Applied Microsoft Analysis Services 2005: And Microsoft by Teo Lachev

By Teo Lachev

Knowledge is energy! As its identify indicates, the promise of Microsoft SQL Server research companies 2005 is to advertise higher information analytics via giving info staff the suitable software to investigate constant, well timed, and trustworthy facts. Empowered with research prone and Microsoft company Intelligence Platform, you're good situated to resolve the perennial challenge with data—that there's an excessive amount of of it and discovering definitely the right details is usually tricky, if no longer impossible.

Applied Micrisoft research providers 2005 indicates database directors and builders the best way to construct whole OLAP suggestions with Microsoft research companies 2005 and Microsoft company Intelligence Platform. Database directors will the best way to layout and deal with refined OLAP cubes that supply wealthy info analytics and information mining services.

The publication supplies builders the required history to increase UDM with customized programming common sense, within the type of MDX expressions, scripts and .NET code. It teaches them how you can enforce a variety of reporting functions that combine with research providers, Reporting prone, and Microsoft Office.

This publication does not imagine any previous event with OLAP and Microsoft research prone. it really is designed as an easy-to-follow advisor the place every one bankruptcy builds upon the former to enforce the parts of the leading edge Unified Dimensional version (UDM) in a chronological order. New thoughts are brought with step by step directions and hands-on demos.

What's Inside:
o layout subtle UDM models
o construct ETL tactics with SSIS
o enforce facts mining tasks
o enhance UDM programmatically with MDX
o expand UDM with SSAS saved procedures
o Create wealthy end-user model
o Optimize research providers garage and processing
o enforce dynamic security
o construct customized OLAP clients
o writer usual and ad-hoc stories with SSRS
o construct Office-based BI purposes and dashboards
o and masses more

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Sample text

Data fidelity lost While dimensions reflect the natural way end-users prefer to analyze data, important dimension characteristics could be lost when transforming OLTP data to fit into the “classic” dimensional model. For example, the Product dimension we’ve discussed has a hierarchy that reflects the natural way end users would prefer to browse the product sales data – by category, subcategory and product name. However, the original Product relational schema may have included columns for product color, size, model, etc.

AMO supersedes the Decision Support Objects (DSO), the object model of SSAS 2000. DSO is still available for backward compatibly in the form of the DSO9 object library. However, as the documentation states, DSO will be removed in the next version of Microsoft SQL Server and you are strongly encouraged to migrate your management applications to AMO. 5 Analysis Services in Action Let’s demonstrate some of the concepts that we’ve discussed so far in a short hands-on lab. Before we start, let’s introduce an imaginary company, called Adventure Works Cycles.

AWC has a cutoff period of one month for the order to be considered finalized (Shipped or Cancelled). AWC has already built a data warehouse to archive the sales history. Data from relevant systems is extracted, transformed, and loaded in the data warehouse. Shipped sales orders that are older than a month are extracted from the AdventureWorks OLTP system and offloaded to the warehouse. The role of the data warehouse is fulfilled by the AdventureWorksDW sample database, which can be installed by running the SQL Server setup program.

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