL-11' deliverydate, '300' qty from dual union all
select 'LaGress' brand, '10-AUG-11' deliverydate, '100' qty from dual union all
select 'LaGress' brand, '11-AUG-11' deliverydate, '200' qty from dual union all
select 'Topshop' brand, '12-AUG-11' deliverydate, '300' qty from dual union all
select 'NewSita' brand, '10-SEP-11' deliverydate, '100' qty from dual union all
select 'Topshop' brand, '11-SEP-11' deliverydate, '200' qty from dual union all
select 'NewSita' brand, '12-SEP-11' deliverydate, '300' qty from dual
) select * from tabI need to convert it into 4 columns
Brand | Month | Week(start date) | Qty (sum)
Please let me know what are the options that i have, especially the date-time calculation functions available to solve such problems.
Thanks
w\

with tab as
select 'Topshop' brand, to_date('10-JUL-11', 'dd-mon-yy') deliverydate, '100' qty from dual union all
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select 'LaGress' brand, to_date('10-AUG-11', 'dd-mon-yy') deliverydate, '100' qty from dual union all
select 'LaGress' brand, to_date('11-AUG-11', 'dd-mon-yy') deliverydate, '200' qty from dual union all
select 'Topshop' brand, to_date('12-AUG-11', 'dd-mon-yy') deliverydate, '300' qty from dual union all
select 'NewSita' brand, to_date('10-SEP-11', 'dd-mon-yy') deliverydate, '100' qty from dual union all
select 'Topshop' brand, to_date('11-SEP-11', 'dd-mon-yy') deliverydate, '200' qty from dual union all
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), week_data as (
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 , trunc(deliverydate, 'day') WEEK_START
 , sum(TO_NUMBER(qty)) SUM_QTY
 from tab
 group by brand
 , to_char(deliverydate, 'Month', 'nls_date_language=american')
 , trunc(deliverydate, 'day')
), weeks as (
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 from (
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 from week_data
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select
week_data.brand,
weeks.week_start,
nvl(week_data.sum_qty,0) sum_qty
from week_data
partition by (brand)
right outer join weeks
on (weeks.week_start = week_data.week_start)
order by
weeks.week_start,
week_data.brand;You construct a set of records of all "week_start" dates from your minimum to your maximum (classic connect by level trick.)
You use a partitioned outer join to fill in the gaps in your sparse data (see doc example [url http://download.oracle.com/docs/cd/E11882_01/server.112/e17118/statements_10002.htm#i2177515]here.
Hope that helps you :-)
(PS. I dislike implicit conversions - that is the only reason I have added a TO_NUMBER to your code within the sum() ;-) )
(PPS. Actually you probably should have asked this in a new question - I believe it is not really good forum etiquette to continue in a thread that has already been answered...)

Weeks and Months roll-up in Time dimension

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