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SQL Server 2005 Course : SQL Server 2005 Analysis Services Course in FL Florida

SQL Server Analysis Services
Next Course Dates Call for schedule
Cost / Duration
Price: US $1,295, 3 days

Pre-requisites

This course does not require any prior experience with Analysis Server 2005. It is assumed that students have working experience with SQL Server 2000 or 2005; basic relational database concepts (e.g., tables, queries, and indexing); data transformation services; Excel 2003; and SharePoint Server 2003.

Who Should Attend?
Developers new to SQL Analysis Services, SQL DBAs, and IT management
Course Benefits

In this course, you will learn how to use Microsoft SQL Server 2005 Analysis Services (SSAS) to design and implement OnLine Analytical Processing (OLAP) cubes and data mining models to support Business Intelligence (BI) solutions. This course includes concepts, procedures and practices based on real-world experience giving both the novice and experienced SQL Server 2005 developer the tools to build data warehousing and decision support system solutions. This course also provides information on end-user tools including Microsoft Excel 2003/2007 and Microsoft SQL Server 2005 Reporting Services. Implementing SSAS solutions have shown to boost data retrieval and report generation from SQL Server by up to 1000%.

In this course you will
  • Learn the core concepts in building solutions using Microsoft Business Intelligence with SSAS.
  • Understand OLAP (cube) modeling and data mining.
  • See how to develop solutions using Business Intelligence Development Studio (BIDS).
  • Understand advanced storage design including MOLAP, ROLAP, and HOLAP.
  • Learn the fundamentals of MultiDimensional Expressions (MDX).
  • See best practices for SSAS administration using SQL Server Management Studio (SSMS) and XMLA (XML for Analysis).
  • Work with OLAP reporting clients including Microsoft Excel and SQL Server Reporting Services.
  • See integration with Microsoft Office 2007 and Microsoft SharePoint 2007

Course Content

What Is Microsoft BI?
Core concept – BI is the cube or UDM | Example cube as seen using Excel pivot table | MS BI is comprehensive – more than Analysis Services on SQL Server | Demonstration of SQL Reporting Services with cube as data source

OLAP Modeling
Modeling source schemas—stars and snowflakes | Understanding dimensional modeling— Dimensions (Type 1, 2, or 3) or rapidly changing | Understanding fact (measures) and cube modeling | Other types of modeling—data mining etc…

Using SSAS in BIDS
Understanding the development environment | Creating Data Sources and Data Source Views | Creating cubes – using the UDM and the Cube Build Wizard | Refining Dimensions and Measures in BIDS

Intermediate SSAS
KPIs | Perspectives | Translations – cube metadata and currency localization | Actions – regular, drill-through and reporting

Advanced SSAS
Using multiple fact tables | Modeling intermediate fact tables | Modeling M:M dimensions, Fact (degenerate) dimensions, Role-playing dimensions, writeback dimensions | Modeling changing dimensions – Dimension Intelligence w/ Wizard | Using the Add Business Intelligence Wizards – write-back, semi-additive measures, time intelligence, account intelligence

Cube Storage and Aggregation
Storage topics – basic aggregations, MOLAP | Advanced Storage Design – MOLAP, ROLAP, HOLAP | Partitions – relational and Analysis Services partitions | Customizing Aggregation Design - Processing Design | Rapidly changing dimensions / ROLAP dimensions | Welcome to the Real Time – Proactive Caching | Cube processing options

Beginning MDX
Basic syntax | Using the MDX query editor in SQL Server Management Studio | Most-used Functions & Common tasks | New MDX functions

Intermediate MDX
Adding calculated members | Adding scripts | Adding named sets | .NET Assemblies

SSAS Administration
Best practices – health monitoring | XMLA scripting (SQL Mgmt Studio) | Other Documentation methods | Security – roles and permissions | Disaster Recovery – backup / restore | Clustering – high availability

Introduction to Data Mining
What and why? | Examples of using each of the 9 algorithms (MS Clustering, MS Decision Trees, Naïve Bayes, MS Sequence Clustering, MS Time Series, MS Association Rules, MS Neural Network) | Data Mining dimensions | Data Mining clients | Processing mining models

Introduction to Reporting Clients
Excel 2003 Pivot Tables | SQL RS & Report Builder | SPS RS web parts & .NET 2.0 report viewer controls | Business Scorecards 2005 & ProClarity

Future Directions – Integration with Office 12
SharePoint 12 and AS | Report Center (type of dashboard) uses KPIs, Reports, Excel Web, Filter | Excel Services 12 and AS (Web Services)

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