2 facts with different dimensions in 1 logical table

hello,
im trying to accomplish the set up as described per blog:
http://108obiee.blogspot.com/2009/08/joining-two-fact-tables-with-different.html
i.e. i have 2 facts, F1: D1 ; F2: D1,D2,D3;
i followed the instructions and all seem to be working fine;
however: when i put the total on the report in Answers: D1,D2, F1, F2 then the measures from F1 that are repeated every row for D2 are being added , like regular sum on the column; this is not correct;
the only correct result i can get if manually i change the Aggregation Rule to :Server Complex Aggregate on all F1 measures;
id like to ask if this is a bug of this OBI version? 10.1.3.2
i wish not to instruct my users to change the aggregation rule; id like to have the set up via rpd such, that they dont have to manipulate the aggregation rules;
did anyone got the above working with correct totals without changing the aggregation rule?
if so, id appreciate any tips on how to achieve that
thanks
rgds

Basically, you need to :
* create your physical schema with the relationship
* drag and drop your Forecast Facts measure in the same logical table than your sales fact
* define your Forecast measure as level based measure (logical column/levels/properties) with the grain of the forecast table
Documentation
http://download.oracle.com/docs/cd/E12103_01/books/admintool/admintool_BusModSetup12.html
And you have an example in OBE series with quota in excel sheet :
http://www.oracle.com/technology/obe/obe_bi/bi_ee_1013/bi_admin/biadmin.html#t8
Success
Nico

Similar Messages

Joining two fact tables with different dimensions into single logical table

Hi Gurus,
I try to accomplish in Oracle Business Intelligence 11.1.1.3.0:
F1 (D1, D2 and D3)
F2 (D1 and D2 and D4)
And we want to build a report F1 F2 D1 D2 D3 D4 to have data for:
F1 that match only for D1-D2-D3
and data for
F2 that match only D1-D2-D4
all that in one row, so D3 and D4 are not common dimensions.
I can only do:
F3 (D1, D2)
F4 (D1, D2 and D4)
And report
F3 F4 D1,D2,D4 (all that in one row, and only D4 is not a common dimension)
Here is the very good example how to accomplish the scenario 1
http://108obiee.blogspot.com/2009/08/joining-two-fact-tables-with-different.html
But looks like it does not work in 11.1.1.3.0
I get
State: HY000. Code: 10058. [NQODBC] [SQL_STATE: HY000] [nQSError: 10058] A general error has occurred. [nQSError: 43113] Message returned from OBIS. [nQSError: 14025] No fact table exists at the requested level of detail: [,,Clients,,Day,ROI,,,,EW_Names,,,,,,,,,,,,,,,,,]. (HY000)
I am sure I set up everything correctly as advised in the blog but it works with only one not a common dimension
Is it a bug in 11.1.1.3.0 or something?
Thanks,
Kate

Thanks for all your replies.
Actually, I've tried the solutions you guys mentioned. Generally speaking, the result should be displayed. However, my scenario is a little bit tricky.
table Y's figures are not the aggregation of table X for D dimension. Instead, table Y's figures include not only D dimension total, but also others (others do not mean A, B, C dimension). For example, table Y stores all food's figure, while table X stores only drink's figure. D dimension is only about drink's detail. In my scenario, other foods' figure is not provided.
So, even if I set D dimension to all/total for table X, table X's result is still not the same as table Y.
Indeed, table Y does not have a column key to join to D dimension's key. So, if I select D dimension and table Y's measures at the same time in BI Answer, result returns no data. Hence, I can't compare table X and table Y's results with selection of D dimension.
Is there any solution to solve this problem?
Edited by: TomChan on Jun 3, 2009 9:36 AM

Joining Facts with Different Grains

Hello
We have a requirement where we have two facts with different grains
DEPT_FACT - Contains (Dept_Id, Dept_Name, Revenue)
EMP_FACT - Contains (Emp_Id, Dept_Name, Is_Current_Employee)
Here is some sample data
DEPT_FACT
========
1 Sales_Dept 100,000
2 Manufacturing_Dept 200,000
EMP_FACT
========
100 Sales_Dept Y
200 Sales_Dept Y
300 Sales_Dept N
400 Manufacturing_Dept N
500 Manufacturing_Dept Y
600 Manufacturing_Dept N
Our requirement is to create an OBIEE report that shows the *"Revenue/ Number of current employees in department BY Department"*
The above example must show
Sales_Dept => $50,000 (100,000 / 2 current employees)
Sales_Dept => $200,000 (200,000 / 1 current employee)
Any suggestions on how this can be done ?

