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Home > Data > Database Administration > MDX with Microsoft SQL Server 2016 Analysis Services Cookbook
MDX with Microsoft SQL Server 2016 Analysis Services Cookbook
MDX with Microsoft SQL Server 2016 Analysis Services Cookbook

MDX with Microsoft SQL Server 2016 Analysis Services Cookbook: Over 70 practical recipes to analyze multi-dimensional data in SQL Server 2016 Analysis Services cubes , Third Edition

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MDX with Microsoft SQL Server 2016 Analysis Services Cookbook

Chapter 2. Working with Sets

In this chapter, we will cover the following recipes:

  • Implementing the NOT IN set logic
  • Implementing the logical OR on members from different hierarchies
  • Iterating on a set to reduce it
  • Iterating on a set to create a new one
  • Iterating on a set using recursion
  • Performing complex sorts
  • Dissecting and debugging MDX queries
  • Implementing the logical AND on members from the same hierarchy

Introduction

Sets in MDX are collections of tuples with the same dimensionality. As in many other programming languages, the basic logical operations, NOT, AND, and OR, can be applied on them.

When putting two tuples together to form a set, we basically ask for the results that contain any of those tuples. Therefore, sets in MDX naturally imply the OR logic. The first part of the chapter focuses on the challenges and solutions of performing NOT and OR logic operations on sets.

Iterations and recursions can also be performed on sets. The middle part of the chapter concentrates on those actions and the different ways to perform them.

The final part of the chapter explains how to perform complex sorts, how to apply the iteration technique to dissect and debug MDX queries and calculations, and how to perform the logical AND operation in MDX.

Implementing the NOT IN set logic

There are times when we want to exclude some members from the result. We can perform this operation using a set of members on an axis or using a set of members in a slicer, that is, the WHERE part of an MDX query.

This recipe shows how to do the latter, that is, how to exclude some members from a set in a slicer. The principle is the same for any part of an MDX query.

Getting ready

Start a new query in SQL Server Management Studio (SSMS) and check that you are working on the Adventure Works DW 2016 database. Then type in the following query and execute it:

SELECT 
   { [Measures].[Reseller Order Count] } ON 0, 
   NON EMPTY 
   { [Promotion].[Promotion].MEMBERS } 
   DIMENSION PROPERTIES 
     [Promotion].[Promotion].[Discount Percent]  
   ON 1 
FROM 
   [Adventure Works]

The preceding query returns 12 promotions and all the top-level promotions on the rows axis. The DIMENSION PROPERTIES keyword is used to get additional information about members each promotion...

Implementing the logical OR on members from different hierarchies

If we need to slice the data by only the black color for products, we would put the Black member in the WHERE clause, like this:

WHERE 
   ( [Product].[Color].&[Black] )

In the Adventure Works DW 2016 database, by putting Reseller Order Quantity and Reseller Order Count on the columns, we would get this result:

Implementing the logical OR on members from different hierarchies

Similarly, to get only the products whose size is XL, we can put the member XL in the slicer as:

WHERE 
   ( [Product].[Size Range].&[XL] )

What if we want to get the products whose size is XL in the same result set as the result set for black only?

Somehow, we need to combine the black member with the XL member. Simply by putting these two members together, it would not work. Putting two members from different hierarchies would form a tuple; a tuple implies the logical AND in MDX, not the logical OR.

On the other hand, MDX implies a logical OR. However, we cannot simply put the preceding two members together...

Iterating on a set to reduce it

Iteration is a very natural way of thinking for us humans. We set a starting point, we step into a loop, and we end when a condition is met. While we're looping, we can do whatever we want: check, take, leave, and modify items in that set.

In this recipe, we will start from a result set as shown in the following table, and iterate through the days in each fiscal month to count the number of days for which the growth was positive. By to reduce, we mean the filtering effect; in our example, we need to filter out the days for which the growth was not positive. Our goal is still to only display the fiscal months on ROWS, not the days:

Iterating on a set to reduce it

Then we will look at a different approach that takes performance advantage of the block- mode calculation.

