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Logically structure the data for archival When you move data from a production environment to an archive, the data can be moved into a separate partition, a separate table, or even a separate database Partitioned tables provide an efficient way to organize and move data for archival storage For example, you can create a single Orders table with two partitions One partition can be reserved for orders placed in the current month, and another partition can be used to archive all orders placed in all previous months At the end of every month, all data from that month can be moved into the sec ond partition Even if you move archival data from one table to another instead of from one par tition to another within the same table, using multiple partitions can still help you organize and simplify the archiving process.

For example, your archive pro cedure might consist of moving data from Table 1 (Orders) to Table 2 (OrdersArchive) To help prepare for data archival, Table 1 might include two partitions one for orders placed within each of the past two months When you need to archive data each month, you can move the partition containing the old est data into an empty partition in Table 2, after which you can move the data into a partition containing the rest of the OrdersArchive table (For more infor mation about using partitions, see Lesson 2, Archiving by Using Partitions, later in this chapter) Regardless of whether you use partitions, you can also structure your archive so that archival data is moved into a completely new database For example, you might move data from the Customer database used in production to the CustomerArchive database used only for archival purposes.

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You can also do the same with the Win32 service control APIs. The ChangeServiceConfig2 method can modify the trigger-start configuration of a service, through the use of elaborate data structures specific for each trigger type. (Some trigger types are simpler to configure than others.)

When you move data in this way from one database to another, remember that the archive database should typically have the same schema as the source database..

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For data archival, a data movement strategy defines how you will move database data from its original source in production to the new location in archival storage. The two main considerations in a data movement strategy include the frequency of data move ment and the method or methods to move the data.

Data archival frequency In general, you want to remove unneeded data from premium storage as soon as possible. How often you should move the data to the archival storage depends on several factors, including how much storage is available in the premium loca tion, how quickly data proliferates in your organization s database, and how quickly data becomes outdated or obsolete. Regardless of how often you decide to archive data, you should choose to archive data on a regular schedule when ever possible. A good starting point for designing such a schedule might be to archive data once a month at the end of every month.

Data movement methods You can move data from production to the archive by using a number of methods. If you have purchased an archive solution from a vendor, this solution might include software to automate the movement of data to the data archive. This method obviously simplifies the process of moving data. If you are creating your own archive solution and are moving data from one table to another, you can use data manipulation language (DML) triggers to automate the movement of data. Such DML triggers could automatically archive data whenever an order is closed (Closed column value set to 1, for example) or whenever a project is successfully completed (Successful and Completed col umn values set to 1, for example). Because DML triggers represent an automated solution that runs only when necessary, they are highly efficient. (Note, how ever, that you can also create and run stored procedures regularly that perform the same essential function.) To move data from one database to another, you have the option of leveraging an existing database replication infrastructure. (However, creating a replication infra structure for the sole purpose of archiving is not necessary or recommended.) Next, you can also use backup operations to archive data. The advantage of this method is that it does not require much administrative overhead. However, a limitation of backups is that they do not remove data from the original source. To offload unneeded data, you will have to delete this data manually or create a

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