Power BI is one of the leading Microsoft BI tools globally, owing to its salient features like in-depth visualization and simplicity of use. Its self-service competency facilitates users to create desired reports and dashboards. The client base leveraging the power of this tool ranges from students to SMEs to enterprises. Power BI developers, consultants, analysts are quite a in demand and the level of expertise in this technology is rising.
Power BI has been doing great when it comes to extracting simple insightful information. But organizations today need more – analyzing information based on different categories, calculating percentage growth, annual growth as compared to peers/last year, etc. This calls for a further level of competence that can offer detailed charts and visualization and give answers to real-life business queries.
The answer lies in Data Analysis Expressions (DAX) – a set of functions, constants, and operators that can be used as formulas to calculate different values based on available data. Power BI DAX consists of a library of 200+ components offering great flexibility to create measures to extract desired results.
DAX stands for Data Analysis Expressions. It is a consolidated library that builds formulas and expressions in Power BI, Power Pivot, and Analysis Services. It can calculate and return a single value or multiple values, from data in related tables and columns in tabular data models. Considered an ideal syntax language, DAX possesses a great capability to manage and manipulate data.
DAX offers the following benefits:
DAX Studio – It is a tool to write, execute, and analyze DAX queries in Power BI Designer, Power Pivot for Excel, and Analysis Services Tabular. It is an open-source client tool that connects to multiple data sources, has integrated support for DaxFormatter.com, and collects detailed query execution statistics while performance tuning.
The basic understanding of DAX lies in the following concepts – Measures, Calculated Columns, Row-level security, Syntax, Context, and Functions.
Measures are the dynamic calculation formulas whose result changes based on the context. They are created utilizing the DAX formula bar in the model designer. Standardized aggregation functions can be automatically used, based on filters applied, or users can create their own formula through the DAX formula bar. Here, the syntax of each measure shows the name of the measure before the formula and it must be defined in a table. Users can move a measure from one table to another without any loss in functionality.
Calculated columns indicate the result of computations between two or more columns, belonging to the same table or different tables, during a data refresh. These are specially meant to undergo row-level computations and create a new column in the existing table. It must possess at least one function and is used when there is a need to filer/sort information. All calculated columns occupy space in memory and undergo computation while table processing. It uses up RAM and hence is not recommended during the production stage.
In row-level security, the evaluation of a DAX formula must be a Boolean True or False condition. It facilitates the creation of an allowed row set; hence other roles cannot access the assigned row. Only if the user is a member of another role, he/she can view data for the other row. These security-based formulas are meant for specific rows and their related ones. Filters are applicable for the currently active relationship.
The different elements that make up the DAX formula are the syntax. It is basically the way we write the formula. Being the fundamental base of any coding scheme, a syntax error is raised if the syntax is incorrect. There is a DAX editor in Power BI Desktop that has a suggestion feature that is mainly utilized for the creation of syntactically correct formulas and choosing the correct elements.
It is important to understand the DAX context fundamentals to get detailed knowledge about the DAX functions and their operations in Power BI. It helps users perform dynamic analysis with an effective way of finding problems in formulas.
Types of Dax contexts:
This considers a specified row, the ‘current row’ that has been filtered through a DAX expression. It emphasizes the formula operation on the current row. Such a type of context is usually applicable to the measure rows. Even if the values belong to another table, it includes the current row value from those tables.
This moves a step further and applies filters on specific values within a row. It is applied in addition to the row context to calculate certain specified ranges. Filters are applicable to columns in the designer or in the presentation layer. It can also be applied through filter expressions in the formula.
This talks about a subset of data that is subtly recovered for a formula. The results of the formula shall depend upon where exactly the formula is placed and how the context changes.
Functions are basically predefined formulas that are used to calculate desired outputs through arguments being passed in a specific order. These arguments could be expressions, text, logical values, numbers, other formulas, etc.
The main reasons why DAX Functions in Power BI is so important are-
There are multiple types of Power BI functions that have their own significance, here are they:
Operates on different mathematical and trigonometric functions and returns relevant values, as needed.
Returns a value from another related table and offers a relationship between different expressions in a single table or different ones.
Offers statistical functions that undergo aggregations. Possible to create aggregations based on relevant information from tables like minimum, maximum, sum, average, etc.
Performs financial calculations like rate of return, net present value, etc.
Offers a comparison between the input value and if the value is correct or not, returning the relevant response.
Offers information about values in an expression based on its logical output.
These are typical date and time functions that are based on the DateTime data type.
They return specified data types, lookup values in different tables, and filter through related values.
Provides a set of functions that can return a part of the string, concatenate values from the string, control functions for date and time formats, and search for text in a string.
Lets users build meaningful comparisons and create calculations that leverage the in-built knowledge about dates and calendars.
These functions either manipulate current tables or return a table, by adding calculated columns to necessary tables.
As important and popular it sounds, DAX in Power BI has its own set of challenges that must be attended to, for a seamless experience, for both developers and end-users both. Here are a few of them:
DAX language in Power BI stands for Data Analysis Expressions. It is a formula expression language that includes several functions, and the entire code resides within different functions.
DAX Studio is a tool in which developers can write, execute, and analyze DAX queries with Power BI Designer, Power Pivot for Excel, and Analysis Services.
Yes, DAX Studio is free to download and use.
Time intelligence DAX functions in Power BI are those functions that empower developers for data manipulation using time periods – days, months, years. It also performs different calculations over the period.
Some commonly used DAX functions in Power BI are CALCULATE(), FILTER(), MAX(), AVERAGE(), RELATED(), SUM(), MIN(), ALL FUNCTION() and many more.
MDX is used to query data from a cube while DAX is an expression language and hence cannot be used that way. MDX is used to query against SSAS multidimensional models while DAX is used for SSAS tabular models. DAX supports direct queries while MDX doesn’t.
DAX in Power BI acts as a catalyst in offering an enhanced experience to Power BI users. It is not that developers cannot utilize Power BI without DAX but if DAX functions are used, it surely brings a big boom to the results that are fetched by using the variety of functions. Power BI is surely benefited big time with DAX and it has a bright future.
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