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Analysis Services en SQL Server 2008

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Presentacion sobre Analysis Services en SQL Server 2008 …

Presentacion sobre Analysis Services en SQL Server 2008


Ing. Eduardo Castro Martinez, PhD
Microsoft SQL Server MVP
http://ecastrom.blogspot.com
http://comunidadwindows.org

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  • 1. Analysis Services in SQL Server® 2008
    Eduardo Castro SQL MVP,MCDBA , MCSE, MCAD, MCSD
    ecastro@mswindowscr.org
    Comunidad Windows Costa Rica
  • 2. Data Warehouse System Components
    Data Warehouse
    User
    Data Access
    Data
    Sources
    Staging
    Area
    Data Marts
    Data Input
    Data Access
  • 3. Understanding Data Warehouse Design
    The Star Schema
    Fact Table Components
    Dimension Table Characteristics
    The Snowflake Schema
  • 4. The Star Schema
    Employee_Dim
    EmployeeKey
    EmployeeID
    ...
    Product_Dim
    Time_Dim
    ProductKey
    TimeKey
    ProductID
    ...
    TheDate
    ...
    Shipper_Dim
    Customer_Dim
    ShipperKey
    CustomerKey
    ShipperID
    ...
    CustomerID
    ...
    Dimension Table
    Fact Table
    Sales_Fact
    TimeKey
    EmployeeKey
    ProductKey
    CustomerKey
    ShipperKey
    Sales Amount
    Unit Sales ...
  • 5. Fact Table Components
    Measures
    time_dim
    134 1/1/2000
    DimensionTables
    sales_fact Table
    customer_dim
    Foreign Keys
    201 ALFI Alfreds
    customer_key
    product_key
    time_key
    quantity_sales
    amount_sales
    product_dim
    201
    25
    134
    400
    10,789
    25 123 Chai
    The grain of the sales_fact table is defined by the lowest level of detail stored in each dimension
  • 6. Dimension Table Characteristics
    Describes Business Entities
    Contains Attributes That Provide Context to Numeric Data
    Presents Data Organized into Hierarchies
  • 7. The Snowflake Schema
    Defines Hierarchies by Using Multiple Dimension Tables
    Is More Normalized than a Single Table Dimension
    Is Supported within Analysis Services
  • 8. Defining OLAP Solutions
    OLAP Databases
    Common OLAP Applications
    Relational Data Marts and OLAP Cubes
    OLAP in SQL Server 2005
  • 9. OLAP Databases
    Optimized Schema for Fast User Queries
    Robust Calculation Engine for Numeric Analysis
    Conceptual, Intuitive Data Model
    Multidimensional View of Data
    Drill down and drill up
    Pivot views of data
  • 10. OLAP in SQL Server
    Microsoft Is One of Several OLAP Vendors
    Analysis Services Is Bundled with Microsoft SQL Server 2005 and SQL Server 2008
    Analysis Services Include
    OLAP engine
    Data Mining technology
  • 11. Dimension Fundamentals
  • 12. Cube Measures
    Are the Numeric Values of Principle Interest
    Correspond to Fact Table Facts
    Intersect All Dimensions at All Levels
    Are Aggregated at All Levels of Detail
  • 13. Relational Data Sources
    Star and Snowflake Schemas
    Are required to build a cube with Analysis Services
    Fact Table
    Contains measures
    Contains keys that join to dimension tables
    Dimension Tables
    Must exist in same database as fact table
    Contain primary keys that identify each member
  • 14. Applying OLAP Cubes
    Defining a Cube
    Querying a Cube
    Defining a Cube Slice
    Working with Dimensions and Hierarchies
    Visualizing Cube Dimensions
    Connecting to an OLAP Cube
  • 15. Defining a Cube
    Atlanta
    Chicago
    Market Dimension
    Denver
    Grapes
    Cherries
    Detroit
    Melons
    Apples
    Products Dimension
    Q4
    Q1
    Q2
    Q3
    Time Dimension
  • 16. Fact Sales
    Atlanta
    Chicago
    MarketsDimension
    Denver
    Grapes
    Cherries
    Dallas
    Melons
    ProductsDimension
    Apples
    Q4
    Q1
    Q2
    Q3
    TimeDimension
    Querying a Cube
  • 17. SQL Server 2008 Analysis Services Enhancements
    Multidimensional Analysis with SQL Server Analysis Services
    Data Mining with SQL Server Analysis Services
  • 18. Multidimensional Analysis with SQL Server Analysis Services
    Cube Wizard
    Dimension Wizard
    The Attribute Relationship Designer
    The Aggregation Designer
    AMO Warnings
  • 19. Cube Wizard
    More efficient interface
    Create a cube based on a single de-normalized table
    Create a cube based on a data source that has only linked dimensions
  • 20. Dimension Wizard
    Create dimensions more efficiently
    Automatically detect parent-child hierarchies
    Provide safer default error configuration
    Set member properties while creating the dimension
  • 21. The Attribute Relationship Designer
    Flexible relationship
    Rigid relationship
