Strategic advice to leverage new technologies
Technology is at the heart of nearly every enterprise, enabling new business models and strategies, and serving as the catalyst to industry convergence. Leveraging the right technology can improve business outcomes, providing intelligence and insights that help you make more informed and accurate decisions. From finding patterns in data through data science, to curating relevant insights with data analytics, to the predictive abilities and innumerable applications of AI, to solving challenging business problems with ML, NLP, and knowledge graphs, technology has brought decision-making to a more intelligent level. Keep pace with the technology trends, opportunities, applications, and real-world use cases that will move your organization closer to its transformation and business goals.
Insight
Time passes quickly. It's hard to imagine that I've been writing Architecture Advisors for three years now. In that time, of course, the world of software development has evolved rapidly, and, as I considered what to write this month, I thought that it might be good to step back and think, very broadly, about the status of software architectures today.
Advisor
Process/Antiprocess
Each year, members of our community present new methods of building and maintaining software. It is our task to be open-minded, learn, and think. We must always look at our people and the product we are building before we decide which process or method to use.
If you are charged with selecting or implementing a customer relationship management (CRM) solution for your organization, it is imperative that you understand the business drivers that propel this application area. The CRM solution space is big and growing.
Software architects at large companies who are focused on the design of enterprise application integration (EAI) systems that can link existing enterprise applications with the latest e-business systems face a horrendous task -- there are so many applications, written in so many different languages, running on such a wide variety of platforms.
"Process improvement challenges -- the process cannot be continuously improved if:
- Sound engineering practices are sacrificed to schedule
- There is no feedback on process performance
- Each person does something different
- Wide variation occurs in performing identical tasks
- Commitment to improve is not organization-wide
CMM [Capability Maturity Model] overcomes these hurdles one by one."
-- Dr. Bill Curtis1
What does the data mean?
"When you make the finding yourself -- even if you're the last person on Earth to see the light -- you'll never forget it."
-- Carl Sagan
A couple of years ago, your boss asked you to lead a software process improvement (SPI) initiative to reduce cycle time and improve quality while still meeting customer commitments to cost and functionality. After you updated your résumé and pondered the impossibility of the mandate, you decided to step up to the challenge (at least until your income tax refund arrived).
Those who know something of my career in computing know that I started as a technology analyst covering the artificial intelligence (AI) market in the early 1980s. More specifically, I wrote Cutter Information Corp.'s Expert Systems Strategies newsletter for almost 10 years.
As companies get swept up in the rush to become an e-business, it's important to remember that distributed computing has been around for a long time. In some cases, a slight change in a technology results in a new name. For example, before 1990, companies selling tools that generated software applications from structured diagrams referred to their products as CASE tools.