BW Data Mining

Hello!
I need information about the following BW Data Mining topics. Hope, someone can help me?
-What 3rd Party Tools are available für Data Mining? (I just know "IBM Intelligent Miner")
-Does someone have experiences with performance of the DM-algorithms? System requirements? Mass data?
-Are there possibilities to improve the performance?
-What is known about new features in Netweaver BI 7.0 for DM?
-Does someone have special experiences in DM in the automotive industy? Are there typical business processes known, which are useful for BW Data Mining?
Thank you for help!
Regards,
Peter

Hallo!
I need different information about BW data mining.
One thing is, what are typical business scenarios for the different algorithms. So it is easy to find such for decision trees, association analysis and maybe for ABC analysis. But i have little problems to find real scenarios vor weighted score tables and regression analysis. It would be helpful to hear about some.
I have to write a paper for my company about data mining with bw. While we have no experiences in this area I´m looking here for people having.
Also Performance. The problem is not to try out with APD and Data Mining models. But to find experiences with this.
Good or bad performance with this or this algo? Or how can I optimize performance for mass data?
After this I have to design typical business scenarios. Especially for automotive area if possible.
So what the question for me is, what is possible with the algorithms? Where are problems with them?
It would be great if you could provide me with more information about your experiences in this area.
Thanks,
Peter

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    (PURCHASE_WEEK, WEEK, SALES)
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    There are a lot of linear regression models and approaches for sales forecast out on the market, however I will focus on what oracle 11g offers i.e. package SYS.DBMS_DATA_MINING to create a model using regression as mining function and then, once the model is created, to apply prediction function on the model.
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    SELECT a.*
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    sales,
    LAG(sales_norm, 1) OVER (ORDER BY week) L1,
    LAG(sales_norm, 2) OVER (ORDER BY week) L2,
    LAG(sales_norm, 3) OVER (ORDER BY week) L3,
    LAG(sales_norm, 4) OVER (ORDER BY week) L4,
    LAG(sales_norm, 5) OVER (ORDER BY week) L5,
    LAG(sales_norm, 6) OVER (ORDER BY week) L6,
    LAG(sales_norm, 7) OVER (ORDER BY week) L7,
    LAG(sales_norm, 8) OVER (ORDER BY week) L8,
    LAG(sales_norm, 9) OVER (ORDER BY week) L9,
    LAG(sales_norm, 10) OVER (ORDER BY week) L10,
    LAG(sales_norm, 11) OVER (ORDER BY week) L11,
    LAG(sales_norm, 12) OVER (ORDER BY week) L12,
    LAG(sales_norm, 13) OVER (ORDER BY week) L13,
    LAG(sales_norm, 14) OVER (ORDER BY week) L14,
    LAG(sales_norm, 15) OVER (ORDER BY week) L15,
    LAG(sales_norm, 16) OVER (ORDER BY week) L16,
    LAG(sales_norm, 17) OVER (ORDER BY week) L17
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    L1, L2, L3, L4, L5, L6, L7, L8, L9, L10,
    L11, L12, L13, L14, L15, L16, L17
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    v) finally, where I am confused is applying the prediction function against this model and making sense of the results.
    On a search on Google I found 2 ways of applying this function to my case.
    One way is the following:
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    LAG(sales,1) OVER (ORDER BY week) as l1,
    LAG(sales,2) OVER (ORDER BY week) as l2,
    LAG(sales,3) OVER (ORDER BY week) as l3,
    LAG(sales,4) OVER (ORDER BY week) as l4,
    LAG(sales,5) OVER (ORDER BY week) as l5,
    LAG(sales,6) OVER (ORDER BY week) as l6,
    LAG(sales,7) OVER (ORDER BY week) as l7,
    LAG(sales,8) OVER (ORDER BY week) as l8,
    LAG(sales,9) OVER (ORDER BY week) as l9,
    LAG(sales,10) OVER (ORDER BY week) as l10,
    LAG(sales,11) OVER (ORDER BY week) as l11,
    LAG(sales,12) OVER (ORDER BY week) as l12,
    LAG(sales,13) OVER (ORDER BY week) as l13,
    LAG(sales,14) OVER (ORDER BY week) as l14,
    LAG(sales,15) OVER (ORDER BY week) as l15,
    LAG(sales,16) OVER (ORDER BY week) as l16,
    LAG(sales,17) OVER (ORDER BY week) as l17
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    FROM t_sales a;
    WEEK, SALES, PREDICTION
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    2, 78336, 104816.995823913
    3, 77248, 104816.995823913
    4, 106624, 104816.995823913
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    Question: where is my week 18 prediction ? or maybe I should say which one is it ?
    Another way of using prediction even more confusing is against the lag table:
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    2, 78336, 75512.3642096908
    3, 77248, 85711.5003385927
    4, 106624, 98160.5009687461
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    Thank you very much for all help that you can provide on this matter.
    It is as always highly appreciated.
    Serge F.

