I have been writing over the last month or so about how the adoption of SOA is evolving in organizations and that in most cases tactical deployment is occuring by individual business domain driving the need for a "Right-sized" federated SOA which segments and connects an enterprise architecture through appropriately targeted layers of technology.
Classic architecture considerations never seem to pass up a generation. The classic debate of whether it is better to buy and implement an "all-in-one" SOA stack from one vendor or to embark on a "best-of-breed" strategy where specific vendors and technology are selected for specific capabilities is a regular discussion I find myself particpating in often.
My last couple posts have touched on the importance of data standards in enabling interoperability in healthcare. It is important to recognize, however, that data standardization is not about dictating the way organizations capture and share clinical data.
There has been much written and discussed about the technology advantages and business value of multi-core computing. At Oracle Open World last week, Intel's CEO provided several compelling examples of how multi-core computing can improve business outcomes, save dollars, and even potentially save lives.
In my last post I looked under the hood at data interoperability, examining the need for the normalization of both "syntactic" and "semantic" aspects of healthcare data. In this post I will present a high-level architecture for data normalization to share some understanding of how health information exchange is implemented in practice.
I went to the InfoWorld SOA Executive forum held in New York this week. The theme of the conference was "Realizing the value of SOA". There were several well delivered presentations on the importance of understanding business process first, organizing the right team skills and structure and picking the right early projects in order to crawl, walk and then run with SOA. Without a disciplined approach focused on these basics any technology selection is doomed to either fai
Data interoperability is vital to today’s healthcare computing environment, allowing clinical information to be effectively and consistently exchanged, compared, and analyzed among healthcare partners such as insurers, pharmacies, affiliated providers, and public health departments. Put simply, data interoperability enables better decision making.
"Time is money". That old saying is as relevant as ever in the modern financial service markets. Complex, real-time, and algorithmic trading are constantly pushing the envelope of that phase.