GROUP BY Day

Query:

SELECT FORMAT(SaleDate, 'dddd') AS DayOfWeek,
SUM(QuantitySold) AS TotalQuantitySold
FROM #TempProductSales
GROUP BY FORMAT(SaleDate, 'dddd');

Output:

Result using Group By Day of Week

Explanation: In above query, we use FORMAT function to extract the day of week, allowing us to group sales by Day of week. The SUM function calculates the total quantity sold for each day of week.

How to Group by Day, Date, Hour, Month or Year in SQL Server

Grouping data by day, date, hour, month, or year in SQL Server involves using the GROUP BY clause and appropriate date functions to extract or manipulate the relevant portions of the datetime column.

The SQL Server GROUP BY operator is similar to the SQL GROUP BY Operator. The GROUP BY clause is a powerful feature for grouping rows based on unique combinations of values in specified columns. It facilitates the aggregation of data, allowing the application of aggregate functions to obtain meaningful insights.

Syntax:

SELECT column1, column2, aggregate_function(column3)

FROM table_name

GROUP BY column1, column2;

Explanation: In the above query, we used the GROUP BY clause to group rows in the result set based on unique combinations of values in columns column1 and column2. The SELECT clause then retrieves these grouped columns along with the result of applying an aggregate function aggregate_function(column3) to another column column3.

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DATEPART()

SQL Server provides a range of date and time functions that enable the database to extract and manipulate date and time information. These functions enable us to perform various operations such as extracting components of a date, performing calculations between dates, and formatting date values....

GROUP BY Day

Query:...

Grouping Data by Day, Date, Hour,Month or Year

GROUP BY Date...

Conclusion

The SQL Server GROUP BY clause, coupled with date and time functions, allows for versatile analysis and aggregation of temporal data. The choice of specific functions depends on the desired output and formatting preferences. Understanding these techniques is crucial for anyone dealing with time-based data in SQL Server databases....