Star Schema/Cube Question

I am fairly new to OLAP and cubes, yet have the task of creating one from a star schema.
The schema has 2 fact tables, instead of most examples I see online with 1 fact table. Should this be 2 cubes? Can it be 1? Any information could prove helpful...thanks!

Assuming the fact tables have related dimensions, then I would recommend one Analytic Workspace with multiple cubes inside that AW. That would allow them to share one or more dimensions. There is an example of this in the Oracle By Example lesson: http://www.oracle.com/technology/obe/obe10gdb/bidw/awm/awm.htm
I am fairly new to OLAP and cubes, yet have the task
of creating one from a star schema.
The schema has 2 fact tables, instead of most
examples I see online with 1 fact table. Should this
be 2 cubes? Can it be 1? Any information could
prove helpful...thanks!

Similar Messages

  • Star schema design question

    Hi!
    I`m trying to build a dw with patient data. I`m mostly interested in the patients` visits table, which will be used for a facts table and the patient table.
    The patient table contains among others the following data:
    patient (id, sex, marital_status, nationality, profession, zip).
    My question is what should I do with the "patient" table. There seem to be three options:
    1. Use it to build a one level dimension and just use the above fields as simple dimension attributes.
    2. Create separate hierarchies for each attribute in the patient dimension
    (e.g. patient -> sex, patient -> nationality, patient -> zip -> city e.t.c.)
    3. Create separate dimensions for each attribute (e.g. a professions dimensions which will be joined with the patient visits facts table) and no patient dimension.
    What would you do?
    Thank you...

    I guess my answer would be based on how you intend to physically implement. If you are deploying this relationally, then I would definitely have a single patient dimension table. Perhaps build a hierarchy for patient -> zip -> city, but I'd keep gender and nationality as simple "attributes" of the dimension.
    If you're going to deploy this through an OLAP cube, its a bit more complex, because the standard Oracle OLAP functionality makes it impossible to do sums over attributes unless they are part of the hierarchy. In that case, I guess I'd deploy multiple dimensions (geneder, nationality, one a generic patient one that includes the hierarchy patient -> zip -> city).
    If you attempt to do your option #2, you'll be in trouble if you need to show queries that cross the hierarchies, i.e. "Male American patients who live in zip code 12345".
    Hope this helps,
    Scott
    p.s. you could also deploy this relationally, and then put an AW on top of the relational model.

  • Star Schema and Cubes

    Hi,
    I'm learning the basic concept of data warehousing and I've some question in this regards.
    1) I want to know, are we have to first create star schema and tables according to that star schema in dbms, from that star schema we have to built cubes OR we directly build cubes from extracted data through OLTP systems.
    2) secondly, when we create cubes, in which formate they are store in dbms and are they directly load in the memory at run time?
    Please clarify me in these concepts as new to data warehouse I've certain concept misunderstanding in this regards. Answers will be highly appreciated
    Regards,
    D.Abbasi

    1) I want to know, are we have to first create star schema and tables according to that star schema in dbms, from that star schema we have to built cubes OR we directly build cubes from extracted data through OLTP systems. Star schema is the Dimensional Modeling Technique and that need to considered while creating Dimension and not cubes.
    So you need to create first design your database either in Start schema or Snow flag and then need to create dimension tables and after wards Cubes.
    2) secondly, when we create cubes, in which format they are store in dbms and are they directly load in the memory at run time?Cubes and Dimensions are stored in Database in some different format.
    This is the nice article regarding how the data is store in DB,
    http://www.dba-oracle.com/t_olap_dimensions_cubes.htm
    Cheers
    Nawneet
    Edited by: Nawneet on Mar 29, 2010 5:47 AM
    Edited by: Nawneet on Mar 29, 2010 5:50 AM

  • Star schema question

    Hi,
    I have a question about the realization of the star schema. I have familiarized me with the basic concepts of dimensions and fact tables. But what I don’t get is how I “combine” the dimensions with the fact table. I know that the fact table includes the dimension-IDs and measures. But do I use the joiner-operator in the OWB to join the dimension-ID (IDs of the dims are the criteria for the joiner condition) to create the fact table?
    So my understanding is when I have for example 3 dimensions (product dimension, sales dimension, time dimension) and one fact table.
    The realization looks like this:
    product dim ->
    sales dim -> joiner operator = fact table with the IDs of the dims and measure
    time dim ->
    Please correct me if I am wrong.
    If there is something that I can read to this subject of matter it would be very nice if someone could post it.
    Thx