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  • Data Mining in 9i

    Hi All,
    We have Oracle 9i Rel2, with OLAP and data miming option. The documents available in the net doesnt cover basic information on the installation/configuration/usage stuff. Can any one point me to a location (not oracle documents), where there is a step by step infor on hopw to get started with oracle data mining.
    Any help will be really appreciated.

    You need to copy the following jar files to your local machine
         $ORACLE_HOME/jdbc/lib/classes12.jar
    $ORACLE_HOME/lib/xmlparserv2.jar
    $ORACLE_HOME/rdbms/jlib/jmscommon.jar
    $ORACLE_HOME/rdbms/jlib/aqapi.jar
    $ORACLE_HOME/rdbms/jlib/xsu12.jar
    $ORACLE_HOME/dm/lib/odmapi.jar
    I have downloaded all the required documents from metalink. In case you still need those, please mail me at [email protected]

  • How to get the Oracle Data Mining

    Hi
    I downloaded Oracle Database 10g r2 on Oracle's download website, and I want the ODM, but it is said in the white paper that ODM is a priced option. I'd like to know how to get it.

    Data Mining is a priced option shipped with Oracle Enterprise Edition. You can get Data Mining option by installing Oracle 10gR2 and select 'general purpose' with the pre-configured database. Data Mining option is installed as default in that choice.
    If for production purposes, customers do need to purchase Data Mining option lisence through Oracle sales.
    Xiafang

  • Collation error when data mining

    I'm trying to process a data mining model but keep getting this error: "Errors in the OLAP storage
    engine: The sort order specified for distinct count records is incorrect. Errors in the OLAP storage engine: An error occurred while processing the..."
    I changed my sql server collation to to Latin1_General_CS_AI with a compatibility level of 100, and in SSAS, I set it to Latin1_General_100 and "Case Sensitive" checked...but I still get the same error...am I not setting the collation correctly?

    I changed my sql server collation to to Latin1_General_CS_AI ...
    The SQL Server setting is just a default value for new databases, when you don't explicit define the collation in the CREATE DATABASE command; same for the database setting, also just a default value. The effective collation is defined on column level.
    Olaf Helper
    [ Blog] [ Xing] [ MVP]

  • Processing a data mining structure throws an error

    Processing a data mining structure throws an exception stating the following:
    "Errors in the OLAP storage engine: An error occurred while the 'IDK' attribute of the 'Test  IDK' dimension from the 'Project1' database was being processed."
    "Errors in the OLAP storage engine: The attribute key was converted to an unknown member because the attribute key was not found. Attribute IDK of Dimension: Test IDK from Database: project1, Record:17072643"
    I am using a DB view as a DSV. It does not have a unique primary key. Since DB view is getting multiple results per IDK, the IDK repeats for multiple rows. The same IDK is defined as Key column for the mining model. Not sure if that is the
    issue. Please help!
    Thanks
    Shallu

    Hi Shallu,
    According to your description, you use a database view in the data source view that do not have a primary key, so you get the error
    Errors in the OLAP storage engine: The attribute key was converted to an unknown member because the attribute key was not found. Attribute IDK of Dimension: Test IDK from Database: project1, Record:1707264
    when processing the project, right?
    In this case, please refer to the links below which describe the similar issue.
    http://agilebi.com/ddarden/2009/01/06/analysis-services-error-the-attribute-key-cannot-be-found-when-processing-a-dimension/
    http://social.technet.microsoft.com/Forums/systemcenter/en-US/432deebe-52b8-4245-af85-5aa2eecd421a/scsm2012-cube-processing-failing-on-two-cubes-configitemdimkey-not-found?forum=dwreportingdashboards
    Regards,
    Charlie Liao
    TechNet Community Support

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