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1.
A new Quote of the Week was posted on the QUOTES page.

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A new To Laugh or Cry? item was posted on the LAUGH/CRY? page.

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A link to an exchange in which I participated was posted on the FP ONLINE page.

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I have added APPLIED MATHEMATICS FOR DATABASE PROFESSIONALS by Toon Koppelaars and Lex Haan to the recommended books widget on the home page.

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There is a tendency in the database field to distort, use poorly defined
terminology, or use it inconsistently.  As I already argued in previous posts, technologies that are founded or used without foundation knowledge and understanding will prove costly fads.

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A new Quote of the Week was posted on the QUOTES page. Consider it in the context of my posts on database vs. application enforced integrity.

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A new To Laugh or Cry? item was posted on the LAUGH/CRY? page.

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1.
A new Quote of the Week was posted on the QUOTES page.
I contend that in a certain sense the perspective is upside down and backwards. Can you figure out why?

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A new To Laugh or Cry? item was posted on the LAUGH/CRY? page.

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My latest Data Fundamentals column and a thread I participated in were posted on the ONLINE page.

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From Erwin Smout (via email):

In 2009, the ACM re-published Codd's paper Derivability, redundancy and consistency of relations stored in large data banks.

For searching purposes, the ACM "classifies" each published article using some "taxonomy" of their own making. Apparently, Codd's paper is classified under "Database Administration" and not under "Relational Database Model".

Says a lot, doesn't it?

UPDATE: I was wondering what ACM did classify under "relational model" (you can probably guess what I suspected). So I asked Erwin to check and here's what he found:

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(Erwin Smout is co-author of this post.)

Revised 8/26/18

In Implementation Data Modeling Styles Martijn Evers writes:

"Business Intelligence specialists are often on the lookout for better way to solve their data modeling issues. This is especially true for Data warehouse initiatives where performance, flexibility and temporalization are primary concerns. They often wonder which approach to use, should it be Anchor Modeling, Data Vault, Dimensional or still Normalized (or NoSQL solutions, which we will not cover here)? These are modeling techniques focus around implementation considerations for Information system development. They are usually packed with an approach to design certain classes of information systems (like Data warehouses) or are being used in very specific OLTP system design. The techniques focus around physical design issues like performance and data model management sometimes together with logical/conceptual design issues like standardization, temporalization and inheritance/subtyping."

"Implementation Data Modeling techniques (also called physical data modeling techniques) come in a variety of forms. Their connection is a desire to pose modeling directives on the implemented data model to overcome several limitations of current SQL DBMSes. While they also might address logical/conceptual considerations, they should not be treated like a conceptual or logical data model. Their concern is implementation. Albeit often abstracted from specific SQL DBMS platforms they nonetheless need to concern themselves with implementation considerations on the main SQL platforms like Oracle and Microsoft SQL Server. These techniques can be thought of as a set of transformations from a more conceptual model (usually envisaged as an ER diagram on a certain 'logical/conceptual' level but see this post for more info on "logical" data models)."

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1.
A new 'To Laugh or Cry?' link was posted on the LAUGH/CRY? page.

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A new 'Quote of the Week' was posted on the QUOTES page.

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My latest blog post, Not All Structures Are Created Equal, at All Analytics.

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Want to get a sense of what a fad looks like? Check out
Big Data News Network. And if are familiar with my argument that instead of leading the industry with science, academia is following industry's fads by substituting vocational training for education, here's an excellent example: 

Announcing a New Master's Degree: Business Analytics 

The department of information systems and the supply chain management department have joined forces to launch an accelerated and specialized master's degree program in the fast growing field of business analytics. The Master of Science in Business Analytics program is full-time, and students will earn their MS in Business Analytics after one academic year. Classes will start in the fall of 2013, a

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Re-write:

• Normalization and Further Normalization Part 1: Databases Representing What
• Normalization and Further Normalization Part 2: If You Need Them, You're Doing It Wrong