    Hi,
    first you load the dimensions. Every entry has an id (surrogate key) and some business key (coming from the data source).
    When you load the fact, you use the business key from the data source to join (using a joiner or lookup operator) the dimension and get the id (surrogate key) from it. You only load the id and the measures into the fact table.
    Make sure to handle the case that the business key is null or no entry in the dimension can be found.
    If you query the fact table you must always join the dimensions.
    Regards,
    Carsten.

  • Show Star Schema of Cube in SAP BW

    Hello experts,
    is ist possible in SAP BW to show  the star schema of  a Cube?
    Thanx
    Axel

    Hi ,
       Goto RSA1 -> in the left side you will find tabs like Modeling, Monitor etc, the last tab is meta data repository -> click it -> right side it will display the screen -> here select info cube it displays active cubes in your system find your info cube here under graphical display you will get 3 options select display as star schema.

  • Newbie question : why is star schema fast and efficient?

    Hi all,
    just a stupid question, but I haven't been able to find a proper
    answer so far...
    Why is star schema a good design for Data Marts and DWH?
    What is the underlying reason that makes it attractive
    performance wise?
    Why wouldn't just one big table with all the data in it and with
    the proper indexes be enough?
    Thanks all!!
    Regards
    Vincent

    There are several reasons to use star schemas, particularly in
    Oracle.
    A flat table like you asked about looks attractive but has
    several flaws, i.e. massive data redundancy, no logical
    groupings, no aggregation (or additional redundant data
    aggregated), etc.
    A start schema is semi-denormalized to allow easy reporting. A
    truely normalized system is diffucult to report against be cause
    you may have to join many tables to return just 2 pieces of
    related data. A star schema enables you to join to only a single
    dimension table to the fact table to return the same 2 pieces of
    data. If you're returning many pieces of data, a star schema
    keeps access very simple. Most third party reporting tools
    recognize star schemas and will build your where clauses behind
    the scenes making them a lot more useful to end users.
    Oracle is adding optimizations to the cbo for start schemas.
    Using dimensions, materialized views, partitions, IOTs, etc
    greatly enhances performance for queries against massive amounts
    of data. It does make loading the data more difficult but the
    trade off at query time is worth it.
    A flat table structure, besides having a lot of redundant data,
    is hard to optimize. When you have terebytes of data, a flat
    table structure gets scary even with indexes.
    This is just my opinion, hope that helps.
    Lewis

  • Question on BW Star Schema

    Hello all
    Please help me understand the DIM/SID table concept.
    I was going through the BW star schema and I was curious to know the importance of Dimension table. What is wrong with putting the SID ID directly in Fact table instead of relating it through the DIM table?
    Please post a link to documentation on SAP Star Schema, if you have.
    This is how I understood
    Fact Table:
    DIM_CUST     | QUANTITY
    001          | 50
    002          | 100
    001          | 60
    Dimension Table:
    DIM_CUST     | SID_CUST
    001          | 011
    002          | 022
    003          | 033
    SID Table:
    SID_CUST     | CUST_ID
    011          | 123ABC
    022          | 767TYT
    033          | 989UHY
    - In Fact table we identify unique transaction by combination of Cust ID and Date/time
    - We can have the same Cust ID appearing multiple times in Fact table for different transactions
    - DIM and SID table have 1:1 relation
    - In SID table, SID ID has 1:1 relation with a customer ID
    If they are all right, I still want to know why can't we have SID ID appear directly in Fact table?
    Please explain.
    Thanks
    -Sudhakar
    Message was edited by: Sudhakar Upadhyaya
    Message was edited by: Sudhakar Upadhyaya

