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MS SQL SERVER: Olap cubes and data mining
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MS SQL SERVER: Olap cubes and data mining

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MS SQL SERVER: Olap cubes and data mining

MS SQL SERVER: Olap cubes and data mining

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MS SQL SERVER: Olap cubes and data mining MS SQL SERVER: Olap cubes and data mining Presentation Transcript

  • OLAP Cubes And Data Mining
  • overview
    Introduction to OLAP
    Processing the Cube
    Querying a Cube
    Browsing a Cube
    OLAP and Data Mining
    Using the Data Mining Designer
    The Data Mining Wizard
  • What is OLAP?
    OLAP is used for decision-support systems to analyze aggregated information for sales, finance, budget, and many other types of applications.
    Online Transaction Processing (OLTP) is mainly used to record transactions of daily operations, such as updating an account balance for a bank transaction.
    An OLAP cube is built for decision-support queries.
    A cube is a multidimensional database.
    A typical cube contains a set of well-defined dimensions, such as Customer, Product, Store, and Time.
  • Processing the Cube
    There are two steps to processing a cube:
    • Dimension processing reads dimension data from underlying dimension tables, builds the dimension structure, creates hierarchies, and assigns members to proper levels of the hierarchy.
    • Cube processing - main task is to precalculate aggregations based on the dimension hierarchies.
  • Querying a Cube
    You can query the Cube, after it has been processed, to retrieve the aggregated information.
    The OLE DB for OLAP specification has defined a query language for querying OLAP cubes.
    The language is called Multidimensional Expressions (MDX).
  • Browsing a Cube
    These tools for browsing a Cubeinclude three Microsoft Office family products
    • Excel
    • Office Web Components (OWC)
    • ProClarity
    • Third-party OLAP client tools (such as Panorama).
    Users can easily slice and dice the cube to generate reports with these tools.
  • Browsing the SalesCube
  • OLAP and Data Mining
    Both OLAP and data mining are key members of the BI technology family.
    Most of OLAP techniques come from the database family, data mining techniques come from three academic fields:
    • Statistics
    • Machine learning
    • Database technology.
    Most data mining algorithms use more or less statistical techniques, such as Naive Bayes and clustering.
  • Using the Data Mining Designer
    You can access the designer either by selecting an existing mining structure item or by using the Data Mining Wizard to create a new mining structure and mining model.
    You can use Data Mining Designer to perform the following tasks:
    • Modify the mining structure and the mining model that were initially created by the Data Mining Wizard.
    • Create new models based on an existing mining structure.
    • Train and browse mining models.
    • Compare models by using accuracy charts.
    • Create prediction queries based on mining models.
  • The Data Mining Wizard
    The Data Mining Wizard in Microsoft SQL Server Analysis Services starts every time that you add a new mining structure to a data mining project.
    The wizard helps you define new mining structures, and chooses the data sources that you will use for data mining.
    The wizard also can partition the data in the mining structure into training and testing sets, and help you add an initial mining model for each structure.
    You can choose which columns to include in the mining structure. All models that are based on that structure can use those columns.
    You can enable users of a data mining model to drill down from the results of the mining model to see additional mining structure columns that were not included in the mining model itself.
  • The Data Mining Wizard
    The content of a mining structure is derived from an existing data source view or cube.
  • Summary
    Introduction to OLAP
    Processing the Cube
    Querying a Cube
    Browsing a Cube
    OLAP and Data Mining
    Using the Data Mining Designer
    The Data Mining Wizard
  • Visit more self help tutorials
    Pick a tutorial of your choice and browse through it at your own pace.
    The tutorials section is free, self-guiding and will not involve any additional support.
    Visit us at www.dataminingtools.net