For me,
DEPT_FACT is not a fact. It's a dimension table because you have a one-to-many relationship and you have a measure in the dimension table (it's an aggregated measure).
And EMP_FACT is also not a fact because you don't have any measure on it.
But if we say that EMP_FACT is a fact. DEPT_FACT is an aggregated table from EMP_FACT.
I will :
* create a logical dimension for the employee with three levels (all, departement and detail)
* create a logical fact table with :
- one logical column for the revenue in the level all departement
- one logical column for the employee
and two physical source :
* DEPT_FACT with the departement level
* EMP_FACT with the level to detail
Success
Nico

Linking 2 facts with common dimensions

Dear all,
Request you help in this.....
I have the following tables as facts and dimensions in the physical layer
Facts: Order, Shipment
Dimensions : Product
1) I have linked each of the facts with the dimension in the physical layer.
2) I brought the model into the BMM layer with the same joins on dimension and facts as in physical layer, but gave a complex join.
now my question is:
1) If I want to have the order and shipment fact data together along with the dimension data , what all the steps I need to follow?
2) I already tried creating hierarchies to the dimension (which is conformed) and set the aggregation level to the lowest in the facts. It didnot work.
Could you please help me in this.
Thanks,
Suma

Yes ..If I do that .. I will get the results...
but the scenario I presented here is only a part of the actual requirement.
Now.... I have 6 dimensions and 8 fact tables....
few concerns...
1) Would the above solution be feasible making a single fact source for all the 8 facts? Even though we take only the required columns ,
the table structure will become huge...
2) Also for all the fact tables I need to give an outer join as per the business requirement
(Ex: an Order is made and it is not shipped yet.. so the shipment table will not have any entries for that Order.. so Order and shipment tabls are to be given an Outer join in the content tab of LTS)
so if I give outer join for all the facts I need, performance will drastically come down as the query makes a full table scan for all the 8 facts.
Is there any other way to get this done, keeping all the facts as separate fact tables only in BMM and joined on all the dimensions?

Matrix with different dimensions for each column

Hi,
I would like to have a matrix with different dimensions (rows) for each
column, for example, I want the first column has 3 rows, the second one
5 rows, the third one 10 rows, and so on.....
With a simple array it is not possible, and then I make an array (for
my columns) of clusters and each cluster has another array (rows for
that column). Is it the best way to do it? Is it correct?
Thanks,
ToNi.

Yes, everything we told you in this old thread is still true!
LabVIEW Champion . Do more with less code and in less time .

Logical fact table with fragmented data sources with different dimensions

Hello.
I have a logical fact table with four logical table sources. Three of the LTS's share the same dimensions, but the fourth LTS has one dimension (called Dim_A) less. In the physical layer the dimension Dim_A is joined to the first three physical fact tables, but not to the fourth fact table (since it doesn't have that dimensionality). In the BMM layer the logical fact table is joines to the logical dimansion Dim_A.
When I run an analysis on this RPD the measures from the logical fact is aggregated correctly (union of all four table sources) as long as I doesn't include Dim_A, but as soon as I include dimension Dim_A I get the error message:
+State: HY000. Code: 10058. [NQODBC] [SQL_STATE: HY000] [nQSError: 10058] A general error has occurred. [nQSError: 43113] Message returned from OBIS. [nQSError: 43119] Query Failed: [nQSError: 14052] Internal Error: Logical column Dim_A.Column_X has no physical sources that can be joined to the physical fact table source [Logical table sources (Priority=0): Fact_B.Fact_Y]. (HY000)+
I would like a solution where the analysis returns correctly aggregated measures also for the LTS with the "missing" dimension, but with a dimension value NULL for this LTS. Or something like this.
Is there a way to set this up in the RPD.
Thanks,
Henning Eriksen