    About you last question:
    "Can anyone give me a scenario where we use multiple characteristic in the same domension?"
    The first consideration about the number of characteristic involved is the most evident, but consider even the problem related with the number of key fields of a DB Table (no more than 16).
    Speaking about a scenario: let's say you have to report on Division, Sales Org, Sales Off, and Sales Pers: putting all this char in a "line item" dimension makes sense only in order to elimiate the corresponding Dimesion Table, but are you sure that the query will be faster that putting all of the in the same Dimension? And what about the comprehension of the underlying schema? Think about a complex one, with 50 or more Chars ...
    By the way the easier way to solve such a doubts is to read something about MultiDimensional Data Modeling: there's a wide litterature about this topic that can't be summarized in few rows without omitting important notes
    If you don't want to start with "heavy" books search in http://service.sap.com/bw for a doc about Multidimensional Data Modeling (see under InfoIndex / DataModeling / BW ASAP for 2.0B Phase 2: Multi Dimensional Data modeling (doc)) that's an old doc (before 2k), but a very good starting point, that will answer to you questons about SidID and DimID.
    Hope it helps
    GFV

  • Regarding Extended star schema

    Hi Friends,
    In Extended star schema,master data will load separately ,which will connect through sid's to dimension table .
    My question is.. This master data tables can be used other than this cube ?
    Please tell me i am in confusion.
    Thanks in advace,
    Regards,
    ramnaresh.

    Hi
    InfoCubes are made up of a number of InfoObjects. All InfoObjects (characteristics and key figures) are available independent of the InfoCube. Characteristics refer to master data with their attributes and text descriptions.
    An InfoCube consists of several InfoObjects and is structured according to the star schema. This means there is a (large) fact table that contains the key figures for the InfoCube, as well as several (smaller) dimension tables which surround it. The characteristics of the InfoCube are stored in these dimensions.
    An InfoCube fact table only contains key figures, in contrast to a DataStore object, whose data part can also contain characteristics. The characteristics of an InfoCube are stored in its dimensions.
    The dimensions and the fact table are linked to one another using abstract identification numbers (dimension IDs) which are contained in the key part of the particular database table. As a result, the key figures of the InfoCube relate to the characteristics of the dimension. The characteristics determine the granularity (the degree of detail) at which the key figures are stored in the InfoCube.
    Characteristics that logically belong together (for example, district and area belong to the regional dimension) are grouped together in a dimension. By adhering to this design criterion, dimensions are to a large extent independent of each other, and dimension tables remain small with regards to data volume. This is beneficial in terms of performance. This InfoCube structure is optimized for data analysis.
    The fact table and dimension tables are both relational database tables.
    Characteristics refer to the master data with their attributes and text descriptions. All InfoObjects (characteristics with their master data as well as key figures) are available for all InfoCubes, unlike dimensions, which represent the specific organizational form of characteristics in one InfoCube.
    Integration
    You can create aggregates to access data quickly. Here, the InfoCube data is stored redundantly and in an aggregated form.
    You can either use an InfoCube directly as an InfoProvider for analysis and reporting, or use it with other InfoProviders as the basis of a MultiProvider or InfoSet.
    See also:
    Checking the Data Loaded in the InfoCube
    If the above info is useful, please grant me points

  • Star Schema tables Creation

    If I am creating a BI analytical application from sample Sales Hisotory schema's transactional data, what is the first Step I need to do? Should I create a star schema from the transactional tables? If this is correct, What I tool I need to use to create such tables with data? I believe once this is done I can create dimensions , measures and cubes using OWM11g. Some on please help me. I am very very new to OLAP , But has lots of interest in it
    Thanks
    George

    Hi George,
    If you are working with 11g - did you install all the latest patches? I strongly recommend applying all available patches when working with 11g. All the information you need is here - http://www.oracle.com/technology/products/bi/olap/collateral/olap_certification.html
    As for your question about the criteria for desgining dimension tables, the best advice I can offer is to work with star or snowflake dimensions. You can also see sample schema designs for both at these links
    Also, in case you haven't already seen it, there is a good blog posting on working with different kinds of dimensions/hierarchies here - http://oracleolap.blogspot.com/2008/01/olap-workshop-4-managing-different.html
    Finally, you might find this [white paper|http://www.oracle.com/technology/products/warehouse/pdf/Benefits%20of%20a%20multi-dimensional%20model.pdf] useful as you say you are new to OLAP
    Let me know how you get on
    Thanks,
    Stuart Bunby
    OLAP Blog: http://oracleOLAP.blogspot.com
    OLAP Wiki: http://wiki.oracle.com/page/Oracle+OLAP+Option
    OLAP on OTN: http://www.oracle.com/technology/products/bi/olap/index.html
    DW on OTN : http://www.oracle.com/technology/products/bi/db/11g/index.html

