Design: Business Design Dimensions

business-design-dimensions

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In my previous post I was thinking about the fundamental components of a business.  Now I want to think about the fundamental contexts and the four dimensions of each context.

Over the next few posts I will be exploring each of these contexts and dimensions.  Personally, I think current data warehouse design is a load of bullshit.  Relational business intelligence is an oxymoron.

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The Brain: ZenUniverse 2.0

zencircle011

“Tao can Tao not Tao”

Lao Tzu

If you have seen ZenUniverse 1.o and liked it.  You will be pleased to know that I have made some major enhancements to this concept.  We will still have the Six Solids, but we will expand considerably on the classifications.

In this version I will incorporate my work describing the six areas of human endeavor:

  1. Astrics
  2. Physics
  3. Archics
  4. Chemics
  5. Bionics
  6. Datics

Then I will correlate them with the Brain’s major regions.

The ordering of everything is very deliberate.

I am not going to belabor you with commentary.

Simply scroll up and down through the tables and think about the correlations and the model of the brain at the end of this post.

So, without further adieu:

Zen Astrics

These are the kinds of theories that can exist.

You might notice the number of sides for each seems large.

What has been overlooked is solids have an outside, midside and inside.

zenarts500

Zen Physics

These are the kinds of space that can exist.

zensciences500

Zen Archics

These are the kinds of arts that can exist.

zendesign500

Zen Chemics

These are the kinds of natures that can exist.

zenmechanics500

Zen Bionics

These are the kinds of skills that can exist.

zenskills500

Zen Datics

These are the kinds of numeracy and literacy.

zendisciplines500

Zen Brain

Each of the above areas of endeavor correlate with the representation of the brain in the fundamental table below.

zenuniverse5009

  1. GREEN: EYE: OCCIPITAL LOBE: visual center of the brain
  2. YELLOW: EAR: TEMPORAL LOBE: sensory center of hearing in the brain.
  3. SKY: NOSE: BRAINSTEM: control of reflexes and such essential internal mechanisms as respiration and heartbeat.
  4. BLUE: TONGUE: PARIETAL LOBE: Complex sensory information from the body is processed in the parietal lobe, which also controls the ability to understand language.
  5. RED: JAW: FRONTAL LOBE: control of skilled motor activity, including speech, mood and the ability to think.
  6. ORANGE: BODY: CEREBELLUM: regulation and coordination of complex voluntary muscular movement as well as the maintenance of posture and balance.

Summary

zenuniverse2_5001

Hope there was food for thought.

Links:

Databases: Structured Associative Model

oraclesentences

For years now I have been struggling with Relational DBMS technology and Associative DBMS technology attempting to get them to do what I want.  In my first efforts, Relational models were structurally restrictive, Dimensional models were unable to grow organically, EAV models are incompatible with relational architecture.  I came upon Simon Williams Associative Model of Data and although enthralled with its potential I found it too had limitations.  It was semi-structured and allowed for too much flexibility.  25 years in Information Technology had taught me that there was a single standard classification system for setting up databases not a plethora of ontologies.  I was determined to find the theoretical structure and was not concerned with hardware limitations, database architecture, abilties of current query languages or any other constraints.

The Associative Model of Data had made the difference in liberating me from Relational and Dimensional thinking.  A traditional ERD of the Associative Model of Data I at first thought would look like the following:

amdschema

Basically what you have is a Schema composed of Nodes with Node Associations through Verbs and Associations with Nodes Attributions through Verbs. The range of Node Entities, Verb Entities, Association Entities and Attribution Entities are endless.  As well the population of the Schema has an unlimited dataset of natural key values.  I have been challenged by Relational database specialists and SQL experts regarding the viability of this model within current limitations, however their arguments are irrelevant.  What is important is the logical validity of the model, not the physical validity.

After receiving the criticism I decided to revisit the model in order to simplify it.  I went over Simon William’s explanations of his model and its application and found I could reduce it to the following:

amdschema02

This was profoundly simpler and better reflected the Associative Model of Data’s Architecture.  But even with this simpler architecture I was not satisfied.  I felt that the Associatve Model although giving the benefit of explicitly defining the associations was a tabula rasa.  Research has shown that tabula rasa’s are contrary to the behavior of the finite physical universe.  There is an intermediate level of nature and nuture.  And this is what I sought to model.

zachman

When I first encountered the Zachman Framework, something about it struck me in a very profound way.  I could see there was something fundamental in its description of systems, however I felt that the metaphors that John Zachman used were wrong because they themselves lacked a fundamental simplicity.  The consequences of this were that those who studied under Zachman ultimately could not agree on what he was talking about.  Also the “disciplines” that Zachman’s Framework generated were continually reinventing the wheel.  Zachman had created a world of vertical and horizontal stovepipes.  To further the confusion Zachman refused to conceive of a methodology based upon his framework.  Consequently, there was no way to determine what the priorities were in creating a system.  I call this the Zachman Clusterfuck.

