Research

Teradata Goes “All In” On Cloud

By David Alles, Sep 22, 2016

I recently attended my first Teradata Partners Conference, where we hosted a booth at the Teradata Partners Expo Hall. Teradata has been an underwriter of IIA since our inception in 2010. It was a great conference as well as an excellent opportunity for IIA to interact with other analytics professionals. Attendees who visited our booth were excited about the show and enthusiastic about the data and analytics work they are doing at their respective companies.

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Inquiry Response: AI and Cognitive Computing Systems in Financial Services

By Kris Hammond, Sep 20, 2016

Available to Research & Advisory Network Clients Only

An IIA client from the Finance industry was interested in how AI and Cognitive Computing are influencing the Financial and Investment Industries.

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Breaking Analytics Out Of The Box - Literally

By Bill Franks, Sep 08, 2016

The lines between open source and commercial products are blurring rapidly as our options for building and executing analytics grow by the day. The range of options and price points available today enable anyone from a large enterprise to a single researcher to gain access to affordable, powerful analytic tools and infrastructure. As a result, analytics will continue to become more pervasive and more impactful.

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inquiry response: Key Components of an Enterprise Data Strategy

By Mike Lampa, Sep 07, 2016

Available to Research & Advisory Network Clients and Professional Members

A health insurance client was initiating an enterprise data strategy and looking to frame out the key components of that strategy. In this exchange, the client asked how to identify where the current resource/skills gaps are, the next steps to fill those gaps, and what are best practices for beginning this process.

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At IIA, we spend most of our time helping enterprises build, sustain and measure their enterprise analytics capabilities. But, we are always on the lookout for standout players who combine technology and analytics for good in their communities.

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Analytics in the Cloud

By Marc Clark, Daniel Magestro, Jul 28, 2016

Available to Research & Advisory Network Clients Only

As companies consider incorporating enterprise-level cloud services offered by Amazon, Microsoft, Teradata, and others, many challenges arise related to data security, integration into existing data architectures, and analytics activities themselves. Marc Clark, Teradata’s Director of Cloud Strategy and Deployment, and Dan Magestro, IIA Research Director, discuss these and other considerations for evaluating and adopting a cloud strategy for your enterprise, and what it means for analytics.

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How to Help Humans Work Better With Smart Machines

By Thomas H. Davenport, May 25, 2016

Perhaps the most important leadership issue is preparing your employees for roles in which they augment smart machines, and vice-versa. There will be new jobs involving implementation and oversight of these technologies—getting them installed, monitoring their daily performance, and improving them over time. Employees with some aptitude need to be groomed for such roles.

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Stronger Cybersecurity Starts with Data Management

By Christopher Smith, Evan Levy, Robert Morison, May 25, 2016

Available to Research & Advisory Network Clients Only

A paradigm shift is underway in the cybersecurity industry. Cybersecurity professionals are moving from a focus on attacker prevention to attacker detection. Preventing the “bad guys” from getting in is still important, but cyber adversaries are increasingly able to bypass even the most sophisticated network defenses. Once inside, it is more important than ever to find these attackers fast, before their activities get buried in the daily volume and pulse of network communications. This is where security analytics holds promise. Security analytics provides the necessary and timely visibility into normal and abnormal network behavior.

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How artificial intelligence explains analytics

By Kris Hammond, May 19, 2016

No one would ever work with a person that just spits out answers and then walks away. Why would we expect people to work with intelligent machines that do any less?

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We’re all generating a lot of data about ourselves and how we live day to day. There are personal fitness devices, preferences and opinions expressed on social media, details on when we’ve come and gone from the house from our security systems, and more. It isn’t just data that companies are collecting from us, but data that we are directly generating ourselves. What should we be willing to do with it and at what price?

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