  • Dimension Hieracrhy in Star Schema

    Hi devs,
    I'm in the process of creating OLAP dimensions using AWM 10.2.0.30A on 10gR2 database, and have successfully created some flat (no levels) dimensions. Now I have to create another dimension, which based on existing model, has parent and child in same dimension table at database end.
    When I first attempt to do this using the default "Star Schema" setting for type of dimension table in the mapping section, I get the below error:
    oracle.AWXML.AWException: Action BUILDDATABASE failed on object TA_DMT_OWNER.GLA_MP
    at oracle.AWAction.BuildDatabase.Execute(BuildDatabase.java:737)
    at oracle.olap.awm.wizard.awbuild.BuildWizardHelper$1.construct(BuildWizardHelper.java:184)
    at oracle.olap.awm.ui.SwingWorker$2.run(SwingWorker.java:109)
    at java.lang.Thread.run(Thread.java:534)
    Caused by: oracle.AWXML.AWException: ***Error Occured in BUILD_DRIVER: In __XML_SEQUENTIAL_LOADER: In __XML_LOAD_HIERS: In __XML_SET_GID_FREL: One or more loops have been detected in relationship GLA_MP!PROD_PARENTREL over GLA_MP!PROD. The 1 items involved are TD.
    at oracle.AWAction.BuildDatabase.Execute(BuildDatabase.java:604)
    ... 3 more
    I've tried changing the type to "Snowflake" but get the same error. Do you have suggestions as to how to best handle these scenarios?
    **Little more background to the data. We DO have surrogate keys in table as well, which is used in fact table. If I do not use the "use natural keys from data source" and use "generate surrogate keys in AW" option, dimension is built successfully. So my follow-up question is, when I build cube will AW know to link the dimension correctly from fact based on surrogates generated by AWM even though those surrogate keys do not physically exist in fact?
    Edited by: user8659932 on Oct 30, 2009 7:58 AM

    When I first attempt to do this using the default "Star Schema" setting for type of dimension table in the mapping section, I get the below error:
    oracle.AWXML.AWException: Action BUILDDATABASE failed on object TA_DMT_OWNER.GLA_MP
    at oracle.AWAction.BuildDatabase.Execute(BuildDatabase.java:737)
    at oracle.olap.awm.wizard.awbuild.BuildWizardHelper$1.construct(BuildWizardHelper.java:184)
    at oracle.olap.awm.ui.SwingWorker$2.run(SwingWorker.java:109)
    at java.lang.Thread.run(Thread.java:534)
    Caused by: oracle.AWXML.AWException: ***Error Occured in BUILD_DRIVER: In __XML_SEQUENTIAL_LOADER: In __XML_LOAD_HIERS: In __XML_SET_GID_FREL: One or more loops have been detected in relationship GLA_MP!PROD_PARENTREL over GLA_MP!PROD. The 1 items involved are TD.
    at oracle.AWAction.BuildDatabase.Execute(BuildDatabase.java:604)This error comes when you have a member rolloing to a different via two different path. If you use surrogate key then as you said the error is gone.
    **Little more background to the data. We DO have surrogate keys in table as well, which is used in fact table. If I do not use the "use natural keys from data >source" and use "generate surrogate keys in AW" option, dimension is built successfully. It appended the some text to the value.
    So my follow-up question is, when I build cube will AW know to link >the dimension correctly from fact based on surrogates generated by AWM even though >those surrogate keys do not physically exist in fact?Yes it do. You needn't to fabricate that kind of fact data.
    You can check this link -> http://www.oracle.com/technology/products/bi/olap/index.html
    Thanks,
    Brijesh
    Edited by: Brijesh Gaur on Oct 30, 2009 9:08 PM

  • Why do we need SSIS and star schema of Data Warehouse?