Getting ready

Start a new query in SSMS against the Adventure Works DW 2016 database. Then write the following query:

SELECT 
   { [Measures].[Customer Count], 
     [Measures].[Growth in Customer Base] } ON 0, 
   NON EMPTY...

Iterating on a set to create a new one

There are situations when we don't want to eliminate certain members from a set, but instead execute for each type of loop. This is done using the Generate() function. The Generate() function applies a set to each member of another set, and then joins the resulting sets by union. In this recipe, we'll show you how to create a new set of members from the existing one.

Getting ready

Let's start a new query in SSMS against the Adventure Works DW 2016 database. Then write the following query:

SELECT 
   NON EMPTY 
   { [Date].[Calendar].[Calendar Year].MEMBERS * 
     [Measures].[Sales Amount] } ON 0, 
   NON EMPTY 
   { [Sales Territory].[Sales Territory Country].MEMBERS } 
   ON 1 
FROM 
   [Adventure Works]

The query returns four years on the columns and six countries plus the top level, All Sales Territories, on the rows. The result is shown as follows:

Getting ready

Our goal is to get a set of best months, one for each year. We will use the Generate...

Introduction

Sets in MDX are collections of tuples with the same dimensionality. As in many other programming languages, the basic logical operations, NOT, AND, and OR, can be applied on them.

When putting two tuples together to form a set, we basically ask for the results that contain any of those tuples. Therefore, sets in MDX naturally imply the OR logic. The first part of the chapter focuses on the challenges and solutions of performing NOT and OR logic operations on sets.

Iterations and recursions can also be performed on sets. The middle part of the chapter concentrates on those actions and the different ways to perform them.

The final part of the chapter explains how to perform complex sorts, how to apply the iteration technique to dissect and debug MDX queries and calculations, and how to perform the logical AND operation in MDX.

Implementing the NOT IN set logic

There are times when we want to exclude some members from the result. We can perform this operation using a set of members on an axis or using a set of members in a slicer, that is, the WHERE part of an MDX query.

This recipe shows how to do the latter, that is, how to exclude some members from a set in a slicer. The principle is the same for any part of an MDX query.

Getting ready

Start a new query in SQL Server Management Studio (SSMS) and check that you are working on the Adventure Works DW 2016 database. Then type in the following query and execute it:

SELECT 
   { [Measures].[Reseller Order Count] } ON 0, 
   NON EMPTY 
   { [Promotion].[Promotion].MEMBERS } 
   DIMENSION PROPERTIES 
     [Promotion].[Promotion].[Discount Percent]  
   ON 1 
FROM 
   [Adventure Works]

The preceding query returns 12 promotions and all the top-level promotions on the rows axis. The DIMENSION PROPERTIES keyword is used to get additional...

Implementing the logical OR on members from different hierarchies

If we need to slice the data by only the black color for products, we would put the Black member in the WHERE clause, like this:

WHERE 
   ( [Product].[Color].&[Black] )

In the Adventure Works DW 2016 database, by putting Reseller Order Quantity and Reseller Order Count on the columns, we would get this result:

Similarly, to get only the products whose size is XL, we can put the member XL in the slicer as:

WHERE 
   ( [Product].[Size Range].&[XL] )

What if we want to get the products whose size is XL in the same result set as the result set for black only?

Somehow, we need to combine the black member with the XL member. Simply by putting these two members together, it would not work. Putting two members from different hierarchies would form a tuple; a tuple implies the logical AND in MDX, not the logical OR.

On the other hand, MDX implies a logical OR. However, we cannot simply put the preceding...

Iterating on a set to reduce it

Iteration is a very natural way of thinking for us humans. We set a starting point, we step into a loop, and we end when a condition is met. While we're looping, we can do whatever we want: check, take, leave, and modify items in that set.

In this recipe, we will start from a result set as shown in the following table, and iterate through the days in each fiscal month to count the number of days for which the growth was positive. By to reduce, we mean the filtering effect; in our example, we need to filter out the days for which the growth was not positive. Our goal is still to only display the fiscal months on ROWS, not the days:

Then we will look at a different approach that takes performance advantage of the block- mode calculation.

