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2008年(1655)

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分类: LINUX

2008-05-28 14:48:49

I am Michael R. Ault, a Senior Technical Management Consultant with TUSC, an

Oracle training, consulting and remote monitoring firm. I have been using Oracle

since 1990 and had several years of IT experience prior to that going back to

1979. During the 20 odd years I have been knocking around in the computer field

I have seen numerous things come and go. Some were good such as the PC

and all it has brought to the numerous languages which have come, flared briefly

and then gone out.

Data warehousing is a concept that really isn't new. The techniques we will

discuss today have their roots back in the colossal mainframe systems that were

the start of the computer revolution in business. The mainframes represented a

vast pool of data, with historical data provided in massive tape libraries that could be tape searched if one had the time and resources.

Recent innovations in CPU and storage technologies have made doing tape

searches a thing (thankfully) of the past. Now we have storage that can be as

large as we need, from megabytes to terabytes and soon, petabytes. Not to

mention processing speed. It wasn't long ago when a 22 mghz system was considered state-of-the-art, now unless you are talking multi-CPU each at over

400 mghz you might as well not even enter into the conversation. The systems

we used to think where massive with a megabyte of RAM now have gigabytes of

memory. This combination of large amounts of RAM, high processor speed and

vast storage arrays has led to the modern data warehouse where we can

concentrate on designing a properly architected data structure and not worry

what device we are going to store it on.

This set of lessons on data warehousing architecture and Oracle is designed to

get you up to speed on data warehousing topics and how they relate to Oracle.

Initially we will cover generalized data warehousing topics and then Oracle

features prior to Oracle8i. A majority of time will be spent on Oracle8 and

Oracle8i features as they apply to data warehousing.

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