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
The Object Management Group (OMG) announced its new Model Driven Architecture (MDA) in March of this year. Recognizing that middleware standards proliferated in the 1990s, and seeking to widen its appeal to all those involved in designing robust distributed systems, the group is extending its original Object Management Architecture.
We recently spoke with Cutter Consortium Senior Consultant Brad Kain, who just completed a project in which he integrated a new system with a legacy system. We discussed the challenges the client faced and the business problems it needed to solve.
Cutter Consortium (CC): Who was the client for this project, and what was the business problem it faced?
In September and October, I reported on the findings of a Cutter Consortium e-business survey. I addressed the commitment companies have to e-business (Executive Update, Vol. 4, No. 18); the types of applications being developed (Executive Update, Vol. 4, No.
As organizations are feeling pressure from the oscillating economic climate, changing government regulations, new customer demands, and high employee turnover, they are grasping at technology solutions to halt their steady loss of business knowledge -- business knowledge that was never complete or comprehensive in the first place.
A purported 60%-70% of business intelligence (BI) applications fail. The root causes for these failures are not related to the technology but to organizational, cultural, and infrastructure issues.
Over the past decades, organ-izations have adopted some unsound habits, which have produced disparate silo decision support systems with a great number of impairments.
Web data analysis has received considerable attention in the general computing and IT trade press, and it is frequently cited by business intelligence (BI) tool vendors as an application area for the use of their products.
The notion of a "postmortem" is familiar to most software developers and project managers: at the end of an application development project, a report is written to document the good, the bad, and the ugly experiences, so that future projects can learn and improve. In theory, it's a useful concept; in practice, it's largely ignored.