    If SSAS in MOLAP mode stores data, what is the application of SSIS and why do we need a Data Warehouse and the ETL process of SSIS?
    I have a SQL Server OLTP database. I am using SSIS to transfer my SQL Server data from OLTP database to a Data Warehouse database that contains fact and dimension tables.
    After that I want to create cubes using SSAS form Data Warehouse data.
    I know that MOLAP stores data. Do I need any Data warehouse with Fact and Dimension tables?
    Is not it better to avoid creating Data warehouse and create cubes directly from OLTP database?

    Another thing to note is data stored in transactional system may not always be in end user consumable format for ex. we may use bit fields/flags to represent some details in OLTP as storage required ius minimum but presenting them as is would not make any
    sense to user as they would not know what each bit value represents. In such cases we apply some transformations and convert data into useful information for users to understand. This is also in the warehouse so that information in warehouse can directly be
    used for reporting. Also in many cases the report will merge data from multiple source systems so merging it on the fly in report would be tedious and would have hit on report server. In comparison bringing them onto common layer (warehouse) and prebuilding
    aggregates would be benefitial for the report performance.
    I think (not sure) we join tables in SSAS queries and calculate aggregations in it.
    I think SSAS stores these values and joined tables and we do not need to evaluates those values again and this behavior is like a Data Warehouse.
    Is not it?
    So if I do not need historical data, Can I avoid creating Data Warehouse?
    On the backend SSAS uses queries only to extract the data
    B/w I was not explaining on SSAS. I was explaining on what happens inside datawarehouse  which is a relational database by itself. SSAS is used to built cube (OLAP structures) on top of datawarehouse. star schema is easier for defining relationships
    and buidling aggregations inside SSAS as its simple and requires minimal lookups to be performed. Also data would be held at lowest granularity level which can easily be aggregated to required levels inside OLAP cubes. Cube processing is very resource
    intensive and using OLTP system would really have a huge impact on processing performance as its nnot denormalized and also doing tranformation etc on the fly adds up to complexity. Precreating a layer (data warehouse) having data in required format would
    make cube processing easier and simpler as it has to just cross join tables and aggregate data based on relationships defined and level needed inside the cube.
    Please Mark This As Answer if it helps to solve the issue Visakh ---------------------------- http://visakhm.blogspot.com/ https://www.facebook.com/VmBlogs

  • Star schema without a fact table?

    Hi,
    I'm preparing my warehouse for using with Discoverer and my question is about the star schema.
    - Is a star schema directly associated with data warehouse?
    - Can I talk about a star schema if a) I do not have a fact table (no summarized values) and b) if I do not have a dimension of time?
    The problem is, I'm thinking of usine Discoverer but should I use it if it's not connected to a data warehouse?
    As I told, I'd like to modelized my data "like" a star schema but my "center table" will contain only the foreign key of my dimensions; no time dimensions, no aggregate data in the center table (fact table).
    Is there another word for the model I'd like to do?
    Thank in advance.

    Hi,
    Is a star schema directly associated with data warehouse?Not really, a star schema is just one where there is one large fact table joined to many smaller dimension tables using key fields. You usually see this in data warehouses.
    Can I talk about a star schema if a) I do not have a fact table (no summarized values) and b) if I do not have a dimension of time?A star schema must have a fact table but it doesn't need contain summarised values or a time dimension.
    You can use Discoverer with any Oracle database, it doesn't have to be a data warehouse.
    Rod West

  • Star schema design

    Hi,
    I know that in classical star schema the dimension tables sits within the info cube and so we cannot use this dimension table in any other cube we need to have separate dimension table for that cube thought it might be having same data. I also know to over come this redundancy extended star schema came into picture where we have SID table and we keep the dimension table out of the cube and reuse the dimension tables across many cubes.
    Now what i don't understand is that instead of having Separate SID tables for linking the dimension and fact tables   why cant we make the DIMENSION table generic and keep them out of the infocube so that we can same the same dimension table for many infocube in this case we wont need SID tables.
    suppose i have one info cube which has dimension vendor material and customer  and its keyfigure is quantity and price and i have a separate infocube which has dimesnion material  customer and location and its key figure is something else ......so here in why cant i keep the dimensions out of the infocube and use the dimension material  customer for both infocube.

