Saturday, May 11, 2024

TLC: TABLES, DIMENSIONS & RDM



 

I am working on entirely new papers (not re-writes) in the PRACTICAL DATABASE FOUNDATIONS series. I have already published two:

  • THE FIRST NORMAL FORM - A DEFINITIVE GUIDE
  • PRIMARY KEYS - A NEW UNDERSTANDING

available for ordering from the PAPERS, and two more:

  • RELATIONAL DATABASE DOMAINS: A DEFINITIVE GUIDE
  • DATABASE RELATIONS: A DEFINITIVE GUIDE

are in progress and forthcoming, respectively.

In the process, I am coming across industry common and entrenched "pearls" that I am using for my "Setting Matters Straight" (SMS) and "To Laugh or Cry" (TLC) posts on Linkedin. I do those posts to enable the few thinking database professionals left realize how scarce foundation knowledge is, and to illustrate fallacies that abound in the industry, of which they are unaware, and which the papers are intended to dispel.

Time permitting, I may expose and dispel some of those fallacies, treated in more depth in the papers, such that those thinking professionals can test their knowledge and decide whether the papers are a worthy educational investment.

Here's one.

“Data is stored in two-dimensional tables consisting of columns (fields) and rows (records). Multi-dimensional data is represented by a system of relationships among two-dimensional tables.” 

Thursday, May 2, 2024

My April FTD, TLC & SMS LinkedIn Posts



 

 

 

 

SMS: PRIMARY KEYS & INDEXES




I am working on entirely new papers (not re-writes) in the PRACTICAL DATABASE FOUNDATIONS series. I have already published two:

  • THE FIRST NORMAL FORM - A DEFINITIVE GUIDE
  • PRIMARY KEYS - A NEW UNDERSTANDING

available for ordering from the PAPERS page, and two more:

  • RELATIONAL DATABASE DOMAINS: A DEFINITIVE GUIDE
  • DATABASE RELATIONS: A DEFINITIVE GUIDE

are in progress and forthcoming, respectively.

In the process I am coming across industry common and entrenched "pearls" that I am using for my "Setting Matters Straight" (SMS) and "To Laugh or Cry" (TLC) posts on Linkedin. I do those posts to enable the few thinking database professionals left realize how scarce foundation knowledge is, and to illustrate fallacies that abound in the industry, of which they are unaware, and which the papers are intended to dispel.

Time permitting, I may expose and dispell some of those fallacies, treated in more depth in the papers, such that those thinking professionals can test their knowledge and decide whether the papers are a worthy educational investment.

Here's one
:

“There seams to be some confusion between what a Primary Key is, and what an Index is and how they are used. The Primary Key is a logical object. By that I mean that is simply defines a set of properties on one column or a set of columns to require that the columns which make up the primary key are unique and that none of them are null. Because they are unique and not null, these values (or value if your primary key is a single column) can then be used to identify a single row in the table every time. In most if not all database platforms the Primary Key will have an index created on it. An index on the other hand doesn’t define niqueness. An index is used to more quickly find rows in the table based on the values which are part of the index. When you create an index within the database, you are creating a physical object which is being saved to disk.”

 Can you identify the fallacies before you proceed?

Friday, April 5, 2024

TLC: RDM & COMPLEX DATA TYPES



I am working on entirely new papers (not re-writes) in the PRACTICAL DATABASE FOUNDATIONS series. I have already published two:
  • THE FIRST NORMAL FORM - A DEFINITIVE GUIDE
  • PRIMARY KEYS - A NEW UNDERSTANDING
available for ordering from the PAPERS page, and two more:
  • RELATIONAL DATABASE DOMAINS: A DEFINITIVE GUIDE
  • DATABASE RELATIONS: A DEFINITIVE GUIDE
are in progress and forthcoming, respectively.

In the process I am coming across industry common and entrenched "pearls" that I am using for my "Setting Matters Straight" (SMS) and "To Laugh or Cry" (TLC) posts on Linkedin. I do those posts to enable the few thinking database professionals left realize how scarce foundation knowledge is, and to illustrate fallacies that abound in the industry, of which they are unaware, and which the papers are intended to dispel.

Time permitting, I may expose and dispel some of those fallacies (treated in more depth in the papers) in short posts here, such that those thinking professionals can test their knowledge and decide whether the papers are a worthy educational investment.

Here comes the first--a TLC I posted on LinkedIn.


“The company was using a [SQL] RDBMS . . . to handle data transactions for its trading applications. However, the applications required arbitrary data types, which is nearly impossible for relational systems, according to experts.”

 which contains three fallacies--can you identify them before you proceed?

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  •  "SQL RDBMS" is a contradiction in terms. Not only are SQL DBMSs not relational (and, thus, fail to provide RDM's advantages), but--even leaving SQL out--the interpretation (and, thus, understanding, such as it is) of RDM dominant in the industry is flawed. Do you know why, and what are the missed advantages?
  • "Arbitrary data types"--more precisely, domains of arbitrary complexity (not to be confused with SQL built-in types)--are not impossible in RDM properly understood, namely, as coupled with a strong type system: a notion of type hierarchy derived from a theory of types that governs manipulation of domain values, which is orthogonal to RDM, albeit necessary, for support of domains in general, and those so-called "complex" in particular (orthogonal in the sense that the relational data sublanguage is insulated from the implementation of the domains and their operators). Such a type system is incorporated in McGoveran's Semantic-Relational Data Model (SRDM)--the correct interpretation, extension and formalization of Codd's work.
  • As to "experts", I do not know many (to understate the case) in RDM and I assure you that the above statement was not made by any of them.


References

McGoveran, D., LOGIC FOR SERIOUS DATABASE FOLK (draft chapters), forthcoming.
Pascal, F., RELATIONAL DATABASE DOMAINS, forthcoming.

 

 

 

Wednesday, February 7, 2024

NEW PAPER: PRIMARY KEYS - A NEW UNDERSTANDING



 New, completely re-written. Available to order here



Table of Contents

Series Preface

Abstract

Introduction

1. Entities, Properties, Names, and Identification

2. Relational Representation

3. Relational Keys

    3.1. Kinds of Keys

           3.1.1. Candidate, Primary and Alternate Keys

           3.1.2. Natural and Surrogate Keys

4. Formal Primary Key Mandate

5. Primary Key Designation

6. Keys and Constraints

7. Keys and Performance

   7.1. Keys and Indexes

Conclusion

References

Appendix A: Keys in SQL

Appendix B: Duplicates and Consequences

B1. Duplicate Interpretation

B2. Duplicates in SQL

      B2.1. Duplicates and Correctness

      B2.2. Duplicates and Query Nestability

      B2.3. Language Redundancy & Duplicates

      B2.4. Duplicates and Performance Optimization

      B2.5. Duplicate Removal

Monday, February 5, 2024

METALOGICAL PROPERTIES Part 2: Assertion Predicate



In Part 1 we introduced in the conceptual model (CM) the metalogical designation property. It represents—in the absence of known shared defining properties of an entity type, the designation by a group's definer that an entity identifier (aka assigned name) or property value is a member of the group. Such a group is not a group of entities, but a group of name and property values. In the logical model (LM), it is formalized as a designation predicate (DP) and defines a domain.

In Part 2, we introduce the metalogical assertion property. It represents the assertion by an authorized database user that a specific entity, represented by a tuple, either does or does not correspond to an actual entity in the real world.

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