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
This survey explored interest in and adoption of various relatively new IT technologies in 126 organizations worldwide. Forty-one percent of respondents hold senior management/policymaking or IS/IT management titles, with project management, software engineering/programming, and planning/development being among the other job titles reported. Forty-six percent of responding organizations are headquartered in North America, 18% in Europe, and 27% in Asia/Pacific, with the remainder in the Middle East, South America, and Africa.
Print, film, magnetic, and optical storage media produced about five exabytes1 of new information in 2002. Ninety-two percent of the new information was stored on magnetic media, mostly in hard disks. [6]
Service-oriented architectures (SOA) have moved beyond the hype stage to where organizations are now carrying out their implementation plans. Their goal: increased agility via the ability to configure composite applications -- implemented in the form of services -- in response to changing business conditions and IT requirements. To help make this goal a reality, business rules management systems (BRMSs) are increasingly becoming a part of organizations' SOA implementation plans. Here's why.
Over the past few years, I've written a number of times on the use of business rules management systems (BRMSs) for implementing automated decision making applications. One particular area in which I see BRMSs as having a major impact on organizations' BI and decision support efforts is for enterprise decision management (EDM). Just to make sure we're all on the same page, EDM refers to the application of BRMSs -- sometimes in conjunction with analytic models -- to automate and improve operational decisions across the organization.
There's been a lot of activity in the past few months around SOA standards. For example:
- August -- Open SOA Collaboration group is formed to advance SCA and SDO
- October -- OASIS Reference Model for SOA approved
- December -- The Object Management Group (OMG) begins work on UML Profile and Metamodel for Services
We've discussed SCA, SDO, Open SOA, and OASIS in previous Advisors this year. This week, I'll turn my attention to the UML Profile.
by Martin Bauer
To think that because you employ an agile methodology you don't need to bother with requirements is simply wrong. Regardless of what methodology you choose for development, you need to know what it is you're building before you start building. To do otherwise is asking for trouble.
As organizations carry out their business performance management initiatives, they are increasingly finding it necessary to provide their metrics, scorecards, and other analytics with access to current data from operational systems. The trouble is, the quality of this real-time operational data is suspect. This is because operational data sources rarely go through the rigorous cleansing processes routinely applied to sourced data before it is loaded into the organization's traditional (i.e., ETL-based) data warehouses and data marts.