Foundations

Foundations Information Commmunication Technicals & Usage.

This is the most technical part. Being enablers there should be no dependicies for business processes.
There are three subtopics:

• 1/ information - computers
• 2/ encryption, communication meaning
• 3/ statistics, data exploration

To go to business processes is by floor operations.
🔰 Too fast .. previous.

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Contents

Reference	Topic	Squad
Intro	Information Commmunication Technicals & Usage.	01.01
newline	Science area´s combined, new .	02.01
IT	Information Technology.	03.01
👓 abacus	Computer & Informmation Technology.	03.xx
ICT	Information Communication Technology.	04.01
👓 enigcod	Understanding meaning computer data.	04.xx
ICU	Information Communication Usage.	05.01
👓 data science	Information usage with a goal.	05.xx
yellow-brick	The yellow brick road.	6.00
	Following steps.	6.02

Progress

• 2020 week:27
  1. Split up in three topics, reviewing content. The split is mirror on other split topics at the business topics side.
  2. Alignment to new CSS style.
• 2019 week:18
  1. Building up new from scratch.
     What is missed in old pages for later to add.

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Science area´s Combined.

Working with machines that process information is a relative new topic of science. The concept of the container "information" is even not clear and simple.
 

Processing Information.

Describing the properties of information (data) in some metadata approach is going back to ancient history philosophers with "Universals" .

"Semiotics" A sign is anything that communicates a meaning, that is not the sign itself, to the interpreter of the sign. The meaning can be intentional such as a word uttered with a specific meaning, or unintentional, such as a symptom being a sign of a particular medical condition. Signs can communicate through any of the senses, visual, auditory, tactile, olfactory, or gustatory. The semiotic tradition explores the study of signs and symbols as a significant part of communications.

There is a sender and receiver of information both parties, sender & receiver, processing in a "Triangle_of_reference" .
 
For a long time there were no machines to support this. The machine for this is called "computer". The first common application usage was computing. In the business mananagement and industrial development there were are develoments on: information (IM Information Management), industrial automatisation and process optimisation.

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Technical Science and management theory combined.

⚖ The technical (math) area´s are:

• Machines and the processing of Information wiht thos (IT)
• Technical communication and the meaning of symbols (ICT)
• Using Information in a more adequate way (ICU)

⚖ The business (bpm) area´s are:

• Information management (IM), who is processing what information / object.
• Technical & administrative processes getting automated (robot).
• Analysing & improving the operations (OR).

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Getting ICT topics more clear understood.

The term elephant test refers to situations in which an idea or thing, "is hard to describe, but instantly recognizable when spotted"
 
Technical and business knowledg of processing information have gone in split worlds but are not possible to exist without each other.

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Information Technology.

The technology using computers has several lines of evolvements. The hardware has become faster, better, cheaper. Application software has a few basic fundaments in logic by flows and constructs. The problem to solve has moved from a pure technical aspect how to run machines into how to process information in a technical way.
 

Technology for machines.

👓 This subtopic did not change conceptual for the last several years. The improvements on what is possible with hardware and software to realise are however still changing fast. The change in speed at communication lines are making is possible to do a lot on far physical distances.

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Technology for logic.

Any process is having a design when it should be adequate, correct, elegant. 👓
Ordering thoughts about the design of a process is having a simple approach by drawings like flowcharts.
The quick & dirty approach of trial and error where failing fast and breaking things is acceptable is only acceptable when the risk assessment does allow it. A functional correct adequate process not only does have to look nice (front end) it should work well (back end).

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Logic Algebra.

"Boolean" algebra has been fundamental in the development of digital electronics, and is provided for in all modern programming languages. It is also used in set theory and statistics.[

Digital logic is the application of the Boolean algebra of 0 and 1 to electronic hardware consisting of logic gates connected to form a circuit diagram. Each gate implements a Boolean operation, and is depicted schematically by a shape indicating the operation. The shapes associated with the gates for conjunction (AND-gates), disjunction (OR-gates), and complement (inverters)

💣 This focus on just two possible outcomes True/False is not what real life is even not what is used and should used in information technology. "Many valued logic" The Priest P3 logic is used in a relational DBMS where undefined is noted as NULL. Not understanding what logic in an information system is applicable will cause unexpected errors when getting used.

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Information Communication Technology.

The change in information processing did not start with machines dong calculations. It did start with using technology to exchange information: communication. Instead of humans used a messenger, using written or just spoken it went to digital with the telegraph .