Getting ready

Start a new query in SSMS against the Adventure Works DW 2016 database. Then write the following query:

SELECT 
   { [Measures].[Customer Count], 
     [Measures].[Growth in Customer Base] } ON 0, 
...
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Key benefits

  • Updated for SQL Server 2016, this book helps you take advantage of the new MDX commands and the new features introduced in SSAS
  • Perform time-related, context-aware, and business related-calculations with ease to enrich your Business Intelligence solutions
  • Collection of techniques to write flexible and high performing MDX queries in SSAS with carefully structured examples

Description

If you're often faced with MDX challenges, this is a book for you. It will teach you how to solve various real-world business requirements using MDX queries and calculations. Examples in the book introduce an idea or a problem and then guide you through the process of implementing the solution in a step-by-step manner, inform you about the best practices and offer a deep knowledge in terms of how the solution works. Recipes are organized by chapters, each covering a single topic. They start slowly and logically progress to more advanced techniques. In case of complexity, things are broken down. Instead of one, there are series of recipes built one on top of another. This way you are able to see intermediate results and debug potential errors faster. Finally, the cookbook format is here to help you quickly identify the topic of interest and in it a wide range of practical solutions, that is – MDX recipes for your success.

Who is this book for?

This book is for anyone who has been involved in working with multidimensional data. If you are a multidimensional cube developer, a multidimensional database administrator, or a report developer who writes MDX queries to access multidimensional cube, this book will help you. If you are a power cube user or an experienced business analyst, you will also find this book invaluable in your data analysis. This book is for you are interested in doing more data analysis so that the management can make timely and accurate business decisions.

What you will learn

  • Grasp the fundamental MDX concepts, features, and techniques
  • Work with sets
  • Work with Time dimension and create time-aware calculations
  • Make analytical reports compact, concise, and efficient
  • Navigate cubes
  • Master MDX for reporting with Reporting Services (new)
  • Perform business analytics
  • Design efficient cubes and efficient MDX queries
  • Create metadata-driven calculations (new)
  • Capture MDX queries and many other techniques

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Nov 30, 2016
Length: 586 pages
Edition : 3rd
Language : English
ISBN-13 : 9781786467881
Vendor :
Microsoft
Category :
Data
Concepts :
Database Administration
Tools :
SQL Server

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Product Details

Publication date : Nov 30, 2016
Length: 586 pages
Edition : 3rd
Language : English
ISBN-13 : 9781786467881
Vendor :
Microsoft
Category :
Data
Concepts :
Database Administration
Tools :
SQL Server

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Table of Contents

10 Chapters
1. Elementary MDX Techniques Chevron down icon Chevron up icon
1. Elementary MDX Techniques
Introduction
Putting data on x and y axes
Skipping axes
Using a WHERE clause to filter the data returned
Optimizing MDX queries using the NonEmpty() function
Using the Properties() function to retrieve data from attribute relationships
Basic sorting and ranking
Handling division by zero errors
Setting a default member of a hierarchy in the MDX script
2. Working with Sets Chevron down icon Chevron up icon
2. Working with Sets
Introduction
Implementing the NOT IN set logic
Implementing the logical OR on members from different hierarchies
Iterating on a set to reduce it
Iterating on a set to create a new one
Iterating on a set using recursion
Performing complex sorts
Dissecting and debugging MDX queries
Implementing the logical AND on members from the same hierarchy
3. Working with Time Chevron down icon Chevron up icon
3. Working with Time
Introduction
Calculating the year-to-date (YTD) value
Calculating the year-over-year (YoY) growth (parallel periods)
Calculating moving averages
Finding the last date with data
Getting values on the last date with data
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
4. Concise Reporting Chevron down icon Chevron up icon
4. 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 a few important members, with the 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
5. Navigation Chevron down icon Chevron up icon
5. 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
6. MDX for Reporting Chevron down icon Chevron up icon
6. MDX for Reporting
Introduction
Creating a picklist
Using a date calendar
Passing parameters to an MDX query
Getting the summary
Removing empty rows
Getting data on the column
Sorting data by dimensions
7. Business Analyses Chevron down icon Chevron up icon
7. Business Analyses
Introduction
Forecasting using linear regression
Forecasting using periodic cycles
Allocating non-allocated company expenses to departments
Analyzing the fluctuation of customers
Implementing the ABC analysis
8. When MDX is Not Enough Chevron down icon Chevron up icon
8. 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 nonexisting 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
9. Metadata - Driven Calculations Chevron down icon Chevron up icon
9. Metadata - Driven Calculations
Introduction
Setting up the environment
Creating a reporting dimension
Implementing custom rollups using MDX formulas
Implementing format string, multiplication factor, and sort order features
Implementing unary operators
Referencing reporting dimension's members in MDX formulas
Implementing the MDX dictionary
Implementing metadata-driven KPIs
10. On the Edge Chevron down icon Chevron up icon
10. 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 (DMVs) to fast-document a cube
Using SSAS Dynamic Management Views (DMVs) to monitor activity and usage
Capturing MDX queries generated by SSAS frontends
Performing a custom drillthrough

