Informatics, Cybernetics, Lean Six Sigma

"If the only tool you have in your toolbox is a hammer, then everything looks like a nail."

Silos can cause problems.  It has been my observation that many, too many, information technology professionals don't know about and therefore do not leverage available tools.  This is problematic.  Also, to me there does not seem to be any sort of "building code" that is being followed for IT systems.

Information technology (IT) involves the practical application of computer systems and software to store, retrieve, transmit (exchange), and modify data.  Tools they use include computer hardware, software applications, programming languages, networking, and data management schemes.  IT is essential for business enterprises to manage their technology infrastructure, keep that infrastructure operating smoothly, keeping things secure, and communicating effectively.

Computer science (CS) involves the study of algorithms, data structures, programming, analyzing data, and the design of computer systems. It encompasses both theoretical and practical aspects of computing. Computer science provides a lot of the tools information technology professionals use to do their job.

Artificial intelligence (AI) involves creating computer-based systems that can perform tasks and processes that typically required human intelligence to perform; replacing that work with a machine.  The business application of artificial intelligence is vast. There are various type of artificial intelligence and the right AI tool needs to be used to perform specific tasks.

Knowledge engineering (KE) is a branch of artificial intelligence that involves integrating human knowledge into computer systems to solve complex problems that normally require human skills and expertise. Knowledge engineering relates to all aspects of knowledge based systems.  Businesses use knowledge engineering to create expert systems that can make decisions, provide recommendations, construct things, and solve problems based on accumulated knowledge available to that business.

Informatics relates to the intersection of information, people, and technology and the practical application of computational systems.  Informatics involves understanding how people will "live" in the digital realm within some specific area of knowledge that makes sense to users of that technology.  Informatics is concerned with the processing, management, and use of information. Businesses use informatics to manage data, improve decision-making, and optimize information systems for better efficiency and productivity.

Cybernetics studies control and communication in systems, whether they are machines, living organisms, or organizations. Cybernetics is the science of dynamic relations (meaning relations changing over time) between the parts of a whole.  Cybernetics deals with things like feedback loops, self-regulation, effective automation, and how systems adapt and function as a business enterprise evolves. In business, cybernetics can be used to design and manage complex organizational systems, ensuring they adapt and respond effectively to changes.

Lean Six Sigma is a set of techniques, principles, and philosophies related to process improvement.  Lean Six Sigma involves systematically removing operational waste, reducing process variation, and managing process quality.

Additional Information:

Comments

Post a Comment

Popular posts from this blog

Relational Knowledge Graph System (RKGS)

Image
Relational Knowledge Graph System (RKGS) is an interesting idea that combines the relational paradigm and the knowledge graph paradigm.  This documentation, Why RKGS , explains the idea. This gets even more interesting with the notion of "relational AI".  RelationalAI is described as follows by the company of the same name, Relational.ai : “RelationalAI is a cloud-based relational knowledge graph management system, with state of the art probabilistic processing and declarative reasoning at scale to make developing Data Applications a superpower for your business.” This notion of knowledge graphs represented in relational databases fits into my belief that knowledge graphs have two aspects: the expression SYNTAX and the logic of what is expressed or SEMANTICS. While the LOGIC of a knowledge graph is always the same regardless of technical syntax used to express that logic; there are many, many different technical syntaxes that can be used to represent a knowledge graph. There
Read more

Getting Started with Auditchain Luca

Image
The Innovator's Dilemma points out that disruptive innovations often look like toys that are doing everything wrong. Auditchain Luca , which is part of the Auditchain Suite , is a unique approach to creating a knowledge graph .  To experience using Auditchain Luca, have a look at the Getting Started with Auditchain Luca instructions. Be sure to grab the Excel and JSON import files used for this getting started exercise.   This getting started exercise uses one of several different approaches to getting information into a tool for constructing and viewing professional quality knowledge graphs .  Additional getting started guides will be made available over time. Auditchain Luca might not make sense to you if you don't understand the paradigm shift that is occurring and if you have not shifted your mental map. For the next step in your journey, consider trying creating a report using a financial reporting scheme template . If you are struggling to figure out how to register or
Read more

Evaluating the Quality of XBRL-based Financial Reports

Image
From the time public companies started submitting XBRL-based financial reports to the U.S. Securities and Exchange Commission, I have been looking at those reports, trying to understand the XBRL-based reports, and trying to figure out how to get them right.  That information was used to figure out how to create software applications that help professional accountants get these reports right. Here is information that summarizes my testing and results which I stopped doing March 31, 2019: Analysis of the high level accounting relationships in the 10-Ks of about 5,716 financial reports  (5,063 public companies, about 89.1% got all these high level accounting relationships consistent with expectation, 623 were inconsistent and manual confirmation revealed the inconsistency was an error) Documentation that helps you understand 26 different types of errors in XBRL-based reports High quality documentation of hundreds of errors in XBRL-based reports submitted by public companies to the SEC Doc
Read more