The movement of applications to the cloud are well underway. With this movement, of course, comes observations both pro & con.

We will cover the good stuff & gotchas - some obvious & some hidden. The upsides of the cloud are pretty well discussed, documented, debated, and advertised. The gotchas, not so much!

We will provide you with a framework to think about both sides of the equation, to allow you to possibly make more informed decisions.

Our EACOE Enterprise Architecture practice looked at security as part of Enterprise Architecture, not as a separate activity.

Starting with this objective is key. In the physical world, look at the Ring doorbell – warn me before someone enters the house, rather than telling me someone is in the house. This comes from REAL Enterprise Architecture. Security is a Business Strategy first - not only an implementation technology concern.

Have you looked at your “smart phone” and its “agility” – your ability to change what you see with a simple press on the screen, and compared it to your internal technology systems or those that you provide to your customers?

This is a manufacturing concept called Mass Customization.

We must realize in information technology solutions, that no matter how quickly we write software, it is handcrafting. We will never be able to meet individual requirements.

You want a roadmap to clearly define what needs to be done to enable your Mission Strategy.

No one wants a series of endless “sprints” not knowing where the goal line is. You want to know what your end-state objective is, how to get there, & how to identify capabilities. No one really wants a set of intellectually entertaining models but to analyze potential mergers or acquisitions of a competitor & determine the degree of “fit”.

That is a Business Outcome Driven Enterprise Architecture.

Major analyst & advisory firms recognize two distinct focus areas in Enterprise Architecture – (1) focus on technology enablement, & (2) focus on facilitating and creating deliverables that guide and inform business decision making – enabling Business Strategy.

We outline what is required & the skill-sets required to bring Business Outcome Driven Enterprise Architecture to your organization. Join the movement to Business Outcome Driven Enterprise Architecture.

Being data driven, achieving digital transformation, developing effective marketing campaigns, making valid business decisions, & ensuring regulatory compliance, are just a few things businesses do, requiring good quality data.

Studies show the low self-reported beliefs on how good the data actually is. Millions of dollars are spent each year on technologies to “clean up” the data organizations are using. It's time to step back & realize that data issue doesn't require technological magic.

What is Enterprise Architecture (EA)? How long has EA been around? How do you cost justify EA? Where should EA reside in the organization? Who is the audience for EA? When do I need to do EA? Why should an organization do EA? What is an EA Framework? What is an EA Methodology? What does EA certification actually mean? What is the background required for a great Enterprise Architect? How do I start?

Most agree that software are a fundamental requirement in today's digital focus & transformations.

What do we really have to understand about software? What should business expectations be about engaging in developing software? Do we need to describe their needs, that are 'transformed' into their described requirements?

We describe 10 things that demystify software development, the business' role in the software development lifecycle, & how to build a true business-technology relationship.

We examine what search engines actually are and the possibilities of what will come next in the future of search. We draw on history for some ideas. Are the issues we are seeing because of bias, privacy, censorship, speed, or accuracy? Or is the real issue money? The short answer is – all of these and more.

Let's think about a library and library science. What makes libraries work? Three things: The Dewey Decimal System, the consistent state of facts in the library, and finally, the librarian.

Artificial Intelligence was first coined by John McCarthy in 1956.

We define what artificial intelligence is, then summarize both positive & negative developments in this field. We suggest there is madness that needs to be addressed, and with not much difficulty.

We have decades of learning about artificial intelligence. But can machines really learn, & who & what are they learning from?

We can't forget the phrase “garbage in, garbage out”? Can we move to “good stuff in, better stuff out”? Yes!