22-25 April 2026
SQLBits 2014

DAX Patterns

Learn ready-to-use DAX patterns improving development speed of Power Pivot solutions. Good also for SSAS Tabular developers.
The DAX language has a low number of built-in functions, but it is very flexible and you can write complex calculations with it. It is so flexible that you might find many alternative ways to write an expression solving a business problem. You can save development time by adapting an existing DAX Pattern to your specific scenario. This session will present a set of fundamental patterns you have to know in DAX, because they are used very often in many business scenarios and are already tested and optimized, saving you from the effort of choosing between different possible optimizations.

Speakers

Marco Russo

sqlbi.com/blog/marco

Marco Russo's previous sessions

Aggregations in Power BI
Introduce Power BI aggregations with practical examples, evaluate pros and cons, and learn how to use alternative approaches by using DAX to control the aggregation used.
 
Using ALLEXCEPT or ALL/VALUES?
Learn when to use ALL / VALUES instead of ALLEXCEPT in DAX calculations.
 
Understanding window functions in DAX
Introduction to DAX window functions and apply semantics through several examples to understand their capabilities and performance.
 
Power BI Performance Analyzer crash course
Learn how to use Performance Analyzer in Power BI to get a first idea of performance bottlenecks in Power BI reports.
 
VertiPaq Analyzer crash course
Introduce VertiPaq Analyzer features in DAX Studio and as a library available in other tools.
 
My Power BI report is slow: what should I do?
Use Performance Analyzer and DAX Studio to find the performance bottleneck in a slow Power BI report.
 
Time Intelligence in Power BI
Create the right Date table and use DAX time intelligence functions or custom filters to get the desired calculation aggregating and comparing data over time.
 
VertiPaq Analyzer crash course
Learn how to read the information provided by VertiPaq Analyzer 2.0 and optimize data models in Power BI, Analysis Services, and Power Pivot.
 
Different types of many-to-many relationships in Power BI
Clarify differences between many-to-many and weak relationships in Power BI
 
DAX Best Practices
Best bractices in DAX formulas from real world experience.
 
Power BI Dashboarding
Power BI offers new features for creating dashboards on the cloud. In this session, you will learn how to create data models, display visualizations and synchronize cloud data with on premise data sources.
 
SSAS Tabular from the Trenches
In this session, we will share some of the hard lessons learned from the first large deployments in Analysis Services Tabular.
 
DAX Patterns
Learn ready-to-use DAX patterns improving development speed of Power Pivot solutions. Good also for SSAS Tabular developers.
 
Power Query in Modern Corporate BI
Explore Power Query features to import data from existing Corporate BI systems.
 
Modern Data Warehousing Strategy
This session will discuss what a modern strategy for data warehousing can be in this era, considering how the use of technologies like PowerPivot or Analysis Services Tabular affect the way you should model your data.
 
Create a Data Model in BISM Tabular
In this session you will see how to create a BISM Tabular data model from scratch, providing the required metadata in order to improve user experience navigating the data model by using client tools like Excel PivotTable and Power View.
 
Analysis Services Advanced Best Practices
This dense hour of presentation will cover design techniques to leverage cube features that also consider possible maintenance of the database structure over time.
 
BISM Introduction
Introduce the features of BISM (BI Semantic Model), the new engine that will be available in Analysis Services "Denali".
 
Vertipaq vs OLAP: Change Your Data Modeling Approach
In this session we will introduce the new modeling capabilities of Vertipaq, showing how the same scenarios can be modeled in both Multidimensional (MOLAP) and Tabular (Vertipaq), looking at how to enable your data warehouse to support both.