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As told by C. J. Date, sometime shortly after the introduction of SQL DBMS's in the industry, when non-relational products e.g. hierarchic and network reigned and the relational idea was a very hard sell, he and Michael Stonebraker (the author of Ingres and at the time a professor of Computer Science at University of California Berkeley) participated in a panel at a technical conference. The following is the (praphrased) exchange between them:

CJD: The reality is that most practitioners are too set in their non-relational ways and we cannot expect them to understand and appreciate the relational model. Rather, we must focus on the young generation of practitioners, who learn the relational model at university.

MS: Chris, you don't understand. I am teaching those youths: they were not around when we struggled with the huge problems of the pre-relational systems and they are reinventing all of them!

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1. Quote of the Week

Now that we have seen a lot of information about NoSQL databases, it is interesting to drop back and look around at how much NoSQL stuff we already have in our organizations. I had never thought of a file system as a database, but it is. The comparison is fascinating. File systems don’t impose any structure on the data that is stored in any given file. There is a key value relationship to each file. There is little control over concurrency beyond file locking. This is very similar to NoSQL, with locking only at the aggregate level. File systems are cheap; everyone has one and they hold huge amounts of data on multiple nodes. --Book review, NoCOUG Journal

2. To Laugh or Cry?

Find GUID in Database

3. Online exchanges

• Consistency...when do you truly need it?
• Is there any difference between Fortress Model and Data Model?
• Which is better practice Composite Key vs Surrogate Key?
• Big data 5nf-fifth normal form
• How to model ternary associative entity with a binary constraint?

4. Interesting elsewhere (corrected first link and added a second):

• CREATE ASSERTION Impossible Dream (by Erwin Smout)
• Why ASSERTIONs Are Important (by Toon Koppelaars)

5. And now for something completely different

Joe Biden wants to nominate Obama for sainthood

The VP of the world's "superpower".

Stanford opening new lab to study bad science

And tomorrow we'll need a lab to study bad science in the study of bad science.

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In What the $&@#^ is Applied Big Data, venture capitalist Greg Sands raises an issue about which I as a scientist (and not just a "data scientist") have often expressed concern. 

"The world is awash in data. Figuring out what to do with it is the problem. The press is littered with reports about Big Data. Many CIOs report that their CEOs have come to them and said, “We need some of that Big Data.” That often means make sure we’re collecting all the available data, often deploying a new Hadoop-based infrastructure to store and analyze it. After this elaborate process and extensive investment, they’ll start mining to figure out if there are critical insights that come out of the data. We see many entrepreneurs that start the same way. Aggregate data and look for a problem."

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In a LinkedIn exchange I argued that an optimal generality-to-simplicity ratio (ability to represent a maximal range of reality with minimal complexity) and a 1:1 correspondence between informal business modeling constructs and formal logical database constructs are beneficial. And I claimed that insofar as data models that are formally defined are concerned, the relational model scores best on both.

One of the responses I got was

GE: Though I might come up with slightly different lists, in general, I agree with your expression of criteria for selecting a primary key and of generality and simplicity, but disagree with your conclusion that "RM scores better than any other modeling scheme."

Let me take his points one by one.

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Note: I usually receive notifications of comments to my posts, which I then publish if they are not spam. Today, however, I noticed a whole bunch of old comments that were waiting for moderation, some of 2013, of which I was not notified. I have just published them and replied. Apologies to the commenters.

1. Quote of the Week

Schemaless describes the storage engine, not the data. Data has schema. No Data is ever Schemaless. Schemaless DBs merely describe a feature of themselves, not the data they store. Namely that they don't store and enforce this schema in addition to the data.
One advantage of this Is that you can change the schema "easily" - helps with up time. Now if you don't evolve the old data with each schema change you can end up with multiple schemas stored in your backend and no way of knowing which data is of which schema without some form of analysis of the data. Show me the Front end that can deal with evolving schemas without knowing about them ;) Point being Schema's always there wether any tier deals with it explicitly or not. Something has to manage it. --LinkedIn.com

2. To Laugh or Cry?

Big data means the reign of the relational database is over

3. Online

What is the best way to explain Normalization 1NF,2NF and 3NF

4. And now for something completely different

Samsung’s entire leadership team is paid less than individual executives at Google, Apple

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Note: This is a 11/06/17 revision. Thanks to Erwin Smout for his review of a draft and suggesting improvements.

The claims that (1) the relational data model (RDM) is old and, by implication, obsolete -- the industry has purportedly "progressed" -- and (2) promoting it as a superior alternative to NoSQL, Hadoop and other "modern" data management technologies is "religious" in character are routine. They have popped again in a LinkedIn exchange and I responded as I usually do, by asking why is the promotion of a scientific approach deemed religious, while pushing ad-hoc alternatives is not?

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1. My presentation at SQLSaturday:

The Last NULL in the Coffin: A Relational 2VL Solution to Missing Data
March 15, 2014 11:15am
Microsoft Technology Center, 1065 La Avenida, Building One, Mountain View, CA, 94043

2. Descriptions of all available courses are now posted on the SEMINARS page. Contact me if you are interested in public or private sessions, with possible customization for particular needs.

3. Quote of the Week

1: - a picture is only one representation of a data model: What is the adequate data structure to store a data model: Picture, Text (UML), formal (Gellish), Database) - is there an API to access, create and manipulate data models - do you handle hundreds of types (Entity, Relationship, Attribute): - do you handle one conceptual data model and derived consistent (external) submodels - document : which meta-attributes must be maintained to describe the elements of the data model. How to create different views of the data model (Pictures with different views, detailed printed documents)
2: - How to check the data model with instance data and queries based on the requirements.
3. - Use the ER-Model for Instance data (instead of the relational model) and thereby avoid the impedance mismatch:
4: A query language to access instance data which is based on the Entity-Relationship-Model and NOT on the relational model" --LinkedIn.com

Ugh!

4. To Laugh or Cry?

mysql - additional information on normalization 

5. Online

Do you use Composite Primary Keys to design a good, solid data model?

6. Elsewhere

http://image-store.slidesharecdn.com/a606a81e-9bd4-11e3-8016-22000a9aa8cc-large.png

The database field.

7. And now for something completely different

Zombie Studies Gain Ground on College Campuses