The SQL could look something like this.
SELECT dim_a.col_1, fact_a.measure_1
FROM db.dim_a
JOIN
db.fact_a
ON fact_a.col_2 = dim_a.col_2
WHERE fact_a.date = '28-nov-2012'
UNION ALL
SELECT dim_a.col_1, SUM (fact_b.measure_1)
FROM db.dim_a
JOIN
db.fact_b
ON fact_b.col_2 = dim_a.col_2
WHERE fact_b.date = '28-nov-2012'
UNION ALL
SELECT dim_a.col_1, SUM (fact_c.measure_1)
FROM db.dim_a
JOIN
db.fact_c
ON fact_c.col_2 = dim_a.col_2
WHERE fact_c.date = '28-nov-2012'
UNION ALL
SELECT NULL, SUM (fact_d.measure_1)
FROM db.fact_d
WHERE fact_d.date = '28-nov-2012'
I would appreciate if you could give me some hints for the RPD.
Thanks,
Henning

Cubes with different dimensions based on the same fact table

I have a fact table (f_a) with three dimensions (dim_a, dim_b, dim_c) and a one measure (m_a).
Is it possible to create cube with only one dimension (dim_a)?
Data for other two dimensions (dim_b, dim_c) should be aggreagated together.
Of course i can create second fact table with only one dimension, and then creating that cube would be no problem.
But is it possible doing this directly from the primary fact table (without creating second fact table)?
Raf
PS:i use AWM 9.2 to create target cubes. Source cubes i create with OEM 9.2

At the beginning i was confused by the numberous kind of cubes...
for example when i created cube in MS i just designed cube, picked fact table, and that's all. In Oracle firstly i create project of cube (first cube) in OWB. Then i export it to the OLAP Catalog (second cube). That cube in OLAP catalog is a source cube for the AW cube (third cube). Then i need to enable AW cube for OLAPI by creating another cube in OLAP Catalog (i use 9iR2, so OLAPI doesn't have direct access to AW cubes).
I spent much time until i could see my first sample cube in Discoverer or Excel as a final user should see it. :-)
Now i'm facing another problem - when you redesign cube (for example add another dimension), you can't just "refresh" it as it was in MS. You have to delete old cube and create new one. And deleting cube isn't so simple (i'm not sure which elements i should delete).
For testing and learning purposes i just create every cube in seperate AW. deleting whole AW is much simplier that deleting one cube.
Raf

Joining Facts With Different Grains to NonConfirming Dimensions - Mystery

Hi ,
Taxonomy Used is - CD stands for Confirmed Dimension && NCD stands for Non Confirmed Dimension.
I have 3 Dimensions (CD1,NCD2,NCD3) and 2 facts (F1 & F2).
==> Fact F1 can be joined to only CD1 and NCD2 dimensions. Grain of Fact F1 is same as CD1 i.e., Nbr of records matches 1 to 1 between CD1 and F1F2
==> Fact F2 can be joined to only CD1 and NCD3 dimensions. Grain of Fact F2 is CD1 & NCD3. There could be multiple records for same value of CD1 within Fact F2, and similarly there could be multiple records for same value of NCD3. But there will always be just 1 and only 1 record for combination of CD1 and NCD3.
Report Requirements:-
1) Get few Metrics from F2 and few from F1 while applying a filter on NCD2. so below columns are needed :-
Dimension Column from NCD2 || Metric from Fact1 || Metric from Fact2
So need to understand how to enforce the relationship between Fact F2 and Dimension NCD2
2) Get few Metrics from F2 and few from F1 while applying a filter on NCD2 and also Display NCD3. so below columns are needed :-
Dimension Column from NCD2 || Dimension Column from NCD3 ||Metric from Fact1 || Metric from Fact2
==> In above case it is perfectly acceptable if Metric from Fact 1 repeats again as Fact1 is at higher Grain as compare to Fact2.
Edited by: user10799880 on Apr 15, 2013 9:37 PM

Hi,
refer to this
http://108obiee.blogspot.com/2009/08/joining-two-fact-tables-with-different.html
mark helps
thanks

How to Link two Facts with Different Time Granularity (Year, Quarter) to a Single Time Dimension

Hello All,
I have the below scenario where i have Two Facts Fact Quarterly and Fact Yearly but one Time Dimension which has Quarter grain.
So my question is how do i Establish relationship from Fact Yearly to Time Dimension??
Ex:

