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

This week saw an interesting development in which Actuate and Infobright teamed up to offer an open source BI solution that combines the former's open source reporting tools with the latter's open source data warehousing database. This effort is interesting for several reasons.

Recently, a well-known IT advisory group brashly announced a "new" approach to enterprise architecture that it described as "emergent" and "nondeterministic," with central IT and its architects ceding some control and choice to constituents rather than trying to design and control everything.

Many of our business processes -- operating over the Internet or otherwise -- remain wedded to a production-line mindset that is stuck in the world of the 1980s. A well-planned business process managemenht (BPM) and service-oriented architecture (SOA) strategy needs to encourage the use of services as a tool to improve processes and solve specific business problems.

In my previous two Advisors ("Selected Innovations in Cloud Products," 9 September 2009, and "SOA and the Cloud: Getting Past the Hype," 19 August 2009), I talked about the different styles of the cloud (infrastructure as a service [IaaS], platform as a

All the recent talk in the US surrounding proposed healthcare reform has inspired me to take a look at how BI and data warehousing are making an impact on healthcare and medicine. For our international readers who've not been following the healthcare debate in the US, the political discourse has reached a level of circuslike behavior.

The idea of separating an organization's core functionality from its contextual functionality, with the view of concentrating its own resources on what it does best -- the "core" -- and outsourcing what others can do faster, cheaper, and better -- the "context" -- is highly prevalent and well known.

Agile testing is, among other things, about testing early, testing often, and testing smart. How do you achieve that? A combination of actions that can take place in parallel can help you get there. You can start by increasing your QA staff's skills through training (formal or peer-based) so that they are able to not only execute automated tests but also enhance the existing test-code base and create new ones.

Efectuar pruebas de forma agile tiene que ver, entre otras cosas, con probar tempranamente, muchas veces, y astutamente. ¿Como puede lograr eso? Llevando a cabo una serie de acciones en paralelo. Puede comenzar con incrementar el nivel de conocimientos del personal de QA mediante entrenamiento (el cual puede ser formal o mediante compañeros de trabajo) con el fin de que no tan solo puedan ejecutar pruebas automatizadas sino también mejorar el código de pruebas existentes, e inclusive codificar nuevas pruebas.