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Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Full star icon 5
(3 Ratings)
5 star 100%
4 star 0%
3 star 0%
2 star 0%
1 star 0%
Amazon Customer Aug 29, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Excellent for beginners
Amazon Verified review Amazon
I.W COETZER Jan 08, 2019
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I have found this book very useful. After struggling for two months with a complex MDX calculation I managed to solve after owning this book for only three days. Well written and good samples.
Amazon Verified review Amazon
Dave Wentzel Dec 07, 2016
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I was the technical reviewer for this book. I've worked with SSAS for years, but frankly often fumbled around with solutions due to the dearth of really good documentation and blog posts. I've learned MDX, like most, through trial and error...the "error" often only being discovered when my solution wouldn't scale anymore and I was pressed to refactor quickly.If you use SSAS or MDX regularly, and even if you consider yourself an expert, you should still peruse this book. I found a number of recipes that I can incorporate into my daily life. I also found some new ideas and ways to use MDX that I hadn't thought about previously.I liked the real-world examples best. Much better than the contrived code you'll see in many other books.
Amazon Verified review Amazon

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About the authors

Left arrow icon
Profile icon Tomislav Piasevoli
Tomislav Piasevoli
Tomislav Piasevoli is a Business Intelligence (BI) specialist with years of experience working with Microsoft SQL Server Analysis Services (SSAS). He successfully implemented many still-in-use BI solutions, helped numerous people on MSDN forum, achieved the highest certification for SQL Server Analysis Services (SSAS Maestro), and shared his expertise in form of MDX cookbooks. Tomislav currently works as a consultant at Piasevoli Analytics company (www.piasevoli.com) together with his brother Hrvoje. They specialize in Microsoft SQL Server Business Intelligence platform, SSAS primarily, and offer their BI skills worldwide. In addition to his regular work, Tomislav manages to find the time to present at local conferences or to write an article or two for local magazines. His contribution to the community has been recognized by Microsoft honoring him with the Most Valuable Professional (MVP) award for six consecutive years (2009-2015).
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See other products by Tomislav Piasevoli
Profile icon Li
Li
Sherry Li is an Analytic Consultant who works for a major financial organization with responsibilities in implementing data warehousing, Business Intelligence, and business reporting solutions. She specializes in automation and optimization of data gathering, storing, analyzing and providing data access for business to gain data-driven insights. She especially enjoys sharing her experience and knowledge in data ETL process, database design, dimensional modeling, and reporting in T-SQL and MDX. She has co-authored two books, the MDX with SSAS 2012 Cookbook and MDX with Microsoft SQL Server 2016 Analysis Services Cookbook, which have helped many data professionals advanced their MDX skill in a very short time.
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Packt eBooks are a complete electronic version of the print edition, available in PDF and ePub formats. Every piece of content down to the page numbering is the same. Because we save the costs of printing and shipping the book to you, we are able to offer eBooks at a lower cost than print editions.

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For optimal viewing of our eBooks, we recommend you download and install the free Adobe Reader version 9.