These systems led to new telegraph codes, starting with the Baudot code. However, telegrams were never able to compete with the letter post on price, and competition from the telephone, which removed their speed advantage, drove the telegraph into decline from 1920 onwards. The few remaining telegraph applications were largely taken over by alternatives on the internet towards the end of the 20th century.

 

Data encoding decoding.

👓 As soon as information was reliable to encode and decode resulting in meaningful information, the question aros how to prevent seeing that by those that should not know that information. The battle of encryption - decryption of information adding an additional layer on the encoding - decoding.
The colossus was an automated machine helping in that information war. It was not a generic computer system.

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Technology fixed and variabel lenght of encoded messages.

In the ease of technical implementations fixed length sizing is prefered. In the ease of text messages variable lengths are prefered. For reliable tecnical data transfer after a number of the same level of signal the opposite level is required. Adding another reversed level signal is quickly adding some length.
💣 Mixing up several conventions can cause un unwanted unclear encoding of information. In a comma seperated file, is the comma part of a digit of it is really segregation of fields.

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Chaotic systems.

Chaos_theory Chaos theory is a branch of mathematics focusing on the study of chaos states of dynamical systems whose apparently-random states of disorder and irregularities are often governed by deterministic laws that are highly sensitive to initial conditions.

💣 The education is focussing on predictable deterministic systems. Assuming when you know all inputs you can predict the outcome with a defined certaintity. This not the truth.

Small differences in initial conditions, such as those due to errors in measurements or due to rounding errors in numerical computation, can yield widely diverging outcomes for such dynamical systems, rendering long-term prediction of their behavior impossible in general. This can happen even though these systems are deterministic, meaning that their future behavior follows a unique evolution and is fully determined by their initial conditions, with no random elements involved. In other words, the deterministic nature of these systems does not make them predictable. This behavior is known as deterministic chaos, or simply chaos. The theory was summarized by Edward Lorenz.

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Information Communication Usage.

Statistics, Operational research. This is nasty topic to understand. Everybody is liking statistics as long as the outcome is not conflicting with the options set in advance. When there are conflicting outcomes it is difficult to analyse whether that result was correct or not.
Going through the assumptions and data being used is hard work, more questionable is whether that activity would be in scope for business management.

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Implementing Technology.

👓 Using technology is realised between strategy (yellow) and operations (dark blue). There are a lot requirements (right side balloons). The user behind the network is getting access through the infra-middleware to their data (information).
This server platform figure is a tactical view with installation configuration generic upper side and evaluation monitoring at the down side.
Decisions should be made supported by measurements into numbers and an explainable number processing (statistics).

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Confused focus area´s.

There is a strange misunderstanding in concepts.

1. When referring to science of information processing than: people are starting to think on just programming languages. That is however a not interesting technology component.
   💣 Issue: Ignoring the process of how information should get understood.
2. When referring to communications for information processing than: people are starting to think on just programming languages.
   🤔 Ignoring the communication, human interaction for decisions.
   😱 Assuming the technical enablement of data exchange in a technical network is all there is what is realy "communications": the information for decisions.
3. When referring to Technology of information processing than: people are going for building databases , program to deliver some numbers and figures.
   🚧 Ignoring the process of how information for decisions should get treated explained and presented while not ignoring all uncertainties and ethical aspects.

❓ Is the Technology Part about Basic Technology or is it about decison maker, imperator.
Without a better understanding on the concepts we are condemned to make the same mistakes over and over again.

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Intra design gates

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The yellow brick road.

Monetizing Data: Follow the Yellow Brick Road
While the tools have vastly improved, and the power of BI buttressed by AI and Machine Learning has helped greatly with incorporating challenges like unstructured and disparate data (internal and external), that Yellow Brick Road journey still requires cultural and operational steps including empowerment of associated teams. There is not a lot of room for autocracy in achieving the best results. Foundational elements work best, and collaboration is a must.

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Idea using automated information decision proprosals.

Explainable AI, better understandable ML Machine Learning, automatic decisions is searched for but lacking.
💡 Proposal in features:
Humans are using multiple sources to evalute what the direction of a decision is going to be. Why is ML stuck by many input sources being input to a single outcome?
Having multiple intermediate (synthetic) leading to more explainable outcomes, combining those to an advice, would be more like human reasoning.

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Following steps.

These are design meta modelling concepts, others:

Switching context to more practice (devops)
Practical Math, 👓 next
bianl Theoretical Math.



Others are operational realisations: 👓
data meta -& security in practice- math
What is not here: 👓 bpm in practice.

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