Hi naveej,
According to your description, you want to know how to build the relationship with time dimension and fact tables. Right?
Based on your screenshot, it's better to have only one fact table for sales and build the relationship with time dimension. To determine quarterly or yearly data only depends on how you slice the time dimension. However, I notice that the Revenue for year
is different from the aggregated Profit for quarters. If the Revenue and Profit are different measure, you need to have two fact tables. And you should build the relationship (Regular) between TimeDim and FactYearly on YYYY attribute.
Reference:
Defining a Fact Relationship
Best Regards,
Simon Hou
TechNet Community Support

Two facts with conformed dimension

Starting new thread per Alistair's request :)
I have two facts
Class Enrollment (who is enrolled in which classes)
External Test Scores (who got what score on what exam)
The only dimension they have in common is "Person".
Is it possible to build a presentation layer that includes both facts, the Person dimension, and dimensions that related to one fact but not the other (e.g. dimension "External Test Type" or dimension "Course")?
How would I set up the BI metadata to answer the question:
What was the average grade for Course ABC for students who scored above a 50 on test XYZ?
So far, for External Test Scores fact, I have created hierarchies(/dimensions) for any related dimension tables that didn't already have hierarchies defined. I then went to the Content tab for External Test Scores and set aggregation levels (lowest level for everything related to the fact, "total" level for everything NOT related to the fact).
I put both facts and the "Person" dimension into a presentation folder. I can query test scores ok, but when I add in a simple "Row Count" column from class enrollment, I get no data back.
Do I now go back and do the same Content tab settings for the Class Enrollment fact? My initial attempts at this yielded consistency check warnings of "Logical table source does not join to any fact source".
Huge thanks for suggestions.
-John

Hi John,
I tend to harp on a lot about the need for a hierachy on every logical dim, even just total -> detail. It allows this (non-conformed) approach for starters, also allows another developer to quickly ascertain the relationship between objects.
About the complex joins, I meant do as you will have done for a normal star with just the conformed dims, so thats Foreign keys where applicable in the Phyiscal layer, and Complex joins where applicable in the BMM layer. I just wanted to make a point that you should do this as per a normal normal star schema with fully conformed dimensions, and merely that the none-conformed dimension will only be connected to its relevant fact table - probably didnt need to say it as it may be more confusing!
Your correct with aggregation rules, ideally all objects in a logical fact should have an aggregation rule - otherwise it should be in a logical dimension.
As to the approach, this is the way i've always handled non-conformed dimensions when the requirement is to see both facts on the same report. Our Peak Indicators OBIEE training material on this subject is as follows :
"order" fact table, dimensioned by Date, Customer, Product.
"inventory" fact table dimensioned by Product only.
Report requirement - Show me all orders where the order_qty (order fact) is greater than the total qty in stock (inventory fact)
So like your example, we sum up both qty's and use a where clause to filter only rows where one fact measure is greater than another measure.
Whats the ideal approach ??
If you had control of the ETL perhaps you could seed an 'unknown' record in the non-conforming dimensions, and then reference this on the other fact table, but I'd say the majority of the time, the customer who wants everything by everything in their subject area needs a little education, its really not good for end users having 10's of folders with 10's of columns - we should be creating analysis subject areas to enable the answering of business questions, theres no reason why we cant combine reports from different subject areas on one dashboard page, all using a common set of prompts, but there really isnt a need to give an end user the whole BMM / DW etc in one go.......unless they are paying of course, and after you've tried to educate them they want it there way :-)

Relating facts with different grains

I'm having an issue designing a cube/star schema where I need to relate 2 fact tables that are at a different grain.
I currently have a star with 1 fact table (Insurance Premium) and 3 dimensions (Date, Account, Policy). The fact table has 1 row for each policy within each account for every quarter (quarterly snapshot). The measure is Premium.
We need to enhance this star with a new fact table that stores Lost Accounts for each quarter. The difference with this data is that we only get it at the Account Level. So the Fact table will have 1 row for each lost account per quarter. The
measure is Lost Premium.
I created the Lost Business Fact table which relates to the same Date and Account dimension as the Insurance Premium Fact table. In the cube, i created a new measure group for the Lost Premium fact table and related it to the same Date and Account
dimensions.
the 2 issues that I am having are:
1. In the Policy Dimension table, there is a field called AccountBroker, which stores the Broker for the account. So if the account has 5 policies, this table will have 5 rows and the AccountBroker field will be the same for each row. The
end users want to be able to use this field (AccountBroker) in the Lost Premium Fact table so that they can slice and dice the Lost Premium by Account Broker. The issue is that I'm not sure how to relate the Lost Premium Fact to the Policy Dimension
since the Lost Premium Fact is at Account level and the Policy Dimension is at Policy Level.
2. The other issue is that when we receive the Lost Business File for each quarter, the account may not be present in the Premium Fact because it was lost. So for example, for Q1 2014, account 1234 was lost and we receive a record in the Lost
Business File with Account 1234 as being lost and it gets inserted into the Lost Premium Fact. However, when we get the file that loads the Insurance Premium Fact for Q1 2014, this account is not present because it was lost in that quarter, so there
is no way to link the records. My first thought was to maybe take the records from the previous quarter (Q4 2012) and insert those records for Q1 2014 into the Insurance Premium Fact with 0 premium so that they exist and then there will be a match, but
not sure if there is a better design.
any ideas would be appreciated.
thanks
Scott