Zachman’s work spawned years of work for me.  I could see that systems had a fundamental structure, but I could not agree with Zachman.  Focuses and Perspectives were useless terms.  The construction metaphor was useless.  I read anything I could get my hands on dealing with systems, methodologies, modeling, networks and a broad range of other literature across the disciplines.  Out of this came a set of conclusions:

  1. There were a fundamental set of Noun Entities
  2. There were a fundamental set of Verb Entities
  3. There were a fundamental set of Association Entities
  4. There was a clear order in which the Nouns were addressed
  5. There was a clear order in which the Verbs were executed
  6. The structure was fractal
  7. The content was a scale-free network

I made some attempts at creating the vocabulary and experimented with this new Structured Thinking Language.  However, the real break came when I worked with John Boyd’s OODA Loop:

theboydpyramid

The OODA Loop revealed a governing structure for the methodology and guided my way into the following hybrid relational/dimensional/associational model I call the Structured Associative Model of Data:

samd

One of the key things this model demonstrates is the sequence followed by the OODA Loop.  Starting from the top, each dimension set spawns the next.  Choices are created from the dimensions.  There is no centrism to this model which is an inherent flaw in Service Oriented Architecture (SOA), Event based architecture, Data centric architecture, Goal-Directed Design, Rule based systems among others.  The stove pipes of Focuses and Pespectives disappear by reasserting a clear order of priorities and dependencies for achieving success.  The model also supports bottom up inductive as well as top down deductive sequencing.  This will make the system able to reconfigure to handle exceptions.

Some of the things I have learned in designing this model include the realization that unit defines datatype and that all measures are variable character string text.  This is because any displayed value is only a symbolic representation of the actual quantity.  If operations are to be performed on measures they are converted to the correct type as part of the operation.  I also recognized that Unit was necessary to define the scale and scalability of the system.  Further, it became apparent that analog calculations should not be practiced.  Every value should be treated as discrete and aggregated.

Another aspect of this system is the inclusion of currency and amount.  I have been critical of Zachman and academics for their hypocrisy regarding the economics of systems.  All systems have a cost and a benefit and they are measurable in currency.  Contrary to the reasoning of the majority, every decision is ultimately economic.

Tim Brown of IDEO has coined the term “Design Thinking” and has been toying with the concept for some time.  Many designers dwell on the two dimensional concept of divergence and convergence as modes of thought.  If we look at my model, divergence is the creation of choice while convergence is selection of choice.  There is no alteration or deletion of choice in my model as history is preserved.

Now what you have is a unencumbered framework with a clear methodological sequence.

czerepakcognitary

Welcome to the Cognitary Universe.

Universe: Interrogative Spaces

iconuniverse14

In my previous post I gave thought to Tim Brown of IDEO’s “design thinking”, Clayton Christensen’s “Innovator’s Dilemma”, Malcolm Gladwell’s “Tipping Point”, and Buckminster Fuller’s “Synergetics” concepts.  What emerged was the above Czerepak Framework.  My claim is this framework is fundamental to designing a system.

The thing that the above table shows is interaction within what I am now going to call the “Interrogative Spaces”: HowSpace, WhatSpace, WhySpace, WhoSpace, WhenSpace, WhereSpace, HowMuchSpace, HowManySpace.  Each ellipse I call a “vortice”.  The Interrogative Spaces are composed of one or more vortices.  The Framework above shows how Spaces are composed within the Interrogatives,  but what about interactions between the Interrogative Spaces?   A good example is speed or velocity.  Speed is the intersection of WhenSpace and WhereSpace:

v = r / t

Where v is velocity, r is radius and t is time.

If you are increasing Speed, which is acceleration, you have one dimension of WhereSpace and two dimensions of WhenSpace:

a = r / t’ * t”

Where a is acceleration, r is radius, t’ is the first clock and t” is the second clock.  You cannot measure acceleration with one clock. This uniqueness of every vortice applies to all the Interrogative Spaces and all inter-relationships between all of the Spaces.  .

Another way to look at the Interrogative Spaces is as sets and subsets.  The first row are the complete Space vortice sets.  The second row are the first Space vortice subsets.  The third row is the intersect between the row two and row three Space vortice subsets. And the fourth row are the intersects between the row two and row three and row four Space vortice subsets.

I do not believe that anything is constant.  Not the speed of light, not gravity, not cosmology.  Every intersection of dimensions creates a vortex in Universe and every one is unique.  We are simply unable to measure and manage the uniqueness of everything, therefore we make generalizations which create models that can always be falsified.

Physics: Within and Without the Box

I have been reading extensively about the thought experiment, called Schrödinger’s Cat, and have reached a personal conclusion that it is inherently flawed by its idealism.  There is no case where any object inside “the box” can be fully shielded from decoherence.  There is no example of this in nature.  Every case for the validity of the experiment is baseless.  Interestingly enough, this is what Schrödinger was out to demonstrate and with which Einstein agreed.  What hadn’t been explored at the time was entanglement can be explained simply by additional dimensions.

Links:

Atomic Tunneling

Garrett Lisi on his theory of everything

I agree with Garrett Lisi. It’s sets and geometry.

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The Lie E8 is a beautiful structure mathematically with 248 dimensions:

However, I think what he wants to achieve is even simpler to model physically.

This is a 3V Icosahedron Geodesate:

This structure gives us 92 vertexes (entities) and 270 edges (associations) or 362 particles.

Employing Occam’s Razor, I suggest that some form of Icosahedron Geodesate theory is more likely the answer.