UML Operator Blog

I am currently teaching modelers how to build effective Use Cases and many are struggling with understanding Technology and Data Variations, especially in Enterprise Architecture, Solutioning, and Design. As an Enterprise and Solution Architect for over 23 years, as well as Program and Operations Manager with 40 years of experience, bridging the 'clarity gap' between stakeholders can be a challenge. In today's age of Data, Machine Learning, and Artificial Intelligence (AI), we must close these gaps. We must understand what we mean regarding the "technologies" we use and/or implement, but more importantly we must understand the impacts to our "data" and desired outcomes.  Interested in following? Visit our Website, " TOT Consulting , home of UML Operator" or go to our UML Operator Channel and subscribe. Be sure to turn on Notifications so that you can keep up with our latest videos. Technology Variation "Technology Variation" typicall...

So when, why, and how to start Data Modeling in your project? First off, I am in many projects where non-technical people do not understand their data or even how to document it. There is no reason to "be afraid" of this subject as anyone can do this. Data Modeling in UML does NOT require you are technical, a data architect or developer, or even follow the conventions of data development, management, or documentation. This only requires a basic understanding of your "Modeling Tool" which could be PowerPoint, Visio, Lucidchart, Draw.io or the myriad of offers out there today. The Tools Out of the dozens of "drawing tools" I have used over the decades, I prefer Sparx Enterprise Architect (EA). Sparx EA allows me to draw anything using UML and CASE techniques. In addition, I can put as much intelligence and information under my drawing elements as I want or need, and to continue to update and manage this intelligence. Plus, this intelligence is in a SQL datab...

 I am working with a group of very smart system, application, and business architects. Each group is using different tooling that they are comfortable with.  The Business Architects are using Draw.io,  while the Application Architects are using Visio and Draw.io, and the System Engineers/Architects are now using Sparx EA Most of this Business's Methods and Procedures (M&P) have been using Draw.io to model their M&P, Policies, Rules, and Knowledge Management (KMS) Flows in Draw.io. Then they pass to engineers, architects, and developers for implementations. Their documentation and KMS is very well done. However, there is some confusion and breaks in their knowledge transfer and management, which makes delivery more complicated and slow than it should be. Since ChatGPT did a better job than I in describing Domain Driven Design (DDD), I will use that intelligence below ... Domain-Driven Design (DDD) is an approach to software development that focuses on understanding...

 A good friend and previous co-worker whom I admire and trust, posted on LinkedIn an article, ..." Here's why layoffs keep happening and why ambitious managers are fueling them ". Since LinkedIn doesn't give me enough space to comment, I am here 😀 Good read...however, I have concerns in what I viewed. First off, the author is a "former head of analytics". Why "former"? And should there be more focus on "Advanced Analytics" and not just "Analytics"? Sorry, I don't mean to be disrespectful, but I did not read or see the core reasons why companies fall into this pit. For more on Advanced Analytics vs Analytics, read my post on The Premise of Analytics . Analytics vs Advanced Analytics What is the difference between analytics and advanced analytics? There is a difference between the two, where advanced analytics uses machine learning, data mining, predictive modeling, optimization algorithms, natural language processing, and mo...

The premise of analytics is to leverage data and statistical methods to gain insights and make informed decisions. Analytics involves the systematic analysis of data to uncover patterns, trends, relationships, and other valuable information that can guide decision-making, problem-solving, and optimization. The Premise The premise of analytics can be summarized in the following key points: Data-driven approach : Analytics relies on data as its foundation. It recognizes that organizations generate and collect vast amounts of data from various sources, such as customer transactions, operations, social media, sensors, and more. By analyzing this data, businesses can gain valuable insights to drive strategic decisions and improve performance. Extracting insights : Analytics aims to extract meaningful insights from data. It involves applying statistical techniques, data mining, machine learning, and other analytical methods to identify patterns, trends, correlations, and anomalies within the...

I am starting a series on Modeling Relevance, Telling Stories through Visualization, and basic UML connection practices. This is Part 1 where Part 2 touches on the remainder of association types. The series will dive deeper into building model relevance and using that intelligence to drive other things. More to come...

CASE (Computer-Aided Software Engineering) and UML (Unified Modeling Language) are related but distinct concepts in the field of software engineering. Here's an overview of the differences between CASE and UML: CASE (Computer-Aided Software Engineering): CASE (Computer Aided System/Software Engineering) refers to the use of computer-based tools and methodologies to support various software engineering activities, such as analysis, design, implementation, testing, and maintenance. CASE tools provide software developers with automated support to facilitate the software development process, increase productivity, and improve the quality of the resulting software. CASE tools typically offer a range of features, including graphical modeling capabilities, code generation, documentation generation, project management, version control, and collaboration support. They help in creating, editing, and managing various artifacts and models used during software development, such as requirements ...