Data Quality Assessment (amazon affiliate link)

I've just started reading Data Quality Assessment by Arkady Maydanchik. From the back cover blurb:

DATA QUALITY ASSESSMENT is a must read for anyone who needs to understand, correct, or prevent data quality issues in their organization. Skipping theory and focusing purely on what is practical and what works, this text contains a proven approach to identifying, warehousing, and analyzing data errors. Master techniques in data profiling and gathering metadata, designing data quality rules, organizing rule and error catalogues, and constructing the dimensional data quality scorecard.

Sounds intriguing.  I'm a fan of theory though, because I think it helps professionals better react to real world situations, so I'll have to see what the publisher means by "skipping theory".

Quote of the day:
I am certain there is too much certainty in the world. - Michael Crichton

I'm happy to announce that Gartner has published a research note on Industry Standard Data Models (ISDM) and InfoAdvisors' services in helping clients use them effectively.  If you are attending DAMA, contact me (karen@infoadvisors.com) for information on how to get a complimentary copy of this case study.

This research note, InfoAdvisors: Modeling Beyond a Blank Sheet, authored by Michael Blechar, focuses on how organizations can benefit from adopting ISDMs.  He discusses how InfoAdvisors provides insights into the benefits, risks and best practices involved with implementing industry-standard data models and patterns.

If your organization is a Gartner subscriber, you can download the note for free by visiting Gartner.com and searching for InfoAdvisors or using the research ID: G00154734.

Otherwise, you can purchase the note from the Gartner website.

As a reminder, I will be speaking on a similar topic at the upcoming DAMA LA meeting on 25 February 2008.  See our event listings for more information.

A valued colleague of mine, David Waxberg, sent me a link to a discussion on the history of the term blob.  I had always understood that BLOB stood for Binary Large Object.  According to some database pioneers, this just isn't the case.

According to Ann Harrison and Jim Starkey (who developed Interbase), the term blob started out as more of a yadda, yadda, yadda type phrase that was used to describe a new DBMS concept.   Marketing and management, though, felt that they could not use the term blob and called the functionality segmented strings.  Then marketing accepted the term blob, but did not want to say that it was just a filler term conscripted to be a serious DBMS functionality, so they came up with Basic Large Object as the meaning, turning blob into a  backronym.

Then the Informix guys used the same concepts and described a blob as a Binary Large Object, yet another backcronym.

" For the trivia inclined: Blob don't stand for nothin'. It isn't an
acronym for "basic large object" or "binary large object". A blob is
the thing that ate Cincinnatti, Cleveland, or whatever.

The precise chain of events that lead to the creation of the sublime
blob is:

1. Barry Rubinson, my boss at DEC, was prone to wandering around
muttering "blobs, blobs, we gotta have blobs." When I asked
what a blob was, he pointed out that I was the architect and
that was my job.

2. Marooned in Colorado Springs (where Barry lived) because of a
snow storm in Massachusetts (where I lived), and unable to
derive the grand theory of transaction consistency, I invented
the blob instead. Ah ha! A concept to hang on a wonder name!"

Now you know more about BLOBs than you did before.

Look for my next post on the birth of a relational DBMS...