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SQL Server Analysis Services 2012 Cube Development Cookbook

Baya Dewald, Paul Turley, Steve Hughes

If you prefer the instructional approach to a lot of theory, this cookbook is for you. It takes you straight into building data cubes through hands-on recipes, helping you get to grips with SQL Server Analysis Services fast.
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Book Details

ISBN 139781849689809
Paperback340 pages

About This Book

  • Develop Business Intelligence solutions using a multi-dimensional model as well as a tabular model
  • Explore cube maintenance with partitions and design effective aggregations, as well as analyzing options for scaling analytics solutions
  • Includes recipes for administering, securing, monitoring, and troubleshooting Analysis Services solutions

Who This Book Is For

If you are a BI or ETL developer using SQL Server Analysis services to build OLAP cubes, this book is ideal for you. Prior knowledge of relational databases and experience with Excel as well as SQL development is required.

Table of Contents

Chapter 1: Introduction to Multidimensional Data Model Design
The business value of Business Intelligence
Challenges and barriers of effective BI
Overcoming BI challenges and barriers
Choosing multidimensional or Tabular Models
Star- or Snowflake-relational schema
A sample scenario for choosing the Snowflake schema
Chapter 2: Defining Analysis Services Dimensions
Defining data sources
Defining data source views
Defining entity relationships in DSV
Extending data source views
Creating named calculations and queries
Creating simple dimensions
Building dimension hierarchies
Setting essential attribute properties
Browsing dimension data
Sorting the attributes
Customizing advanced attribute properties
Creating parent-child dimensions
Creating the date and time dimensions
Chapter 3: Creating Analysis Services Cubes
Defining measure groups and measures
Setting measure properties
Browsing the cube data
Dimension usage with measure group
Examining cube file structures
Partitioning strategies
Defining partition slice
Merging partitions
Defining aggregation designs
Distinct count measure groups
Enabling write-back feature
Deployment options
Chapter 4: Extending and Customizing Cubes
Defining calculated measures
Defining named sets
Defining drillthrough actions
Defining URL actions
Defining reporting actions
Defining key performance indicators
Defining perspectives
Defining translations
Defining measure expressions
Chapter 5: Optimizing Dimension and Cube Processing
Understanding dimension processing options
Learning about basic dimension processing
Learning advanced dimension processing options
Using out-of-line bindings for dimension processing
Dealing with partition processing options
Using SQL Server Integration Services to process Analysis Services objects
Monitoring and tuning processing performance
Chapter 6: MDX
Returning data on the query axes
Limiting the query output
Sorting the query output
Defining query level calculations and named sets
Navigating dimension hierarchies
Working with the Time dimensions
MDX script's functionality
Monitoring and tuning MDX queries
Chapter 7: Analysis Services Security
Managing instance-level administrative security
Managing database-level security
Managing cube-level security
Managing dimension hierarchy-level security
Implementing dynamic dimension security
Implementing cell-level security
Chapter 8: Administering and Monitoring Analysis Services
SSAS instance configuration options
Creating and dropping databases
Monitoring SSAS instance using Activity Viewer
Monitoring SSAS instance using DMVs
Cancelling a session
Checking whether cubes are accessible
Checking SSAS object sizes programmatically
Backup and restore
Synchronizing databases
Detaching and attaching databases
Chapter 9: Using Tabular Models
Creating a Tabular Model
Working with data sources and loading data
Modeling the data
Creating a hierarchy
Creating a calculated measure
Creating a calculated column
Creating a KPI
Analyzing your model in Excel
Deploying Tabular Models
Scripting Tabular Models using XMLA
Processing Tabular Models
Partitioning Tabular Models
Implementing perspectives
Implementing security in Tabular Models
Automating Tabular Model processing
Chapter 10: DAX Calculations and Queries
Combining tables using calculated columns
Adding a calculated column
Creating measures
Testing a Tabular Model in Excel
Using the CALCULATE function
Querying a Tabular Model
Chapter 11: Performance Tuning and Troubleshooting Tabular Models
Understanding usability limits
Optimizing and managing a model's design
Diagnosing performance issues
Using performance tools
Investigating query performance with SQL Server Profiler

What You Will Learn

  • Design commonly encountered dimensions
  • Extend your cubes to include advanced features such as actions, translations, and key performance indicators
  • Maintain cubes by adding/removing data using partitions
  • Administer Analysis Services instance
  • Scale out your solution by synchronizing cube data
  • Build tabular model solutions

In Detail

Microsoft SQL Server is a relational database management system. As a database, it is a software product whose primary function is to store and retrieve data as requested by other software applications. SQL Server Analysis Services adds OLAP and data mining capabilities for SQL Server databases. OLAP (online analytical processing) is a technique for analyzing business data for effective business intelligence.

This practical guide teaches you how to build business intelligence solutions using Microsoft’s core product – SQL Server Analysis Services. The book covers the traditional multi-dimensional model which has been around for over a decade as well as the tabular model introduced with SQL Server 2012.

Starting with comparing MultiDimensional and tabular models – discussing the values and limitations of each, you will then cover the essential techniques for building dimensions and cubes. Following on from this, you will be introduced to more advanced topics, such as designing partitions and aggregations, implementing security, and synchronizing databases for solutions serving many users.

The book also covers administrative material, such as database backups, server configuration options, and monitoring and tuning performance. We also provide a primer on MultiDimensional eXpressions (MDX) as well as Data Analysis expressions (DAX) languages.

This book provides you with data cube development techniques, and also the ongoing monitoring and tuning for Analysis Services.


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