The Data-Centric Revolution: Restoring Sanity to Enterprise Information Systems
Shift from application-centric to data-centric to enable your organization to develop more efficient and successful Enterprise Information Systems. This book is the first part of a trilogy to follow Software Wasteland. In Software Wasteland, we detailed the current poor state of application software development. We offered some tactical advice for reducing some of the worse of the excess. This is the first book in the “what to do instead” trilogy.
Software Wasteland: How the Application-Centric Quagmire is Hobbling Our Enterprises
This is the book your Systems Integrator and your Application Software vendor don't want you to read. Enterprise IT (Information Technology) is a $3.8 trillion per year industry worldwide. Most of it is waste. We've grown used to projects costing tens of millions or even billions of dollars, and routinely running over budget and schedule many times over. These overages in both time and money are almost all wasted resources. However, the waste is hard to see, after being so marbled through all the products, processes, and guiding principles. That is what this book is about. We must see, understand, and agree about the problem before we can take coordinated action to address it.
The Silicon Review 2020: Semantic Arts future-proofs the enterprise with data-centric transformation programs
Semantic Arts discovered it’s possible to build an elegant core model of even the most complex enterprise in a limited amount of time (typically less than six months) and with a limited amount of complexity (typically fewer than 500 concepts (classes+ properties). When well implemented, the said model can be extended and specialized in handling specific requirements of subdomains or departments while still staying aligned with the enterprise core as business continues to grow.
CIO Techie Magazine Feature 2019: Big Data Technology Special
"Semantic Arts exists to make the transition to data-centric information systems possible."
99% of all large companies are caught in what we call the “Application-Centric Quagmire,” which is the opposite of being Data-CentricThere is another way. It does not involve implementing yet another application. It is not the next shiny object. It is a discipline, and a different way of thinking about and executing information systems projects. We call it the “Data-Centric Revolution.”
2019 BizWest List: Mercury 100 Fastest-Growing Private Companies in Northern Colorado
BizWest celebrated Semantic Arts as one of Northern Colorado’s fastest growing companies at the 2019 Mercury 100 awards. Companies on the Mercury 100 list are ranked by percentage revenue growth over a two-year period.
Are You Spending Way Too Much on Software?
Strategy + Business
Author and technology consultant Dave McComb on how to curb runaway IT spending.
Semantics in Business Systems
The Savvy Manager's Guide
Semantics in Business Systems begins with a description of what semantics are and how they affect business systems. It examines four main aspects of the application of semantics to systems, specifically: How do we infer meaning from unstructured information, how do application systems make meaning as they operate, how do practitioners uncover meaning in business settings, and how do we understand and communicate what we have deduced? This book illustrates how this applies to the future of application system development, especially how it informs and affects Web services and business rule- based approaches, and how semantics will play out with XML and the semantic Web. The book also contains a quick reference guide to related terms and technologies. It is part of Morgan Kaufmann's series of Savvy Manager's Guides.
Demystifying OWL for the Enterprise
After a slow incubation period of nearly 15 years, a large and growing number of organizations now have one or more projects using the Semantic Web stack of technologies. The Web Ontology Language (OWL) is an essential ingredient in this stack, and the need for ontologists is increasing faster than the number and variety of available resources for learning OWL. This is especially true for the primary target audience for this book: modelers who want to build OWL ontologies for practical use in enterprise and government settings. The purpose of this book is to speed up the process of learning and mastering OWL. To that end, the focus is on the 30% of OWL that gets used 90% of the time.