Reg Snow Flake schema design

Hi Experts,
Can any one post few scenarios regarding Implementation of snow flake schema which can not be converted to star schema in BMM layer for better under standing about schemas. I searched my blogs but i did not found exact answer.
Regards,
Rafi

Rafi,
Check these links
http://iniu.net/content/obiee-define-star-schema-over-snowflake-data-model-data-source
http://www.varanasisaichand.com/2012/05/denormalizing-physical-tables-in-bmm.html
http://majendi.blogspot.com/2009/01/obiee-snowflakes-and-stars-part-3.html
http://blogs.datadirect.com/2012/02/obiee-oracle-business-intelligence-integration-with-salesforce-com-crm-and-database-com-via-odbc.html
In general if you follow the OBI best practices you never get snowflake schema in BMM layer.
If helps pls mark

Similar Messages

  • Star schema and snow flake schema

    can any one tell star schema is better or snow flake schema is better why
    thx in advance

    Hi,
    Difference : http://www.diffen.com/difference/Snowflake_Schema_vs_Star_Schema
    When it comes to OBIEE star schema will be easy to configure because it don't involve much tables where as snow flake schema need to denormalize the tables in BMM layer to get the desired model but again it all depends on how your system was designed
    HR schema which is more like a snow-flake schema structure
    Refer http://www.varanasisaichand.com/2012/05/denormalizing-physical-tables-in-bmm.html
    Thanks,
    Saichand

  • Multiple star or snow flake schema for universe

    Hi,
    I would like to know following things
    1. Can we use more than one star or snow flake schema for an universe? and how to do this?
    2. Using multiple shemas for one universe is it good practice or not?
    Regards,
    Manjunath

    Manjunath,
    This is exactly where BusinessObjects excels.
    When dealing with multiple fact tables, you use contexts.
    Contexts are very simple to understand and you must take your time to do so if you are going to successfully develop universes based on more than one fact table. No matter what universe you build, the rule for contexts is always the same; there are no different circumstances based on, say, industry.
    Each context starts with a base table, typically a fact table, where all its joins are at the many end of the relationship. The joins are then followed out through the joined tables up other joins where they in turn are at the many end, as in a snowflake schema.
    For example, consider the very basic schema below:
    D1 -< D2 -< F1 >- D3 -< F2 >- D4
    There are two tables that only have many joins attached to them - F1 and F2.
    Starting with F1, I can move to D2. I can also move from there to D1. In the other direction, I can move from F1 to D3. However, I cannot move from D3 to F2 because the join cardinalities are in the wrong direction. So, I've found all the joins that belong in the first context. They are D1-D2, D2-F1 and F1-D3. By the same process, I will get to the second context containing joins D3-F2 and F2-D4.
    It doesn't work well with many-to-many joins, but you really shouldn't be facing these in a well-designed multi-star.
    As for one-to-one joins, set the cardinality as one-to-many in the direction that you know the relationship should be in for the ownership to work out correctly..
    The process that I've described above is essentially how the Detect Contexts algorithm works.
    The only remaining thing for you to read up on is the SQL parameters but essentially you need ot be able to select multiple contexts and generate multiple sql statements for each context. Otherwise, what's the point in defining them?!!
    Hope that clears it up for you.
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  • Question for integration star and snow flake schema in data warehouse

    Dear Reader,
    I facing a problem like that
    I have two data warehouse, one use star schema, other use snow flake schema. I would like to integrate both of them into one data warehouse. What is the strategy should these two data warehouse adopt in order to integrate int one data warehouse?
    Should I scrap both data warehouse and build a new one instead, or scrap one of them and use the other?
    What factors should be considered in order for me to more easily resolve the differences between the two data warehouses.
    Please advise. Thank you very much.

    Hi Mallis,
    This is a very broad question and the answer depends on so many factors. Please go through the following articles to get an
    understanding of what the differences are when to use which.
    When do you use a star schema and when to use a snowflake schema -
    http://www.information-management.com/news/10000243-1.html
    Star vs Snowflake Schemas – what’s your belief? –
    http://www.networkworld.com/community/blog/star-vs-snowflake-schemas-%E2%80%93-what%E2%80%99s-your-belie
    Hope this helps!

  • Snow flake schema to star schema

    Hi Gurus,
    I am having a snow flake schema how can i turn it into star schema.
    thanks,
    kumar

    In Obiee You can use multiple table source and join 2 tables abd make as singel table.
    EX A->B->C
    Now we need to join B,C and call it D. Then A->D is star Schema.
    Steps is. Join B and C in the physical layer. join B to A Drop B into the Logical layer, Now Drop C on top od the B.
    Table B wil get all the column from C. Here it wont create 2 sources, It will look like single source only.
    IN the column mapping you can mpa the column to desired physical table.
    Later as usula you can join B and A in logical layer.
    Get A and B into presentaion layer.
    mak if correct/helpful
    fiaz

  • Snow Flake Schema

    anybody give me some knowledge about snow flake schema.
    in which type of situations,useually snow flake schema creates in data model.
    can you please provide me with example?
    Thanks in Advance.

    In case of large dimesnsion, we will split them to smaller dimensions, this is to make the table better manageable.
    Let's take an example you have a Dimension table which stores the information about the shop details, you may have a seperate dimension table which hold the dempgraphic information of the sales area this provide the logical separation of data.
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    If you have snowflake defined, will be flattened the same in the logical layer of OBIEE.
    Thanks,
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  • How to make snow flake schema to star in Business layer

    i have snow flake data model.
    anybody tell me how can i convert that snow flake to star by doing the adding multiple sources to a dimention.
    how to do the joins with 2 dimention tables in the business layer

    Hi
    we can do that for example we have dimension table that connected with another dimension table in physical layer
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    Regards
    prabhu haridass

  • URGENT MODELING SNOW FLAKE SCHEMA

    Hi i have 2 fact tables fact1 and fact 2 and four dimension tables D1,D2,D3 ,D4 & D1.1 ,D1.2 the relations in the data model is like this :
    NOTE: D1.1 and D1.2 are derived from D1
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    Now from D1 there is a child level like this: [D1 --(1:M)..> D1.1 and from D1.1.. 1:M..> D1.2.. 1:M..> D4]
    Please help me how to design in physical layer and BMM layer. I will be very glad to you guys this is very urgent requirement.
    PS: Deepak Gupta you are very helpful earlier please help me.
    Thanks,
    ch

    They too are snowflake.... but we speak snowflake w.r.t dimension attached to FACT...
    Alternate solution, but of the same type..
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    In Physical Layer, just have all the joins as Physical Foreign Key Join, just the way you have described, making sure that
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    Now work with Aliases only in BMM Layer
    Here D4 is snowflaked...
    So in BMM just bring D4 Alias from Physical Layer and onto it, drop D1.1 alias, D1.2 alias and D1.A2 alias , so that now you have 4 logical table sources under 'Logical Table folder' D4.
    This is it....
    The Only thing is that you ll have to create two Aliases for D1...
    Thanks
    Ashish Gupta

  • Snow flake problem

    Hello
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    I suggest you do some reading on dimensional modeling and use aliases and multi-source LTSs
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  • URGENT!!!!! Schema design help

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    my bad I didnt explain that correctly
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