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Microsoft SQL Server is an enterprise database platform that contains a multitude of technologies, Analysis Services being one of them. SQL Server Analysis Services (SSAS) provides OLAP and data mining capabilities and allows users to analyze multidimensional data stored in cubes using the MDX query language. This cookbook contains over 80 practical, task-based recipes that show how Microsoft SQL Server 2008 R2 Analysis Services solutions can be taken further by enriching them with high-performance MDX calculations and flexible MDX queries. Packed with immediately usable, real-world recipes, the book starts with elementary techniques that lay the foundation for designing further MDX calculations and queries. Here you will find topics such as iterations on a set, Boolean logic, and dissecting and optimizing MDX calculations. In the first half of the book you will learn how to efficiently work with time, strings, metadata, calculated members and sets in general, and how to implement MDX solutions that are appropriate in a particular context: a time-aware calculation, a concise report, a calculation relative to another. You will also learn how to implement various types of conditional formatting, how to perform typical MDX calculations like ranks, percentages and averages, and year-to-date calculations. The book then deep dives into topics such as enhancing cube design with utility dimensions, context-aware calculations, and other advanced topics. In this part you will learn how a utility dimension can be of great help, for example when you want to calculate histograms or implement time-based calculations. The advanced topics also cover parent-child hierchies, recursion, random values, and complex sorts. Enrich your Business Intelligence solutions with over 80 recipes for high-performance MDX calculations and flexible MDX queries What you will learn from this book : Create time-aware calculations (relative to the current date) Create context-aware calculations (relative to members on axes) Implement business-related calculations like forecasting, allocation of values and ABC analysis Calculate various percentages, averages, and ranks Work with related members (on the same and other dimensions) Combine MDX with utility dimensions Implement error handling Implement AND, OR, NOT logic Conditionally format your MDX calculations Optimize, dissect, and debug MDX calculations and queries Capture MDX generated by SSAS front-ends Register SSAS-related assemblies and use stored procedures in them Approach This book offers practical, task-based, and immediately usable recipes covering a wide range of MDX calculations and queries. In addition to its cookbook style, which ensures the solutions are presented in a clear step-by-step manner, the explanations are done in great detail, which makes it good learning material for everyone who has experience in MDX and wants to improve. The book is designed in such a way that you can read it chapter by chapter or refer to recipes in no particular order. However, some of the recipes depend on each another. When this is the case, you will be notified. The book is focused on Microsoft SQL Server 2008 R2 Analysis Services, but most of the concepts and explanation are also applicable to previous versions of Microsoft SQL Server Analysis Services. Who this book is written for If you are a Microsoft SQL Server Analysis Services developer and want to improve your solutions using MDX, then this book is for you. The book assumes you have a working knowledge of MDX and a basic understanding of dimensional modeling and cube design. About the Author Tomislav Piasevoli is a Business Intelligence Specialist with years of experience with SQL Server Analysis Services. He lives in Croatia and works for SoftPro Tetral d.o.o. (http://www.softpro.hr), a company with a long tradition in building advanced SSAS frontends and implementing BI solutions on the Microsoft platform. During his career in the company, Tomislav has successfully implemented more than 20 still-in-use BI solutions and now specializes in dimensional modeling, cube design and MDX. Tomislav has been honored with Microsoft's MVP award twice, mostly for his contribution to the SSAS community on the MSDN forum. Besides solving MDX puzzles, he presents at conferences, writes articles for magazines, and maintains his blog at http://tomislav.piasevoli.com. Table of Contents Preface Chapter 1: Elementary MDX Techniques Introduction Skipping axis Handling division by zero errors Setting special format for negative, zero and null values Applying conditional formatting on calculations Setting default member of a hierarchy in MDX script Implementing NOT IN set logic Implementing logical OR on members from different hierarchies Iterating on a set in order to reduce it Iterating on a set in order to create a new one Iterating on a set using recursion Dissecting and debugging MDX queries Using NON_EMPTY_BEHAVIOR Optimizing MDX queries using the NonEmpty() function Implementing logical AND on members from the same hierarchy Chapter 2: Working with Time Introduction Calculating the YTD (Year-To-Date) value Calculating the YoY (Year-over-Year) growth (parallel periods) Calculating moving averages Finding the last date with data Getting values on the last date with data Hiding calculation values on future dates Calculating today's date using the string functions Calculating today's date using the MemberValue function Calculating today's date using an attribute hierarchy Calculating the difference between two dates Calculating the difference between two times Calculating parallel periods for multiple dates in a set Calculating parallel periods for multiple dates in a slicer Chapter 3: Concise Reporting Introduction Isolating the best N members in a set Isolating the worst N members in a set Identifying the best/worst members for each member of another hierarchy Displaying few important members, others as a single row, and the total at the end Combining two hierarchies into one Finding the name of a child with the best/worst value Highlighting siblings with the best/worst values Implementing bubble-up exceptions Chapter 4: Navigation Introduction Detecting a particular member in a hierarchy Detecting the root member Detecting members on the same branch Finding related members in the same dimension Finding related members in another dimension Calculating various percentages Calculating various averages Calculating various ranks Chapter 5: Business Analytics Introduction Forecasting using the linear regression Forecasting using the periodic cycles Allocating the non-allocated company expenses to departments Calculating the number of days from the last sales to identify the slow-moving goods Analyzing fluctuation of customers Implementing the ABC analysis Chapter 6: When MDX is Not Enough Introduction Using a new attribute to separate members on a level Using a distinct count measure to implement histograms over existing hierarchies Using a dummy dimension to implement histograms over non-existing hierarchies Creating a physical measure as a placeholder for MDX assignments Using a new dimension to calculate the most frequent price Using a utility dimension to implement flexible display units Using a utility dimension to implement time-based calculations Chapter 7: Context-aware Calculations Introduction Identifying the number of columns and rows a query will return Identifying the axis with measures Identifying the axis without measures Adjusting the number of columns and rows for OWC and Excel Identifying the content of axes Calculating row numbers Calculating the bit-string for hierarchies on an axis Preserving empty rows Implementing utility dimension with context-aware calculations Chapter 8: Advanced MDX Topics Introduction Displaying members without children (leaves) Displaying members with data in parent-child hierarchies Implementing the Tally table utility dimension Displaying random values Displaying a random sample of hierarchy members Displaying a sample from a random hierarchy Performing complex sorts Using recursion to calculate cumulative values Chapter 9: On the Edge Introduction Clearing the Analysis Services cache Using Analysis Services stored procedures Executing MDX queries in T-SQL environments Using SSAS Dynamic Management Views (DMV) to fast-document a cube Using SSAS Dynamic Management Views (DMVs) to monitor activity and usage Capturing MDX queries generated by SSAS front-ends Performing custom drillthrough Conclusion Appendix: Glossary of Terms Parts of an MDX query MDX query in action Cube and dimension design MDX script Query optimization Types of query Index