The Road of Moderation

In preparing my presentation on “Enterprise Architecture vs. Collection of Architectures in Enterprise”, I tend to think the relationship of the two is about the balance of the top-down guidance, planning, governance, and coordination with the freedom of organic growth from bottom-up. This also makes me think about the recent financial chaos in the world, which leads to the discussion of the effectiveness and performance in socialist system .vs. capitalist system, where the socialism emphasizes the centralized top down guidance, governance and coordination, while the capitalism emphasizes the organic growth with freedom for individual. After the melting down of the typical socialist system, represented by Soviet Union, by late 90s, now we see the typical capitalist system, represented by United State, is getting into fundamental problems as well.

The Open Group Conference in D.C

This is the first time The Open Group will host a conference in Washington D.C (July 16-20), which is convenient to me. The conference and my presentation info follow:

https://www3.opengroup.org/events/timetable/967

Enterprise Architecture vs. Collection of Architectures in Enterprise

 

Enterprise Architecture (EA) is becoming popular in most private enterprises these days due to the practical needs in this era of IT, after its noticeable fading in public sectors. At this stage, the lessons learned from public sectors could be very helpful to the EA adoption in both public and private sectors in moving forward.

We noticed that there is still no unified answer regarding to what is EA and what should be in it. It is not rare to see that so called “EA” is to use an EA tool and/or an EA repository to collect all type of “architecture” artifacts inside enterprise. These “architecture” artifacts are developed in different timeframes, cover different level of content details, and are created from different perspectives for different purpose. While a real EA should consist of “architecture” artifacts in concert by planning ahead with a designated purpose for each view. The level of details is good enough to convey intent and to serve the purpose, no more and no less.

Training: Shared Service and Cloud Computing Best Practice, Governance, and Lifecycle Management

Day One: Shared Service and Cloud Best Practice with Business and IT Alignment ICE
Build a foundation for Shared Service and Cloud Computing understanding, and provide a practical guidance with comprehensive content coverage and case studies to address the popular issues and confusions during practice.

Day Two: Shared Service Governance and Lifecycle Management

Provide a comprehensive coverage in governance concept, model, content, as well as the governance practice references for shared service and cloud computing. It’ll demonstrate how service lifecycle can be managed effectively with the help of shared service governance practice. Also, it’ll demonstrate how shared service practice can be evolved towards higher maturity with a roadmap. Finally, we’ll discuss where shared service and cloud computing are heading to.

More details can be found at: http://architechllc.com/4122.html

Inter-Enterprise Architecture for Shared Service, Cloud, and Interoperability

With Internet business model grows beyond enterprise boundaries, such as service outsourcing, public cloud, and interoperation of business partnerships, the architectures for these extended enterprises seem necessary. My recent discussion with folks working with The Office of the National Coordinator for Health Information Technology (ONC) and on the Federal Health Architecture (FHA) reveals such real needs for the Inter-Enterprise Architecture, which I’ve introduced earlier in this blog and in the San Diego Open Group Conference 2011. I hope more efforts will happen in this arena. The ArchiTech Group LLC is definitely well positioned for such service. A short paper can be found here:  http://architechllc.com/4122.html

A Different Perspective for Information and Data Management

Information and data management is getting more challenging these days, with the velocity of data we are producing and the tendency of increased data production. However, I think the key for the solution is beyond information and data management. It is about how and what data should be collected.

I still remembered the raw data collection from web sites for data preservation. The amount of data growing makes me wonder even we can store them, how we can catch up in processing them to make them meaningful, e.g. to transform the data into information, let alone transform information into useful knowledge. If data processing speeds continue lag behind data collection speeds, the data collected will not be useful, but add burden to the slow process. If more meaningless data involved, it’ll add more burden to the process. Therefore, we need to improve the data collection process, to collect the data with purpose, e.g. a Service Oriented Data Collection and Management Process, and collect the data cleanly.