INSERT PurchaseOrderHeader(PurchaseOrderID, EmployeeID, VendorID) VALUES (8, 256, 1616) INSERT PurchaseOrderHeader(PurchaseOrderID, EmployeeID, VendorID) VALUES (7, 255, 1678) INSERT PurchaseOrderHeader(PurchaseOrderID, EmployeeID, VendorID) VALUES (6, 253, 1664) INSERT PurchaseOrderHeader(PurchaseOrderID, EmployeeID, VendorID) VALUES (5, 251, 1654)
INSERT PurchaseOrderHeader(PurchaseOrderID, EmployeeID, VendorID) VALUES (4, 261, 1650) INSERT PurchaseOrderHeader(PurchaseOrderID, EmployeeID, VendorID) VALUES (3, 257, 1494) INSERT PurchaseOrderHeader(PurchaseOrderID, EmployeeID, VendorID) VALUES (2, 254, 1496) INSERT PurchaseOrderHeader(PurchaseOrderID, EmployeeID, VendorID) VALUES (1, 258, 1580) Let’s look at the example with a simplified table of orders – PurchaseOrderHeader. For example, dbForge Studio for MySQL includes Pivot Tables functionality that provides the desired result in just a few steps. There are applications that have tools allowing to implement data pivot in a convenient graphical environment. Pivoting data by means of tools ( dbForge Studio for MySQL) It is through the transformation from rows to columns that such a result can be easily achieved. moving values from rows to resulting columns.īelow is an example of the old table of products – ProductsOld and the new one - ProductsNew.
So, when reorganizing the database and transferring data to new tables or generating a required data representation, data pivot can be helpful, i.e. Often, the result of the pivot is a summary table in which statistical data are presented in the form suitable or required for a report.īesides, such data transformation can be useful if a database is not normalized and the information is stored therein in a non-optimal form. Such transformation is called pivoting tables.
This article deals with the transformation of table data from rows to columns. Automating data pivoting, creating query dynamically.Pivoting data by means of tools (dbForge Studio for MySQL).