RE: Datawarehousing help

Yechiel - I did not mean to imply that SAS had not improved since the '80s. They would be out of business otherwise. And of course every DW vendor is "full solution" vendor. Just read their brochures if you don't believe me. My point was that if you understand a company's roots, then often a lot of their quirks start to make sense. My point was that SAS has a VERY strong mathematical foundation, which may help set your understandings.

        The features you have listed Rachel can get off their brochures. Can you provide any more ideas? My guess is that they might be very strongly positioned to perform data mining. Can you confirm that? Dennis Williams
DBA
Lifetouch, Inc.
dwilliams_at_lifetouch.com

-----Original Message-----
Sent: Sunday, May 05, 2002 6:23 AM
To: Multiple recipients of list ORACLE-L

Hello Dennis

SAS has progressed a little in the last years and now offer a complete DW solution, including ETL tools.

You can use their tools also to populate and query oracle.

Yechiel Adar
Mehish

• Original Message ----- To: Multiple recipients of list ORACLE-L <ORACLE-L_at_fatcity.com> Sent: Saturday, May 04, 2002 2:48 AM

> Rachel - I always find it helpful to understand something if I know the
> origins. I worked with SAS several years ago. At that time it was a
> statistical analysis package. A scientist or engineer could load a set of
> test data into it and perform various arithmetic and statistical analyses.
> Today most of that can be done with Oracle or MS Excel. My point is that I
> would expect it to be heavily biased toward mathematical capabilities.
Like
> Data Mining, which is all statistics. Learn what that term means.
> To learn Data Warehousing, I would encourage you to just do some
> "Googling" and find good tutorials. An excellent newslist is dwlist.
> Instructions:
>
> For help with list commands, send a message
> to <mailto:dwlist-request_at_datawarehousing.com> with the
> word "help" in the body of the message.
>
> The magazine http://www.intelligententerprise.com/ has some excellent
> information. I would search for "Ralph Kimball". He is one of the leading
> figures in the DW arena. Look for some of his earliest columns on the
> magazine site. He also answers questions on dwlist from time to time.
>
> The main change you need yourself is to forget normalization. DBAs that
> can't get past that point don't last long in the DW field. In the early
days
> the DW people would patiently explain the reasons to a DBA, but today
there
> are enough DBAs that have made the leap that a hard-headed normalization
> bigot just isn't tolerated. It is much easier to just ask for a
replacement
> DBA.
> The reason normalization isn't adhered to in DW is that users will
> be creating their own queries and they can't understand 10-table joins
with
> outer joins, etc. A DW is usually loaded and then queried. Our DW is
loaded
> each weekend and then queried all week. So a DW is deliberately
denormalized
> and contains redundant data for ease of use.
> OLTP databases have no concept of "time". A DW is all about time. To
> reconstruct what the situation is at various points of time, the DW has
> loads of historical data. For example, marketing people need to be able to
> reconstruct the amount of business they did with a customer over a period
of
> time last year and compare it with the same period this year.
> So between denormalization and tons of detailed historical data, DWs
> are normally BIG! Fortunately they are usually read-only.
> For Oracle, you want Enterprise Edition with the partitioning
> option. And study Oracle Materialized Views.
> In schema, a DW is usually a central fact table and 4-6 dimension
> tables. Less than 4 dimensions and you don't need a DW. More than 6 and
> marketing people can't understand the model. Normally the fact table is
much
> larger than the others, but not always. One of Wal-Mart's dimension tables
> is each person in the U.S. Just size each of those tables, and you've got
> your size. Growth is easy to predict. Ralph Kimball warns that often
people
> will get the grain wrong. They will size it for data summarized at the
> weekly level, then after it is built they will realize that isn't going to
> cut it and need a daily level. You must start almost from scratch and get
7
> times the disk capacity. That is the fun side of being a DW DBA. Your
> cynical instincts will still serve you well, just get them away from
> normalization and worry about getting the grain right.
> Okay, I've rambled along here too long. Hope that gets you off on
> the right foot.
>
> -----Original Message-----
> [mailto:Rachel_Carmichael_at_Sonymusic.com]
> Sent: Friday, May 03, 2002 5:08 PM
> To: Multiple recipients of list ORACLE-L
>
>
>
>
> Okay, my background is OLTP, but we are looking at a data warehousing
> project
> here....
>
> any and all help appreciated! Specifically:
>
> 1) does anyone have any experience with a product called "SAS
> Datawarehousing
> Administrator" (or SAS)?
> 2) how do I go about doing rough estimates of sizing needs, assuming I
will
> get
> rough numbers of information being collected, growth rates, length of
> history to
> keep, etc.
>
> help?
>
> Rachel
>
>
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> Author:
> INET: Rachel_Carmichael_at_Sonymusic.com
>
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> Author: DENNIS WILLIAMS
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-- 
Author: Yechiel Adar
  INET: adaryechiel_at_hotmail.com

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Author: DENNIS WILLIAMS
  INET: DWILLIAMS_at_LIFETOUCH.COM

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