POWER BI DAX EXPRESSIONS – Level 2 – PART – 8

YTD, QTD, MTD Calculations with DAX: 

Understanding Year-to-Date (YTD), Quarter-to-Date (QTD), and Month-to-Date (MTD) calculations with DAX are essential for time-based analysis. Here’s how to practically implement these calculations:

Use DAX functions like TOTALYTD, TOTALQTD, and TOTALMTD to calculate YTD, QTD, and MTD values based on date hierarchies.

Apply these calculations to measure data within specific time frames for meaningful insights.

DAX Calculations and Measures: 

DAX calculations and measures are fundamental for deriving insights from data. Here’s how to practically create and use these elements:

Build DAX calculations by combining functions and operators to perform custom data transformations and calculations.

Define measures to encapsulate complex calculations and aggregations for use in visuals and reports.

Using TOPN, RANKX, RANK.EQ: 

Employing TOPN, RANKX, and RANK.EQ functions enable ranking and filtering of data. Here’s how to practically work with these functions:

Utilize TOPN to retrieve the top N values from a table or column based on specified criteria.

Apply RANKX to assign rankings to data points within a table or column, considering user-defined sorting criteria.

Use RANK.EQ to calculate rankings and handle ties more precisely than RANKX.

Computations using STDEV & VAR: 

Performing computations with STDEV and VAR functions involves statistical analysis. Here’s how to practically work with these functions:

Utilize STDEV to calculate the standard deviation of a data set, which measures data variability.

Apply VAR to compute the variance, indicating data dispersion around the mean.

SAMPLE Function, COUNTALL, ISERROR: 

Practical usage of functions like SAMPLE, COUNTALL, and ISERROR is crucial for data analysis. Here’s how to practically employ these functions:

Use SAMPLE to retrieve a random sample of data from a table or column for analysis or visualization.

Apply COUNTALL to count all rows, including those with blank or null values, in a table or column.

Utilize ISERROR to identify and handle errors or exceptions in data calculations.

ISTEXT, DATE FORMAT, TIME FORMAT: 

Managing text, date, and time data in DAX involves functions like ISTEXT, DATE FORMAT, and TIME FORMAT. Here’s how to practically handle these data types:

Use ISTEXT to determine whether a value is text, allowing for conditional operations.

Apply DATEFORMAT and TIMEFORMAT to format date and time values according to desired display preferences.

Time Intelligence Functions with DAX: 

Time intelligence functions in DAX facilitate in-depth temporal analysis. Here’s how to practically use these functions:

Implement DATESYTD, DATESQTD, and DATESMTD to calculate YTD, QTD, and MTD periods for date-based data analysis.

Utilize END OF YEAR, END OF QUARTER, END OF MONTH, FIRSTDATE, LASTDATE, and DATESBETWEEN for precise date calculations.

Apply CLOSINGBALANCEYEAR and CLOSINGBALANCEQTR for accumulating balances in financial data.

Employ SAMEPERIOD and PREVIOUS MONTH to compare data across time periods, facilitating trend analysis.

Utilize QUARTER for extracting the quarter from a date value, aiding in period-based calculations.

KPIs with DAX. Vertipaq Queries in DAX: 

Key Performance Indicators (KPIs) and VertiPaq queries are essential for advanced data analysis. Here’s how to practically work with these concepts:

Define KPIs in DAX to measure and monitor critical performance metrics within your data.

Understand VertiPaq queries, which optimize data retrieval and processing for improved query performance.

IF.ELSEIF. Conditions with DAX: 

Using conditional statements in DAX is vital for data processing and decision-making. Here’s how to practically create IF.ELSEIF.. conditions with DAX:

Implement IF functions to apply conditional logic based on specified criteria.

Extend conditional statements with ELSEIF for handling multiple conditions and outcomes.

Slicing and Dicing Options with Columns, Measures: 

Slicing and dicing data involve interactive analysis with columns and measures. Here’s how to practically perform these operations:

Slice data by filtering and selecting specific values or ranges within columns to focus on specific subsets of data.

Dice data by combining measures and columns to explore multidimensional data perspectives and analyze interactions.

DAX for Query Extraction, Data Mashup Operations: 

Leveraging DAX for query extraction and data mashup operations enhances data integration. Here’s how to practically use DAX for these tasks:

Extract data from tables and columns using DAX queries to obtain specific data subsets.

Perform data mashup operations by combining data from different sources and tables, enabling comprehensive analysis.

                                            Power BI Deployment & Cloud – PART-9

Calculated Columns and Calculated Measures with DAX: 

Understanding and working with calculated columns and measures is fundamental in DAX. Here’s how to practically create and utilize these elements:

Create calculated columns to add new data columns to your tables based on DAX expressions.

Define calculated measures to perform calculations and aggregations for use in visuals and reports.