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This chapter covered the use of derived schemas to enhance query performance or reduce the complexity of report creation Key lessons included the following: A single schema design can rarely meet 100 percent of the reporting needs with maximum efficiency For a minority of business questions, an alternative format may be optimal A derived schema takes data from the original dimensional schema and restructures it for specific kinds of use A derived schema may be implemented as a star or as a cube Supplementing a star containing granular data with cubes derived for reporting purposes is a powerful combination Snapshots may be derived from transactions, although they are not always When derived, they greatly simplify the process of determining the cumulative effects of individual transactions on status measurements like levels or balances Accumulating snapshots are usually derived from one or more stars.

In many ways, security risks are overstated. Often, popular technical media will expose some shortcoming in a networking protocol and thus give the impression that no computer is safe. A common example is a legitimate warning about a virus that will affect very few (if any) systems. It s important not to underestimate what people may do. For this reason, it s best to consider what is possible instead of what is probable. Many organizations keep controls in Human Resources departments for handling salary information. However, they overlook the fact that a junior database administrator may have unrestricted access to this information. Clearly, both a management and a technical solution are required to prevent problems.

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Each row correlates multiple activities, greatly simplifying the otherwise complex process of studying the time spent at various process stages Core fact tables are often derived from type-specific custom fact tables The core fact table makes it possible to conduct analysis across all types, without the need to perform unions Merged fact tables precompute the results of drilling across two or more fact tables This makes cross-process comparison easier and faster, and is especially helpful when existing tools cannot be used to drill across Pivoted fact tables transpose facts organized row-wise into multiple facts in a single row, or vice versa There may not be a large performance benefit, but there may be value in the reduced complexity of report development Sliced fact tables take subsets of the original star, normally defined based on a single attribute value.

If you really wanted to secure your server, you d probably bury it in six feet of concrete and make sure that a network cable gets nowhere near it Then, even the best hackers won t be able to get to it (unless, perhaps, they do part-time masonry work) However, this causes another problem: No one who should be able to get information from the machine can do so On the other end of the spectrum, you could forget security entirely The most usable system design is probably one where all data resides in an organized collection that is accessible to all users Preventing unauthorized access to data will always include a tradeoff between security and convenience If policies are too strict, legitimate users (the vast majority of people in your company) will find it difficult to get their jobs done.

These tables have a smaller size and scope but do not sacrifice detail They may be useful in departmental, distributed, or mobile applications, or as the basis of a role-based security architecture Set operation fact tables precompute the results of comparing two fact tables using subqueries or union, intersect, or minus operations They can be significant timesavers, and dramatically simplify the necessary report SQL Remember that derived tables do not achieve their advantages for free The cost is an increased burden for the loading and management of warehouse data structures Do the heavy lifting up front is an admirable mantra but must be balanced with the business benefit of derived structures This balancing act will be discussed in 18, How to Design and Document a Dimensional Model..

Codd defines relational database model IBM's System/R project begins First article describing the SEQUEL language System/R customer tests Oracle introduces first commercial RDBMS Relational Technology introduces Ingres IBM announces SQL/DS ANSI forms SQL standards committee IBM announces DB2 ANSI SQL1 standard ratified Sybase introduces RDBMS for transaction processing ISO SQL1 standard ratified Ashton-Tate and Microsoft announce SQL Server for OS/2 First TPC benchmark (TPC-A) published TPC-B benchmark published SQL Access Group database access specification published Microsoft publishes ODBC specification ANSI SQL2 standard ratified TPC-C (OLTP) benchmark published First shipment of specialized SQL data warehousing systems First shipment of ODBC products TPC-D (decision support) benchmark published Commercial shipment of parallel database server technology Publication of standard API for OLAP database access and OLAP benchmark