    Your dimension tables are filled based on your transaction data - which is why dimension table design is very important  you decide to group related data for the incoming transaction data into your dimension tables .
    The dimension tables have SIDs which in turn point to master data = in the classic star schema - the dimension tables are outside the cube but the dim tables have the master data within them whhich is overcome using the extended star schema.
    The reason why dimension tables can be reused is that the dim IDs and SIDs in the simension table correspond to the transaction data in the cube - and unless the dim IDs in both your cubes match you cannot reuse the dim tables - which means that you have exactly the same data in both the cubes - which means you need not have two cubes with the same data.
    Example :
    Cube 1 : Fact Table
    Dim1ID | DIM2ID | KF1
    1|01|100
    2|02|200
    Dimension Table : Dim 1 ( Assumin that there are 2 characteristics in this dimension ) - here the DIM1ID is Key
    Dim1ID | SID1 | SID2
    1|20|25
    2|30|35
    Dimension Table Dim 2 - Here the Dim2ID field is key
    Dim2ID| SID1 | SID2| SID3
    01| 30| 45
    02|45|40
    Here the Dim IDs for the cube Fact table are generated at the time of load and this is generated from the NRIV Table ( read material on Number Ranges ) - this meanns that you cannot control DIM ID generation across cubes which means that you cannot reuse Dimension Tables

  • Star schema versus snowflake schema

    I have a question regarding dimensional data modeling. My question here is, when star schema model would be useful and when snowflake schema model would be useful.
    In star schema, we have only fact and it is connected with dimensions. But in snowflake schema, we are normalizing dimension into one more level. Let us say, we have dimension product. Product can be normalized into another table called supplier. Let us take another example, customer dimension. Customer dimension can be normalized into country…
    Advantage of star schema is, easy to write the query since we have only less tables. You do not need to join multiple tables when we write the query. It would improve the performance some time.
    Advantage of snowflake schema is, it is little complex to write the query, since we have to join multiple tables. Performance might improve some time when we join smaller tables…
    My question is, at what circumstances, we can use star and snowflake schema? I am not able to define the word sometime_
    Any help is highly appreciated…

    Hi,
    There is a trade off on the availability and the Complex analytics.
    A star schema is good if you have the functional requirements really simple. Like the dimension is not SCD Type2 (slowly changing dimension) and you don't need to do "AS IS" vs "AS WAS" reporting.
    In modern Analytics in any domain dimensions are SCD Type 2 as business keep on evolving. In a star schema structure this will cause explosion of data if there are frequent changes at the higher levels of the dimensional hierarchy. That anyway will hit the performance.
    As far as my experience goes, at the data model level it is better to have snow flaked dimensions. and while managing the metadata (in a BI reporting tool) you can consolidate the snowflaked dimensions in star schema structures. That will make ah hoc analytics much simple for the business users.
    A lot of performance measure can be taken to improve the end user experience.
    In short the trend in BI analytics demands to have a snowflaked structure rather than a simple star schema structure.
    Hope this helps.

  • Error in database parameter for star schema table in RSRV

    Hi Experts,
    In RSRV, I executed the following checks in my cube and it is showing me the following error:-
    1)  Check database parameter for star schema table for InfoCube ZMM_MVAL
    564971 units missing from fact table /BIC/FZMM_MVAL; see details
    Message no. RSRV134
    Diagnosis
    In the fact table /BIC/FZMM_MVAL records have been found that contain values other than zero for key figures that have units, but that have no value for the unit of the key figure. Since the value of the unit has to correspond to the value of the key figure, this inidicates an error when the data was loaded. The values of the units have not been loaded into BW correctly. Choose Details to display the incorrect records.
    2)  Consistency of time dimension of InfoCube ZMM_MVAL
    /BIC/FZMM_MVAL PARTITIONED 1878 ( 30 - 50 )
    Please advise me on this.
    Thanks in Advance.
    Aparna

    As mentioned in the log, check the Unit KFs in your cube and make sure that unit is populated for all such values.
    e.g. if Qty is 5 KG, then unit KF will have 5 and unit info object should have KF.
    Regards,
    Gaurav

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