A Guide to Utilising Monthly Date Tables for Trend Analysis

Usama Ahmed
Dec 20, 2023
2 min read

In the realm of data analysis, understanding how to harness the power of temporal data is crucial for uncovering trends and patterns. Today, we’ll explore how to use the dbo.udf_ReturnSelectedMonths function to generate monthly date tables, offering a valuable resource for trend analysis. Let’s dive into the script and see it in action.

Script Overview

/*
This Function provides all the Month Year and data that can be joined with another table for trend analysis
*/
-------====== Test Values ======
DECLARE @MonthFrom INT
    ,@MonthTo INT
    ,@Year INT
    ,@SPName VARCHAR(100) -- Parameters
 
SET @MonthFrom = 1
SET @MonthTo = 3
SET @Year = 2011

Setting the Stage

@MonthFrom, @MonthTo, @Year: These variables define the temporal scope for the trend analysis. Adjust them based on the desired timeframe.

-----=============================
DECLARE @main TABLE (
    ID INT identity
    ,DateToJoin DATETIME -- These has to
    )
 
INSERT @main
VALUES ('1 jan 2011')
 
INSERT @main
VALUES ('21 jan 2011')
 
INSERT @main
VALUES ('6 feb 2011')

Preparing the Main Table

A test table, @main, is created with a DateToJoin column. This column holds dates that will be joined with the generated monthly date table for trend analysis.

SELECT * --MonthName, MonthNumber, MonthYear, StartDate, EndDate, Dimension1, Measure1--, Dimension2, Measure2, Dimension3, Measure3
FROM udf_ReturnSelectedMonths(@MonthFrom, @MonthTo, @Year) sm
INNER JOIN @Main mn ON mn.DateToJoin BETWEEN sm.StartDate AND sm.EndDate
ORDER BY 1

The Joining Dance

The function is invoked to generate a monthly date table (sm) for the specified timeframe.
The @main table is joined based on the DateToJoin column, ensuring a seamless connection between the two tables.
The result set includes essential details like MonthName, MonthNumber, MonthYear, StartDate, and EndDate, offering a comprehensive view for trend analysis.

Example Output

ID	MonthName	MonthNumber	MonthYear	StartDate	EndDate
1	January	1	2011	2011-01-01T00:00:00Z	2011-01-31T23:59:57Z
2	February	2	2011	2011-02-01T00:00:00Z	2011-02-28T23:59:57Z
3	March	3	2011	2011-03-01T00:00:00Z	2011-03-31T23:59:57Z

Conclusion

As demonstrated, utilizing the dbo.udf_ReturnSelectedMonths function can significantly enhance your ability to perform trend analysis. By seamlessly joining a monthly date table with your main data, you gain valuable insights into patterns, allowing for more informed decision-making. Incorporate this approach into your SQL toolkit, and unlock the power of temporal trends in your data.