Consumer data has been used since the ancient Greek times to guide shipments of olive oil and other commodities throughout the Ancient Grecian Empire and beyond. While the foundations of the data storage have changed dramatically from the Mesopotamian clay tablets to today's modern database management systems, the goals of business intelligence and data mining remain unchanged. The basic tenet of business intelligence is that one can predict the future by analyzing the past and grouping together related consumers to develop highly sophisticated and accurate predictive models. These predictive models can save tens of billions of dollars a year in advertising. At the same time, consumers are provided with targeted marketing which is most appropriate to their needs.
Business intelligence is not limited exclusively to the area of marketing and sales. Today, hospitals group patients together in terms of their age and symptoms, and analyze treatment regimens in order to determine the best course of treatment for specifically identifiable populations.
Though the use of business intelligence no doubt saves lives, it has even more wide ranging social implications. First and foremost is the issue of data privacy. As consumer monitoring becomes more and more ubiquitous, we see that many privacy advocates do not want even the most innocuous behaviors recorded. For example, many supermarkets monitor consumer purchasing habits via a buyers’ club card. Fortunately, most consumers don't care whether anyone else knows they prefer peas to string beans. Through the use of the buyers’ club card, consumers passively allow point of sale systems to readily track purchases, and tie individual purchases to background demographic information. When consumers apply for buyers’ club cards, they provide basic demographic information which is in turn analyzed with publicly available information on major life events, such as the purchase of a house, a divorce, the presence or absence of children, and income, such that the database has
detailed information not only about what products are being purchased, but the basic demographics of the person who is purchasing.
The issue of data storage has always been important to business intelligence because of the dynamics of changing technology. Disk prices are falling radically each and every year. Back in the 1980’s, 1.2 gigabytes of storage could cost upwards of $200,000.00; whereas, today you can purchase the same amount for less than $100.00. Given our ability to store large amounts of empirical information cheaply, the goal of the business intelligence manager is to somehow be able to cleanse and manipulate this data in such a way that accurate predictive models can be built.
Follow the link below to take a closer look at the evolution of business intelligence from the perspective of the database manager and explore how the database influences the manipulation of these vast quantities of observable data in the real world.
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Database Management for Business Intelligence
Super Fast Database Copying/Cloning
A database cloning procedure is especially useful for the DBA who wants to give his developers a full-sized TEST and DEV instance by cloning the PROD instance into the development server areas.
An Oracle database cloning procedure can be used to quickly migrate a system from one UNIX server to another. The process can clone an Oracle database, ultimately resulting in the fastest way to copy an existing Oracle database.
To find out more on the secrets of super fast database cloning, see the full article here:
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The Top 10 Reasons for Poor Oracle Performance
The Oracle Documentation lists reasons for poor performance, but they are not as comprehensive or useful as our BC top-10 list. Oracle Corporation has never been as good at tuning their own software as third-party experts, and their performance cause list is missing many important factors.
Some factors, like a mis-configured I/O sub system, are obvious causes of poor Oracle performance; however, some of the others may come as a surprise.
Click below to see the BC top-10 list of the most common Oracle performance problems:
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Managing an Aging Oracle Database
The Geriatric Instance – Managing the legacy Oracle database is not an easy task.
As Oracle databases pass the decade mark, they begin to suffer from a host of age-related problems. Just like people, the sheen is gone, parts become unwieldy and creaky and some areas of the database need ongoing medical attention.
See these important tips and tricks for caring for an elderly legacy Oracle database:
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Oracle hash joins tips
In cases where a very small table is being joined to a large table, the Oracle hash join will often dramatically speed-up the query. Hash joins are far faster than nested loop joins in certain cases, often in cases where your SQL is joining a large table to a small table.
However, in a production database with very large tables, it is not always easy to get your database to invoke hash joins without increasing the RAM regions that control hash joins. For large tables, hash joins requires lots of RAM.
Oracle places limits of the amount of RAM available for hash joins so that no single session will "hog" all of the RAM.
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Auditing and reporting Oracle user activity
Changes in U.S. federal laws have mandated increased security for auditing Oracle user activity. HIPAA, the Sarbanes-Oxley Act, and the Gramm-Leach-Bliley Act have all produced serious constraints on Oracle professionals who are now required to produce detailed audit information for Oracle system users.
Starting with Oracle8i, Oracle introduced special triggers that are not associated with specific DML events (e.g., INSERT, UPDATE, and DELETE). These system-level triggers included database startup triggers, DDL triggers, and end-user login/logoff triggers.
While Oracle provided the functionality for these new triggers, it was not clear how they could be used in order to track system-wide usage.
Read more about Oracle auditing and reporting here:
http://oracle-tips.c.topica.com/maamFPSabM2uEbLGJrib/