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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I've face various challenges in my consultancy assignments. Over a decade ago I started to think of EA as a unification framework, which describes the subject of effort spent every day by countless IT professionals.

Testing is potentially a risk-based activity. The fact is, one can't test everything equally, and even if one could, it would be too expensive. The risk-based testing (RBT) approach helps to identify risk factors associated with testing. Various RBT models and approaches available today deal with assessing and calculating risks associated with the test scenarios for a system under test. These studies have described risk calculation for test scenarios by considering various factors from both business and technical perspectives.

Hadoop continues to generate a lot of attention as the Big Data platform for the enterprise. Here are the benefits and obstacles I see that organizations should carefully weigh when considering how they can employ Hadoop.

I am currently writing a series of Executive Updates about the most practical architecture frameworks and how organizations are using them (see "A Practical Guide to the Most Useful Architectural Frameworks: Part I -- The Arc

There is no question that analytics has been undergoing significant upheaval as traditional BI, advanced analytics, and Big Data have come together. As we have pointed out in previous Advisors, recent attention has focused upon the velocity component, and application to real-world processes.

"With any substantial investment in new technology comes the question of value. Is there enough value in the mountain of unstructured social media data to justify the expense and effort of examining it?"

-- Matt Ganis and Avinash Kohirkar, Guest Editors