    Manage Relationship through right-click options in the Attribute Relationship pane
  • 22. The Aggregation Designer
    New Aggregation Designer:
    Aggregations designs are shown grouped by measure group
    New view available for manual aggregation design
    Improved Usage-Based Optimization Wizard:
    Ability to append new aggregations to an existing aggregation design
    Ability to modify storage settings for one or more partitions simultaneously
    Improved Aggregation Design Wizard
  • 23. AMO Warnings
    Uses familiar symbols such as the wavy underline and a yellow triangle with an exclamation point
    Non-intrusive warning messages appear when you pause the mouse over a warning
    Available for logical errors in database design, when users depart from design best practices, and for non-optimal aggregation designs
  • 24. Data Mining with SQL Server Analysis Services
    Improved Data Mining Wizard
    Separating Test and Training Data
    Filtering Model Cases
    Cross Validation of Mining Models
    Data Mining Add-Ins for Microsoft Office Systems
  • 25. Data Mining Enhancements
    Improve both short-term and long-term predictions with the Microsoft Time Series algorithm, which has been enhanced to support both ARTXP and ARIMA algorithms
    Enable drillthrough on a mining structure to allow queries about the cases used for both training and testing
    Create column aliases to make it easier to understand column content. In the Data Mining Designer, the alias appears in parentheses next to the column usage label
    Separate test and training data
    Improve performance and analyze different scenarios by using Model Case Filtering
    Create cross-validation reports
    Utilize Data Mining Add-ins for Office
  • 26. Separating Test and Training Data
    Three ways to partition data into training and test sets:
    The Data Mining Wizard
    Modifying the properties of the mining structure:
    If you did not create a test partition when you created the structure, you can modify the HouldoutMaxCases, HoldoutMaxPercent, and HoldoutSeed properties
    DMX statement, AMO, or XML DDL
  • 27. Filtering Model Cases
    • Limit the cases used in a model based on any attribute included in the model
    • 28. Use to compare subsets of your data such as different regions
  • Cross-Validation of Mining Models
    Additional method to test and view mining model accuracy
    Data is partitioned into cross-sections which are used to train and test models against each of the other cross sections
    One portion of the data is used to test, the remaining data is used to train the model
    To define a cross-validation report, you must configure:
    The Fold Count, which specifies the number of folds or partitions that the data is broken into for testing
    The Max Cases, which specifies the maximum number of cases to use (a value of 0 specifies that all cases will be used)
    The Target Attribute, which defines the column or attribute that you want to predict
    The Target State, which defines a particular value that you want to analyze within the target attribute
  • 29. Data Mining Add-Ins for Microsoft Office System
    Data Mining Client for Excel – create, test, and manage data mining projects within Excel 2007
    Table Analysis Tools for Excel – use powerful analysis tools such as analyzing key influencers, highlighting exceptions, and forecasting for data stored in spreadsheets
    Data Mining Templates for Visio – render decision trees, regression trees, cluster diagrams, and dependency nets in diagrams created in Visio 2007
    Important: Data Mining Add-ins for Microsoft Office System will be available for SQL Server 2008 when it releases to manufacturing.
  • 30. Demonstration
    Implementing Multidimensional Analysis
  • 31. Optimizing Storage
    What Are Sparse Columns?
    How to Compress Data and Backups
  • 32. What Are Sparse Columns?
    Eliminate limitation of 1024 columns.
    Efficient way to manage object models that frequently contain numerous NULL values.
    CREATE TABLE products (product_numint, item_numint, price decimal(7,2), ...,                       color char(5) SPARSE, width float SPARSE...)
  • 33. How to Compress Data and Backups
    Data compression can be enabled on tables or views
    Different compression types can be configured on a per-partition basis
    The following data compression types can be defined:
    Row compression
    Page compression
    Backup compression:
    Normally decreases time required to perform a backup
    Managed with Transact-SQL, Backup Task, Maintenance Plan Wizard, and Integration Services Backup Database task
  • 34. Contact Information
    Eduardo Castro
    ecastro@mswindowscr.org
    http://ecastrom.blogspot.com