Follow @DBDebunk Follow @ThePostWest


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?

• Rise of the Multi-Model Database
• 42% of Database Pros Struggle to Manage NoSQL Solutions

3. Online debunkings

• Alternate Keys, Normal Form question
• With large hacks, how should we change database design

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

Follow @DBDebunk Follow @ThePostWest

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.

Follow @DBDebunk Follow @ThePostWest


1. Quote of the Week

I was wondering what people were using and what people would recommend as a good data modelling application? I guess I want to do two things - one reverse engineer existing databases into an ER diagram, as well as start from scratch and design a new conceptual/logical/physical data model. Any suggestions?
--LinkedIn.com

2. To Laugh or Cry?

Just Give Me the Factless Facts, Ma'am

3. Online

42% of Database Specialists Struggle to Manage NoSQL Solutions

4. Elsewhere

Test shows big data text analysis inconsistent, inaccurate

5. And now for something completely different

Follow @DBDebunk Follow @ThePostWest

See series starting at

The First Normal Form in Theory and Practice Part I

Follow @DBDebunk Follow @ThePostWest


1. Quote of the Week

I like a GUID as a primary key on every table so that I can uniquely identify that row. For consistency I'll call it "UID" and defined as a NewSequentialID. I'm aware of the various discussions that have been had regarding Guids vs sequences vs COMB etc., etc., but for me any performance issues have occurred in the size of databases I've worked with. The ability to create a new UID as part of an insert is of huge benefit to reduce round trips if you're handling that kind of thing from within a business layer outside of the database server. --LinkedIn.com

2. To Laugh or Cry?

Data Principles

3. Online debunkings

Comments on Relational Fidelity & Analytics Integrity
Comments on Data Model: Neither Conceptual, Nor Logical, Nor Physical Model

4. Elsewhere

Thou shalt not commit logical fallacies

5. And now for something completely different

Follow @DBDebunk Follow @ThePostWest


1. Quote of the Week

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. --LinkedIn.com

2. To Laugh or Cry?

Types of database management system and their evolution

3. Online debunkings

• Comments on Relational Fidelity & Analytics Integrity
• Comments on June post @All Analytics

4. Elsewhere

Big Data is Dead!

5. And now for something completely different

Follow @DBDebunk Follow @ThePostWest


"To Laugh or Cry?" Test Your Foundation Knowledge

Tuesday, January 20, 2015 6:30 PM

Microsoft
1065 La Avenida
Building 1
Mountain View, CA  (map)

RSVP here
 


You are a DBMS ace, able to squeeze every ounce of performance out of it. But how about your foundation knowledge, how good a grasp of data fundamentals do you possess? Are you a data management ace too?

The two are distinct and while the former is necessary for a career, it is insufficient for an informed, intelligent, reliable and productive data management practice. The industry is full of myths, misconceptions and traps and without foundation knowledge you are unable to see through them.

This is your opportunity to test yourself. If your instinct is neither to laugh, nor to cry at the contents of this presentation, education may be in order.

• How misconceptions that you are unaware of, lead you astray;
• Practical implications thereof;
• How foundation knowledge, scarce in the industry, is the only way to see through them.