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This is a good example of where a technical failure, combined with human error, contributed to a catastrophic loss of data The general method of protecting against a hardware failure is to implement redundancy Redundant systems often have one or more backup (redundant) parts that can be used in the event that the primary part fails This is commonly done with power supplies and hard disks Although the concept of redundancy has some negative connotations in conventional language, it is very important in data protection situations Later in this book, we ll look at examples where redundant components can improve network performance When you re designing a redundant system, manual intervention may be required to prevent downtime and to replace failed parts Redundancy also applies to software and data; we maintain copies of this information on other forms of media so that it can be replaced if lost.

TiP Source aggregate tables from the base schema to guarantee consistent structure and content Following these guidelines, the overall dependency of table load routines during the ETL process might look like this: 1 Load base dimensions 2 Load conformed rollups 3 Load base fact table 4 Load aggregate fact table Actual dependencies are slightly more relaxed than this For example, after base dimensions have been loaded, it is possible to load the base fact table Unfortunately, there is a complication..

The SQL1 standard provided only the first possibility for the preceding examples it prohibited the modification of a primary key value that was "in use" and prohibited the deletion of a row containing such a primary key DB2, however, permitted other options through its concept of delete rules The SQL2 standard has expanded these delete rules into delete and update rules that cover both deleting of parent rows and updating of primary keys..

Even within the area of hardware and software failures, many misconceptions and oversights exist For example, assume that you implement hard disk redundancy to protect against disk failures This doesn t protect against a power supply failure, so you choose to upgrade to a server that has redundant power supplies You also place an uninterruptible power supply (UPS) on the circuit to prevent power problems external to the machine Now, you have reasonably protected this machine against disk and power failures But, what if a critical motherboard component or a disk controller fails As you can see, the list of things you need to protect against is a long one, and not all types of protection are practical We ll cover all of these topics later in the book.

One potential roadblock stands in the way of this simple workflow: the type 1 change. When base data and aggregates are loaded sequentially, the occurrence of a type 1 change can force the need to reload the aggregate completely, rather than update it incrementally. To understand why this happens, consider a very simple example. Suppose an aggregate of order_facts contains rows that summarize orders by product manager, which is a type 1 attribute. This aggregate will call for a simple conformed rollup of the product dimension, which includes only the column product_manager.

Although hardware and software failures are very real possibilities that shouldn t be ignored, there are several other events you must protect against..

Delete and Update Rules *

The product dimension has hundreds of products Each is managed by one of three people: Richard Meyers, David Yu, and Robert Jones The product_manager table has one row for each of these people Orders for all the products are recorded in order_facts, and the aggregate fact table summarizes orders by product_manager Subsequently, one of the products that Richard Meyers managed is reassigned to David Yu If we try to follow the process flow outlined earlier, this type 1 change gets us into trouble Step by step, here is what happens: 1 Load base dimensions The type 1 change calls for the product in question to be updated; its new manager is David Yu 2 Load conformed rollups If there is a date_updated on the base dimension table, it tells us the product has changed The manager on the changed record is David Yu.

Problems may occur by sheer accident. I gave an example earlier about how easy it might be to lose information in this Microsoft Word chapter file (and yes, I have made a backup since then). In many environments, accidental data loss is by far the most common type.