Thursday, March 5, 2015

Domains, R-tables, and SQL

March blog post @All Analytics:

To ensure sensible results from and correct interpretations of analysis of data from SQL tables or extracts thereof, analysts must know the tables’ interpretation -- the business rules underlying them -- which is rarely documented.

They should be represented in the database by integrity constraints -- not perfect substitutes, because they are very loose approximations to the rules -- but if they are enforced in the database by the DBMS they are usually recorded either in the definition statements that created the tables and constraints, or the database catalog.

Read it all




Sunday, March 1, 2015

First Normal Form, Part 1: Atomicity

Shortly after posting First Normal Form Is Not Structural Regression I received the following email, taking me to task for stating "[Codd's] initial concept was not "single-valuedness", but "atomicity", which was problematic, as it lacks a precise definition."
Contrary to this received wisdom, Codd in 1969/70 (and RM V/2 20 years later) gave a precise relational definition of "atomic" aka "simple" aka "nondecomposable" (later aka non-"compound" aka non-"structured"): not relation-valued. And he gave a precise definition of "normalized": free of relation-valued-domains.
I was referred to an exchange in which the argument is further amplified.

Wednesday, February 25, 2015

SQLSaturday Presentation


March 28, 11:15,  Mountain View

MEANINGLESS, BUT CONSISTENT: DATABASE TRUTH VS. CORRECTNESS


You're a SQL Server ace: your ability to squeeze everything from SQL and your performance tuning skills are unparalleled, but do you know what your tables really mean and, therefore, what queries make sense and whether results are correct and their interpretations sensible? This is a critical part of data fundamentals, the grasp of which is poor. It is a subject usually neither much covered in education, nor part of job requirements and industry dialogue, yet can defeat the entire purpose of your DBMS expertise. This presentation covers
  • Meaning, business rules and table interpretations;
  • Types of business rule; 
  • Meaning and database truth; 
  • Business rules, integrity constraints and database consistency; 
  • DBMS and user reponsibilities.
Session Level: Intermediate

Event full details

Contact: Mark Ginnebaugh  mark@designmind.com




Saturday, February 21, 2015

Weekly Update


1. Quote of the Week
what is an index in database? how can it make the search faster? please help me understanding this. Project Manager Technical
--LinkedIn.com
Note the job title.


2. To Laugh or Cry?
Tableau Data Modeling Resolving Many to Many Relationship

3. Online debunkings
Comments on Codd's Marks are not SQL's NULLs

4. Interesting elsewhere

5. And now for something completely different 

Book:
The Nixon Defense: What He Knew and When He Knew It
The PostWest:
Doesn't have what it takes to survive.
Dirty Wars
And the US has the gal to criticize Israel? At least Israel is defending its immediate existence.

The Arab-Israeli Conflict
Let's give them a state!




Monday, February 16, 2015

Weekly Update


1. Quote of the Week
The most visible limitation of the relational model has been its inability to handle multimedia files, but the importance of this has been overstated. In fact, the relational model has some far more significant limitations that have not yet been challenged:

Every new relational application needs a new set of programs developed from scratch, which is labour-intensive, expensive and wasteful.

Relational applications cannot be readily tailored to the needs of large numbers of individual users, which is an issue for ASPs.

Relational applications cannot record a piece of information about an individual thing that is not relevant to every other thing of the same type. This limits our ability to continually improve customer service levels.

Information about identical things in the real world is structured differently in every relational database, so it is difficult and expensive to amalgamate two databases."
--Simon Williams, The Associative Data Model
2. To Laugh or Cry?

3. Online debunkings

4. Interesting elsewhere
Rare Alan Turing journal shows his genius at work"
It's clear that fundamental logic is at the heart of computer science and everything we do--and in that sense it's clear the whole field owes Turing so very much" ... But in a sense, it also shows how far we've come."
Including away from logic.

5. And now for something completely different

The PostWest:

I guess this makes them experts:

Arab-Israeli Conflict reality check:

Recommended video: The Wall Street Code

Recommended book: Eichmann Before Jerusalem



Sunday, February 15, 2015

The Conceptual-Logical Conflation and the Logical-Physical Confusion (UPDATED)


GE: The future in data modeling is Object Role Modeling (ORM). It is a far superior way to approach data modeling (compared to any record-based methods such as relational) that avoids all the pitfalls of "Table Think" and the necessity of normalization.

Big data or any other kind of data--you still need to know your data and what it represents. That is the myth in big data--that you don't need a schema, i.e., knowledge of what the data means. True you may not need a SQL schema in Oracle, but you do need to know your data. You need to have names for things (that is the vocabulary) and their relationships.