To understand both the necessity of SQL statements and the challenges of it, it’s important to examine the traditional methods of using pivot and SQL unpivot statements. SQL is a programming language that can be used to manipulate databases to make data usable for analysis. Analysts can use SQL as a powerful tool to examine and analyse data, but using SQL well does require advanced technical knowledge.
An SQL pivot query aggregates data and connects it to show relationships. The pivot command turns unique values from one column into multiple columns. Here is an example of the syntax of an SQL pivot command:
That syntax is primarily only valuable to coders and developers because they understand it. Without the technical background, the query isn’t possible to make. The syntax isn’t intuitive. The output of the command is a table that displays the new columns and rows that are extremely valuable in analyzing the data. The key is finding a way to make a SQL pivot command easier.
After a pivot SQL command, there’s the SQL unpivot commands. Pivot and unpivot sound like opposites, but the unpivot command isn’t the true reverse of the pivot command. The unpivot command rotates columns into rows. The command doesn’t reproduce the original table before a pivot command because that command resulted in merged rows. Unpivot and T-SQL unpivot commands only rotate the existing columns, turning the SQL pivot columns to rows. Here is an example of the syntax of an SQL unpivot command:
The syntax for these unpivot commands is even more time-consuming and clunky than the pivot command. It takes training and time to be able to create these statements and get the output table.
So if both SQL pivot and unpivot statements are time-consuming and difficult to create, why do analysts continue to use them?