More than 100 recipes to develop Business Intelligence solutions using Analysis Services Overview 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 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. What you will learn from this book 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 Approach A practical cookbook packed with recipes to help developers produce data cubes as quickly as possible by following step by step instructions, rather than explaining data mining concepts with SSAS. Who this book is written 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.