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.

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Insight

All agile methodologists share a common foundation: they all believe that delivering iterative demonstrations of real software to real customers provides the shortest and safest path to delivering real value.

Customer collaboration is a cornerstone of agile development, but it is also one of the more difficult aspects of implementing agile. Of course, lack of customer involvement isn't unique to agile development -- software developers have had problems in this area ever since software entered organizational life.

I just attended the Architecture and Design World 2008 conference in Chicago, Illinois, USA. It was an exciting collection of 300-plus architects and designers with an array of about 75 talks that provided a good representation of what's of current interest to software architects and designers.

Microsoft has announced it is acquiring data warehousing appliance specialist DATAllegro, Inc. Microsoft plans to convert DATAllegro's massively parallel processing (MPP) data warehousing appliances to work with the Microsoft SQL Server database.

Increasingly, we're hearing about cloud computing, with a host of companies -- including Amazon, Google, Hewlett-Packard (HP), IBM, Microsoft, Oracle, SAP AG, and Sun -- all promoting it to varying degrees.

Advanced data visualization tools have been around for some time. They first gained a following among scientists and engineers, who used them to build models for fluid-flow analysis, aerodynamic simulation, and other complex applications involving large data sets with many cause-and-effect variables.

Many agile teams do their estimations in abstract measures, such as story points or complexity points, rather than using effort or time. Though the difference is subtle, abstract measures allow a self-adapting estimation process, decrease wish-based planning, and increase realism.

Practically everyone has started down the path toward software-oriented architecture (SOA). Industry surveys show that 80% or more of enterprises have already adopted, or are in the process of adopting, some kind of SOA. We're told we need to for a variety of reasons, although the ones we use are often not the best reasons for us to consider it.