For me,
DEPT_FACT is not a fact. It's a dimension table because you have a one-to-many relationship and you have a measure in the dimension table (it's an aggregated measure).
And EMP_FACT is also not a fact because you don't have any measure on it.
But if we say that EMP_FACT is a fact. DEPT_FACT is an aggregated table from EMP_FACT.
I will :
* create a logical dimension for the employee with three levels (all, departement and detail)
* create a logical fact table with :
- one logical column for the revenue in the level all departement
- one logical column for the employee
and two physical source :
* DEPT_FACT with the departement level
* EMP_FACT with the level to detail
Success
Nico

Comparing facts of different dimension levels - drilldown problem.

With our customer, we do a lot of comparisons of sales budgets vs. actual sales. The sales budgets are given per month, like this:
Sales budgets: Jan 09: 40,000 EUR, Feb 09: 45,000 EUR, Mar 09: 20,000 EUR... and so on.
There is a time dimension (year -> quarter -> month -> day). Since BI does not seem to allow binding facts to other dimension levels than the lowest one (day in my example), I used a trick and modelled these sales budgets as a fact table: (expected sales, last_day_of_month)
So I have this:
Sales budgets: 01/31/09: 40,000 EUR, 02/28/09: 45,000 EUR... and so on.
This way, I can connect both actual sales and sales budgets to the same time dimension. With this, I can create an answers report that compares the two facts easily.
The problem is now that the customer wants to drill down. This is no problem with year->quarter->month. But then, BI naturally allows to drill further to day, and in this case, BI compares the sales budget of 01/31/09 with the sales on 01/31/09, producing wrong values.
I either need a solution to prevent BI from drilling down from the month level in this special answer report, or maybe I am making an error with my modelling. Are there any ideas on how to do this better?

Hi,
I'd model the repository differently, by modeling the actual sales fact on the lowest day level, and sales budget fact on monthly level. That's how I've understood the data really is defined, right? (Lowest level physical time table you already have but for sales budget you need to create also a physical time table which is on the month level. First define the correct physical joins. Then define the logical table sources in the BM layer accordingly.) In order to be able show the sales budget together with lowest level you can create the sales budget measure as a level based measure (fix the measure to the level month in the column properties-->Level in the Administration tool).
If you just want to prevent users from drilling-down on a specific dashboard report you can go to properties of the column(s) in that report and set the interaction type for both title and values to "No interaction" in the second tab of the properties menu in the front-end.
Hope this helps!
Cheers,
Ilmari

2 Facts with common dimensions

Hi All,
I am trying to developer an Answer
I have two Fact tables :- Budgets and Actuals
The two Fact Tables have common dimensions (Period, Cost Centre and Expense)
When I create an answer which combines these common dimensions and the two fact tables I can create a report that compares Actuals Vs Budgets and that works fine
However the Budget Fact has an additional dimension Bugdet Name (which can have values like 'Budget','Forecast','Allocation') that does not apply to Actuals
When I try to fliter or include the Budget Name I lose all my actuals
(Incidentally some actuals do not have budgets, some budgets do not have actuals and I want to see all rows)
Any ideas?
Cheers
Pete

