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

A reader asked me to name the major goals and benefits that organizations should seek to obtain by implementing business performance management initiatives. I've recorded my thoughts in this Advisor.

In my last Advisor (see "Summer Reading: Blink, Mirror Neurons, Antonio Damasio, David Gelernter, and Real Intelligence," 5 July 2007), I talked about Malcolm Gladwell's book Blink and how it got me thinking about how experts often know something is wrong in an instant, like when a big project is probably

If you're heard of UML, then you've probably heard comments that it is big, unruly, and complicated, and that things are even worse with UML 2.0. Although I don't necessarily agree with the sentiment, I can understand where it's coming from. UML is a general-purpose modeling language, directed at IT systems. Well, IT systems are a big topic area.

The latest acquisition to affect the data warehousing/BI market is IBM's announcement that it is buying real-time data integration specialist DataMirror Corporation for approximately US $161 million.

I work with a lot of database and data warehouse practitioners who have a hard time seeing how agile software development practices can be adapted to the complexities of data-centric systems integration and development. Large data volumes, integration of commercial software, disparate systems integration, and so on, make this adaptation a challenging one.

If it hasn't happened already, eventually your organization is likely going to be faced with the question: should we use advertising-supported business software?

Since the term "Web 2.0" started appearing, the key questions that seem to keep coming back are: What does it mean? What is the relevance to the enterprise? Should we fear it?

As I recently helped update my company's knowledge management strategy (our business vitally depends on the effective transfer of knowledge from experts to novices, but then, what business doesn't?), I realized that leveraging Web 2.0 in the enterprise meant relinquishing traditional control mechanisms over the editing and publishing of corporate knowledge.

Companies are starting to direct their attention at how they can better facilitate collaboration among their BI users using so-called Web 2.0 technologies such as instant messaging (IM), wikis, and blogs.