Research

Monetizing Your Data

Sep 20, 2017

Available to Research & Advisory Network Clients Only

With data and analytics leaders focusing energy on improving core operations, it’s easy to overlook the opportunities to monetize a firm’s data in new commercial directions. In this phone briefing, Michael Balsam who covers platforms and data businesses for Outsell, Inc. speaks with research clients about business models, processes, and technologies that can be used to convert internal data assets into new commercial business.

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Transform.AI brought together enterprise and startup CEOs, economists, technologists, venture capitalists, and journalists. We discussed the myths and realities of the economic impact of AI, enterprise applications of AI, the ethical questions surrounding AI, and the state of what’s possible in the field. Here is part three of the highlights.

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Yes, Artificial Intelligence Is Analytics

By Bill Franks, Sep 14, 2017

There seems to be some confusion as to exactly what artificial intelligence (AI) is, and how the discipline of AI should be categorized. Is AI a form of analytics or is it a totally new discipline that is distinct from analytics? I firmly believe that AI is more closely related to predictive analytics and data science than to any other discipline. One might even argue that AI is the next generation of predictive analytics. Additionally, AI is often utilized in situations where it is necessary to operationalize the analytics process. So, in that sense, AI is also often pushing the envelope of prescriptive, operationalized analytics. It would be a mistake to say that AI is not a form of analytics.

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Transform.AI brought together enterprise and startup CEOs, economists, technologists, venture capitalists, and journalists. We discussed the myths and realities of the economic impact of AI, enterprise applications of AI, the ethical questions surrounding AI, and the state of what’s possible in the field. Here is part two of the highlights.

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Inquiry Response: The Bridge Between Internal and External Reporting

By Adam Moore, Sep 11, 2017

Available to Research & Advisory Network Clients Only

Inquiry:

We have an external reporting tool with a certified process and strong governance. Separately, we have management reporting data and analytics data, and for analytics we are standing up a data lake from disparate sources. My challenge is around the external tool and management reporting data. Right now we bridge the management reporting back to the externally reported figures, but I don’t see a need for this tie because the purposes are different. However, senior management has an emotional commitment to the bridge, so I’m wondering if that bridge is really important and whether you are seeing companies diverting from the need to build a bridge.

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Transform.AI brought together enterprise and startup CEOs, economists, technologists, venture capitalists, and journalists. We discussed the myths and realities of the economic impact of AI, enterprise applications of AI, the ethical questions surrounding AI, and the state of what’s possible in the field. Here are some highlights.

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Inquiry Response: Recommendations for Rolling out a new technical solution

By IIA Faculty, Sep 05, 2017

Available to Research & Advisory Network Clients Only

Inquiry:

I’m interested to discuss a topic that I can best describe as ETL (extract, transform, load) as a service that can be deployed for the enterprise. I’m looking to see if other companies have successfully attempted this, and whether there are vendor platforms for this or if this is typically a capability that is built internally.

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“The real issue is that every business is now a tech business – whether it wants to be or not – and that means not just new skills and experiences, but a new outlook on opportunity and strategy.” This quote is from a recent Forbes analysis of the different business models companies can deploy and how each one is performing in the new digital world.

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A Revolution in Analytical Technology

By Thomas H. Davenport, Aug 22, 2017

It’s been 10 years since Jeanne Harris and I published our book, Competing on Analytics, and we’ve just finished updating it for early-fall (2017) re-publication. We realized during this process that there have been a lot of changes in the world of analytics.

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O’Reilly AI Conference NYC 2017: Developments in Artificial Intelligence

By Bill Franks, David Alles, Aug 16, 2017

Available to Research & Advisory Network Clients Only

As we reported in Strata Hadoop World 2017 – Big Data and Analytics Developments from the Heart of Silicon Valley, O’Reilly’s Strata Conference already has a heavy focus on machine learning and AI. What makes O’Reilly AI unique, versus Strata, is its exclusive focus on AI and the inclusion of more cutting-edge AI research topics that have huge potential, but are further from commercialization. The objective for this report is to summarize the common themes and key trends emphasized at O’Reilly AI into an easy-to-read guide that can serve as both a general reference and a resource for planning AI initiatives. With this in mind, the report is organized into seven sections.

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