Download Delivering Business Intelligence with Microsoft SQL Server by Brian Larson PDF

By Brian Larson

Maximize the company Intelligence instruments in Microsoft SQL Server 2008

Manage, learn, and distribute company facts with aid from this specialist source. Delivering company Intelligence with Microsoft SQL Server 2008 covers the total BI lifecycle and explains the right way to construct powerful info integration, reporting, and research options. Real-world examples illustrate all the strong BI features of SQL Server 2008. this can be your one-stop consultant for remodeling disparate information into actionable perception for clients all through your organization.

  • Understand the objectives and merits of industrial intelligence
  • Design and create relational information marts and OLAP cubes
  • Manage research providers databases utilizing BI improvement Studio
  • Cleanse info and populate info marts with SQL Server Integration Services
  • Take good thing about the flexibleness of the Unified Dimensional Model
  • Manipulate and learn info utilizing MDX scripts and queries
  • Use info mining to spot information styles, correlations, and clustering
  • Develop and distribute interactive stories with SQL Server 2008 Reporting Services
  • Integrate company intelligence into firm functions utilizing ADOMD.NET and the file Viewer Control

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Extra resources for Delivering Business Intelligence with Microsoft SQL Server 2008

Example text

Fact tables are named for the set of measures they contain, with the word “Fact” added to the end. The fact table for the example in the previous section is shown in Figure 3-1. The dimensions are stored in dimension tables. The dimension table has a column for the unique identifier of a member of the dimension, usually an integer or a short character value. The dimension table has another column for a description of the member. One dimension is stored in each dimension table, with one row for each member of the dimension.

Total Sales $33,708,421 2002 2003 2004 2005 2006 2007 Years We now have a line made up of measures of total sales at various points along that line, one point for each year in the dimension. In geometry, a line is a one-dimensional object. Thus, we have added a dimension to our measure: 2002, 2003, 2004, 2005, 2006, and 2007 are each said to be members of the year dimension. We can again spread out the total sales, this time for each product type. Total Sales Guiding Lights Product Type $12,394,238 Warriors of Yore Mythic World Woodland Creatures 2002 2003 2004 2005 2006 2007 Years The measures of total sales are now arranged in a square.

Highly sophisticated mathematical algorithms are applied to the data to find correlations between characteristics and events. Data mining can uncover such nuggets as the fact that a customer who purchased a certain product is more likely to buy a different product from your organization (we hope a product with a high profit margin). Or, a client receiving a particular service is also likely to need another service from your organization in the next three months. This type of information can be extremely helpful when planning marketing campaigns, setting up cross-product promotions, or doing capacity planning for the future.

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