DAX Function for Tagging Dates Based on Criteria

In this guide, we will create a DAX function to tag dates as 'MOC' if they fall between the 20th and 21st of any month, and attach the month number only if it is greater than 1.

Step-by-Step Solution

Function Documentation

The function TagDateMOC tags dates as 'MOC' with specific criteria:

• Criteria: Date should be between the 20th and 21st of the month.
• Suffix: If the month is greater than 1, append the month number to 'MOC'.

Function Definition

--
-- TagDateMOC: This function tags dates as 'MOC' if they fall between the 20th and 21st of the month.
-- It appends the month number if the month is greater than 1.
-- 
-- Parameters:
-- * DateColumn (Date): The date column to be evaluated.
--
-- Returns:
-- * Tagged date string based on the specified criteria.
--

TagDateMOC := 
VAR DayOfMonth = DAY(DateColumn)
VAR MonthNumber = MONTH(DateColumn)
VAR TagLabel = 
    IF (
        DayOfMonth >= 20 && DayOfMonth <= 21,
        IF (MonthNumber > 1, "MOC" & MonthNumber, "MOC"),
        BLANK()
    )
RETURN
    TagLabel

Explanation

• Input Validation: The function assumes DateColumn is a valid date column.
• Logic:
  1. Extract the day of the month using DAY(DateColumn).
  2. Extract the month of the date using MONTH(DateColumn).
  3. Tag as 'MOC' if the date is between the 20th and 21st.
  4. Append the month number if it is greater than 1.
• Return Value: Returns 'MOC' or 'MOC' concatenated with the month number, based on the criteria.

Real-World Usage Example

Here is an example of how to use the TagDateMOC function within a larger DAX query:

EVALUATE
ADDCOLUMNS (
    CALENDAR (DATE(2023, 1, 1), DATE(2023, 12, 31)),
    "MOC_Tag", TagDateMOC([Date])
)

• Explanation:
  • CALENDAR function generates a date table for the year 2023.
  • ADDCOLUMNS function adds a new column "MOC_Tag" using the TagDateMOC function, evaluating each date in the calendar.

Good Practices and Recommendations

• Code Readability: Ensure that your DAX code is well-commented and variables are meaningfully named for better readability.
• Error Handling: This solution does not incorporate error handling, assuming DateColumn is always valid. For production, consider adding error checking mechanisms.
• Testing: Extensively test the function on different datasets to ensure accuracy.

Further Learning

For more advanced DAX concepts and in-depth learning, consider exploring courses on the Enterprise DNA platform, focusing on DAX formulas, advanced analytics, and data modeling.

By following these steps, we created an efficient DAX function that exemplifies best practices in DAX coding and addresses the user-defined problem effectively.