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How to achieve more effective services - the evidence ecosystem

Google Search itself provides one of the most familiar examples of predictive intelligence. When you enter keywords in the search box, Google predicts what you are interested in and then presents you with results that match that intent. Since it released the first version of its Prediction API in 2010, Google has made some of these methods available to developers. Adoption among developers has not been high because machine learning requires a lot of infrastructure and validation to produce accurate results. Developers have also reported discomfort with basing products on black box APIs.

When managers say they are data driven and ROI focused they are usually more intent on professing a belief than delivering results. They are, essentially, accidental theorists, putting their faith in an abstract idea rather than engaging in any true analysis of cause and effect. Despite what many will tell you, numbers can lie and only fools follow them blindly.

Ensuring that big data creates big value calls for a reskilling effort that is at least as much about fostering a data-driven mindset and analytical culture as it is about adopting new technology. Companies leading the revolution already have an experiment-focused, numerate, data-literate workforce. Are you ready to join them?

Curated website of all things about Big Data, Analytics etc.

Good managers-even great ones-can make spectacularly bad choices. Some of them result from bad luck or poor timing, but a large body of research suggests that many are caused by cognitive and behavioral biases.

How should statisticians be communicating with the media? This meeting explores the relationship between statisticians, journalists and the public, and the statistician's role in providing expert statistical comments on media stories. Speakers present their experiences of working with the media, reflecting on the challenges of communicating statistical ideas for non-technical audiences, whilst preserving the integrity of the story

People who can effectively communicate the results of analytics applications to business executives are becoming big contributors to the analytics teams in some organizations.

Humans are biased, and the biases we encode into machines are then scaled and automated. This is not inherently bad (or good), but it raises the question: how do we operate in a world increasingly consumed with "personal analytics" that can predict race, religion, gender, age, sexual orientation, health status and much more.

Simplify the big data conversation within your organization. Here are 10 priorities to get you started.

Systems of insight are the business discipline and technology to harness insights and turn data into action.

IBM's Watson - the future of machine learning

BM's Watson Artificial Intelligence System is capable of searching across vast repositories of unstructured data and returning answers to natural language queries, but it won't replace humans. Instead, the system will augment humans and help us to make better decisions.

Finding useful knowledge nuggets amongst the torrents of data is a skill in itself. Creating insightful stories that bring the data to life is an emergent skill practiced by data journalists. An excellent article with lots of useful references for anyone who aspires to blend data analytics with storytelling.