Learn the difference between calculated columns and measures in Data Analysis Expression (DAX) in this free, 10-minute video by Marco Russo, a well-known book author on the subject. Calculated columns are calculated row-by-row when the content of a table is refreshed, whereas measures are computed at query time, by aggregating rows. However, they have different uses, including filtering or classifying data, so you often need to make a trade-off between purpose and performance.

• 16 August 2012
• 46971 views

CALCULATE is the most important function in Data Analysis Expression (DAX) because it allows you to manipulate filter context, which is necessary for building real-world calculations. Let Marco Russo explain it to you in this 47-minute video tutorial that contains 5 detailed demos. You will learn: when to use CALCULATE, its syntax, how to manipulate filters at column granularity level, and how to transform a row context into a filter context. Learning these concepts will enable you to write advanced calculations in DAX, and it will make following the remaining modules of our DAX video series easier.

• 19 December 2012
• 16752 views

Data Analysis Expressions (DAX) is useful for querying data, in addition to its more common use for defining measures and calculated columns in PowerPivot or tabular models. Marco Russo explains the tools, including DAX Studio, and the syntax necessary for writing DAX queries in this 46-minute video, containing 7 detailed demos, part of our series on DAX. You will learn about the EVALUATE statement, how to control projection of data by using ADDCOLUMNS and SUMMARIZE functions, how to use the ROW function to test new measures for your data model, and how to use DAX measures within MDX queries. By learning these concepts you will be able to use DAX queries as a data source for your reports, and for Excel tables.

• 30 January 2013
• 13343 views

The second module in this online training course, offers a 1 hour introduction to PowerPivot for SQL Server 2012, sometimes referred to as PowerPivot “2”. This module is of importance to those who need to model tabular data for analytics, or who simply want to explore a data set, before making a decision if it is worthwhile analysing it further. Also, if you plan on learning about BI Semantic Model, you need to know about PowerPivot “2”, as Tabular Mode of SSAS, and BI Semantic Model, make extensive use of the new PowerPivot features, extending them to enterprise needs. This module is presented as a series of slides, graphics, discussions, and 15 demos, recorded in high-resolution, so that you can follow the steps yourself.

• 12 March 2012
• 6937 views

Time Intelligence is a set of techniques for performing time and date-based calculations. It covers a broad set of calculations needed for business reporting. Let Alberto Ferrari, book author and a renowned Data Analysis Expressions expert, show you an in-depth tour of these functions, in this 1-hour video that contains 6 detailed, hi-def demos. You will learn about: calendar tables, time-based role dimensions, TOTALYTD, TOTALQTD, TOTALMTD, and the CALCULATE function used with time-oriented, predefined and custom filters, and dealing with semi-additive measures, including last-day, or last-non-empty aggregations.

• 27 August 2013
• 6187 views

Hierarchies, including parent-child ones, can be created using a combination of a few DAX formulas and a data model in Power Pivot or SSAS Tabular. Marco Russo, BI expert from sqlbi.com, shows you how to work with them in this 55-minute video. Well-implemented hierarchies can greatly enhance navigation and usability, so learn how to implement their calculation logic by watching this demo-rich tutorial.

• 10 December 2013
• 5747 views

Alberto Ferrari, BI expert from sqlbi.com shows how to solve common business patterns using the DAX language in this 50-minute, demo-focused video. Patterns are useful for two reasons: they let you learn advanced DAX techniques and, by adapting their code to your needs, you can use them as a quick recipe for your own scenarios. This video discusses banding, computing new vs old metrics, and many-to-many relationship patterns.

• 20 November 2013
• 4235 views

The learning goal of this module is to introduce you to the notion of table functions and to quickly describe the most important ones, but not to provide a detailed explanation of all the functions yet, as that happens in the later modules. Above all, you will see the interaction between tables and relationships and how to create calculated tables.

• 25 November 2017
• 475 views

CALCULATE is by far the most important, useful, and complex function of the DAX language. In reality, the function itself is an easy one. It only performs a few tasks, but the number of scenarios where CALCULATE is necessary, along with the complexity of the formulas that can be written with CALCULATE, make a full chapter absolutely necessary.

• 25 November 2017
• 308 views

At this point in the course, you have learned the basics of the DAX language. You know how to create calculated columns and measures, and you have a good understanding of common functions used in DAX. With the knowledge you have gained so far, you can already create many interesting reports, but you will need to learn evaluation contexts in order to create reports that are more complex.

• 25 November 2017
• 264 views

After you have seen the basics of evaluation context and the CALCULATE function, it is time to analyze how the relationships of a data model affects their behavior. You will learn how to transfer a row context following relationships, and how the filter context automatically propagates through relationships.

• 25 November 2017
• 197 views

In this final section, you will learn how to handle complex relationships between tables by leveraging the DAX language. The goal is not to just give you pre-built patterns that you can use in your model. Instead, we want to show you unusual ways of using DAX to build complex models, to widen your idea of relationships, and to let you experience what you can achieve with DAX formulas.

• 25 November 2017
• 182 views

Almost all data models need to analyze data over time. The first step for handling date calculation is to create a Date table, which simplifies any date-related calculation. Because of its importance, you should be careful when you create a Date table.

• 25 November 2017
• 149 views