Time Related Dimension(table) in communication data model

Hi,
The most common and important thing for a communication data model to me is time metrics.
Things like mean up time, or mean down time are common KPIs we are tracking.
To make this model efficient, we need to create a time dimension can precisely and efficiently to calculate the mean.
How do we create such time dimension with common year, quarter, month, date, and time, while with UTC to local conversion?

Not sure i follow your question.
Can you give some example of the KPIs you mentioned - Mean up time and Mean down time with examples -- as detailed as possible (fact data details)?
On the face of it, it looks like these KPIs should be Calculated Measures involving Time expressions on date columns (date datatype =day+time infomation present in source columns) but nothing in it which needs a customized time dimension. Maybe not out of the box but very much doable in analytical layer (either using olap or relational rpd). So it should be do-able without needing any changes to the default time dimension available with OCDM.
HTH

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Edited by: 1007582 on May 23, 2013 2:17 AM

Can you please give some more detail as in what you have model in RPD;
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Ok, thanks.
I see I left "Copy" out of the first reply I sent.
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hi kishore,
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=================
I have logged the following data with usage tracking, posting here as examples:
1.
compile_time_sec = 0
c um_db_time_sec = 23
total_time_sec = 12
start_ts = 18-AUG-09 (14:15:47)
end_ts = 18-AUG-09 (14:16:00)
end_ts - start_ts (in sec) = 13
cache_ind_flg = N
num_cache_hits = 0
num_cache_inserted = 1
2.
compile_time_sec = 0
c um_db_time_sec = 125
total_time_sec = 110
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end_ts = 21-AUG-09 (16:47:35)
end_ts - start_ts (in sec) = 3718
cache_ind_flg = N
num_cache_hits = 0
num_cache_inserted = 0
3.
compile_time_sec = 0
c um_db_time_sec = 1252
total_time_sec = 932
start_ts = 24-AUG-09 (17:23:40)
end_ts = 24-AUG-09 (17:49:27)
end_ts - start_ts (in sec) = 1547
cache_ind_flg = N
num_cache_hits = 0
num_cache_inserted = 0

Check out DOC ID 973090.1 in metalink.

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What is being referred here as u201CStandard Processu201D since document is on u201C u2026 modeling with BIu201D?
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Performance
Compounding always implies a heritage of source systems and just because it makes sense within the
source systems does not necessarily mean that it will also make sense in data warehousing.u201D
Thanks

Hi Amanda.......
In a dimension table, any number of semantically related dimension attributes are stored in a hierarchy (parent-child relationship as a 1:N relationship). If an M:N relationship exists between dimension attributes, they are normally stored in different dimension tables.
I checked the document.........
On page 36 of this link, the author noted that
u201CAccording to the standard process, color should be in the master data table for material, like material type. But this is not possible because the material is the unique key of the master data table. We cannot have one material with multiple colors in the master data table.u201D
1.
What is being referred here as u201CStandard Processu201D since document is on u201C u2026 modeling with BIu201D?
Here the first thing that I want to tell u is that............the diagram shown here is Classic Start Schema............since Extended Star Schema will never store Master data in Dimension tables.........it stores Masterdata in seperate Master data tables..........and nowadays..............Classic Star schema is obsolet.......Dimension table will only store Dimension id and SID......
Now the Standard process is that..........anything which is Describing a master data..........can be added as an Attribute of that master data.......
Suppose........Employee is the Masterdata.then Ph no can be one of the Attribute of this master data......
So this the Standard Process.........but this cannot be followed every time.........why........already explained.....
2.
It goes on to discuss u201CDesigning M:N relationships using a compound attributeu201C as a solution to the M:N relationship in a dimension.
What is the need to address this problem with compound attributes if characteristics in M:N relationships within a dimension, such as material and color, are not a problem in BI Data Model?
Bcoz ..........we use compounding Characteris tic to define the Master data uniquely.........and we load compounding Characteristic seoerately...which is independent of the Master data........ie......compounding Characteristic there is a seperate master data tables...........so ..........problem resolved......
3.
Can you help explain the underlined cautions of the following guidelines for compound attributes (with examples if possible please):
u201CIf you can avoid compounding - do it!
Compound attributes always mean there is an overhead with respect to:
Reporting - you will always have to qualify the compound attributes within a query
Performance
Compounding always implies a heritage of source systems and just because it makes sense within the
source systems does not necessarily mean that it will also make sense in data warehousing.u201D
For Compounding Characteristic............u hav to laod the Coumpoundede master data seperately..which is a overhead...........moreover while query execution......two tables will be accessd..which may result a performance issue.......Performance can be affected when compounded characteristics are used extensively, particularly when a large number of characteristics are included in a compounding. In most cases, the need to compound is discovered during data modeling.
Regards,
Debjani.........

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Tabular data model (SSDT)
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Hi ManikantM,
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Dimension Tables
WorkOrder_D
Operation_D
Resource_D
Organization_D
Fact Tables
WorkOrder_F
Operation_F
Resource_F
Joins
WorkOrder_D -> Operation_D
Operation_D -> Resource_D
WorkOrder_D -> WorkOrder_F
Operation_D -> Operation_F
Resource_D -> Resource_F
Organization_D -> WorkOrder_D
Organization_D -> Operation_D
Organization_D -> Resource_D

Hi,
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Data Modeler - Naming Conventions

I was using Oracle Designer for several year.
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It saved you a lot of time because you kept stuck to the logical model generated your relational model and had all scripts satisfying all naming conventions you needed.
In Data Modeler i really miss the naming conventions and can't understand some parts, sometimes somebody here can help me if i have overseen something or it is just not implemented.
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Two well known tables - Employees (abbreviation EMP), Departments (abbreviation DEP)
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In a logical model you should design entities, attributes and relations and don't mess around with FK-columns.
Is there any support for surrogate keys? I don't wanna add an ID manually with every table.
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Data Modeler to prefix it automatically. The name can just be changed in the Relational View afterward.
P.S.
Surrogate Keys.... There are some pros and cons for/against this out there. I have seen a lot of Oracle Projects and in all except one i always had a surrogate key column. It really makes life
easier. In the one no-surrogate-key-project we began to add surrogate keys after a while...

COLUMN(!) is added with every Foreign key relation, i could live with that, but there is no way to tell
Data Modeler to prefix it automaticallyLook at "General options>Naming Standard>templates" - you can define template for FK columns/attributes and then apply them for whole relational/logical model using "Apply Naming .." functionality from pop-up menu in the browser. For Logical model (FK attributes) - you also need to clear related setting at "General options>Logical>Keep as the name of originating attribute".
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There is no support for surrogate keys in current release.
Philip

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Hi Hari,
Why can't you create two tables in BMM one is as FACt and DIM and place all description columns in dim and measures in fact?
this way you would achieve Star Schema in BMM
http://www.varanasisaichand.com/2012/04/fact-and-dimension-from-single-source.html (2nd approach)
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Ed Price, Azure & Power BI Customer Program Manager (Blog,
Small Basic,
Wiki Ninjas,
Wiki)
Answer an interesting question?
Create a wiki article about it!

Time Related Dimension(table) in communication data model

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