Hi,
I try this:
I have in BMM one subject area with two fact and common dimension
SALES -> quantity_sold measure
and
SALES_TIME_ID -> select (amount_sold-100) as amount_sold, time_id from sales
and dimensions
TIMES
PRODUCTS
Both are joined to a SALES and just TIMES is joined to a SALES_TIME_ID in physical layer and in BMM complex join are propagated from facts to dimensions
Test in Answers - both queries are generated:
TIMES.CALENDAR_YEAR
SALES.QUANTITY_SOLD
SALES_TIME_ID.AMOUNT_SOLD
select T20553.CALENDAR_YEAR as c1,
sum(T20550.QUANTITY_SOLD) as c2
from
TIMES T20553,
SALES T20550
where ( T20550.TIME_ID = T20553.TIME_ID )
group by T20553.CALENDAR_YEAR
order by c1
------------------- Sending query to database named orcl (id: <<13806>>):
select T20553.CALENDAR_YEAR as c1,
sum(T35447.amount_sold) as c2
from
TIMES T20553,
(select (amount_sold-100) as amount_sold, time_id from sales) T35447
where ( T20553.TIME_ID = T35447.time_id )
group by T20553.CALENDAR_YEAR
order by c1
PRODUCTS.PROD_CATEGORY
TIMES.CALENDAR_YEAR
SALES.QUANTITY_SOLD
SALES_TIME_ID.AMOUNT_SOLD
select distinct D1.c2 as c1,
D1.c3 as c2,
D1.c1 as c3,
cast(NULL as DOUBLE PRECISION ) as c4
from
(select sum(T20550.QUANTITY_SOLD) as c1,
T20553.CALENDAR_YEAR as c2,
T21473.PROD_CATEGORY as c3
from
TIMES T20553,
PRODUCTS T21473,
SALES T20550
where ( T20550.PROD_ID = T21473.PROD_ID and T20550.TIME_ID = T20553.TIME_ID )
group by T20553.CALENDAR_YEAR, T21473.PROD_CATEGORY
) D1
order by c1, c2, c4
Amount sold is null because SALES_TIME_ID does not contain PROD_CATEGORY attribut, it's not common.

Multiple dimensions from single logical table

Hi,
I cannot seem to create multiple dimensions based one one single logical table. For example, I have a Time table from which I'd like to create a calendar time dimension and a fiscal time dimension. However, as soon as one dimension is created, I cannot create another dimension from the same logical table.
Is it possible?
Thanks

Jlin,
If I understood your requirement correctly you need to create multiple Hierarchies out of a single Logical Dimension table, this is possibe the base rule for creating a hierarchy is you should have a common starting point( Grand Total Level) and a common ending point( Detail Level), first create this and create sublevels and share the Detail Level as a child. This will allow you to create multiple hiearchies out of a single dimension. One level will have drill down on the Calendar dimension and one one the Fiscal and both will have the common detail key like day key.Hope this helps.
Arjun

Wny does ACR 7.3 open a .JPG with different dimensions than PS 13.0.1 x64?

I have a .jpg file that opens in Photoshop 13.0.1 x64 as an image with dimensions of 5588 x 4627 pixels. If I set Photoshop to open it in ACR 7.3 it opens with dimensions 4453 x 4418 with the image looking squished horizontally and cropped at the top.
I captured the image on a Nikon D600. I developed the NEF with DxO Optics Pro 8.1.1 and output a TIFF. I opened the TIFF in Photoshop (without using ACR) and did my editing including some transformation to create mirrored wrap for a canvas. There are versions saved as PSDs. I resized the image for output and used PS to create a JPG. That JPG causes the strange (to me) behavior when Photoshop tries to open the file.
I used the same PSD to create multiple JPGs with differing levels of quality (varyiing from 9MB to 27MB). Photoshop exhibits the same behavior on all of them.
If I process the JPG thruough ACR, the resultant image retains the bad dimensions and distortions.
The Adobe "chat" preresentative said this was expected behavior in a 2+ hour chat. He/she said that they were able to replicate the different dimensions on their end with their images.
Does anyone know if this is normal behavior? If so, why?
Has anyone experienced something similar?
Thanks,
Joe
I am running this on Win7 x64 Home Premium with 8 GB RAM. I also have LR 4.3 installed on the computer and previously used it to process the same NEF file.

I sent the JPG to a service for a print on canvas. They reported that the image was not the proper size and shape when they opened it in Photoshop. Unfortunately I have not been able to get them to tell me what pixel size it was, just rough inches (!?!?!). So I started trying things in Photoshop and came up with this strange behavior that might explain the problem at the service.

2 facts with different dimensions in 1 logical table

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