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A Few 2016 Technology Predictions

In(tegrate) the Clouds

I enjoy the end of the year technology predictions, even though it’s hard to argue with this tweet from Merv Adrian: By 2016, 99% of readers will be utterly sick of predictions. 2016 will be the year of the data lake. In 2016, which software company will be the biggest game-changer for the long term? Does Elon Musk count?

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Cushman & Wakefield builds a foundation for enterprise-wide AI

CIO Business Intelligence

First there was the company’s full embrace of cloud computing, and then a pivot from project management to a product operating model. About a year and a half ago, we moved to a full product operating model. In prior years, we were project-oriented. It appears to be working well. It’s also important to start small, she advises.

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Belcorp reimagines R&D with AI

CIO Business Intelligence

Belcorp operates under a direct sales model in 14 countries. The second stage focused on building algorithms and models to predict and simulate intricate biological conditions, accelerate discoveries, reduce risks, and optimize the cost-benefit ratio of technological developments using AI solutions.

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Key Factors in Choosing Data-Driven Digital Signage Solutions

Smart Data Collective

We talked about this back in 2016 and this trend has only accelerated since. But if you have to break the bank for it, ensure that your ROI is worth it. You will have to decide if a perpetual or Subscription-based model is better suited to your organization’s needs.

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What is TOGAF? An enterprise architecture methodology for business

CIO Business Intelligence

The Open Group developed TOGAF in 1995, and by 2016, 80% of Global 50 companies and 60% of Fortune 500 companies used the framework. TOGAF helps organize the development process through a systematic approach aimed at reducing errors, maintaining timelines, staying on budget, and aligning IT with business units to produce quality results.

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Themes and Conferences per Pacoid, Episode 5

Domino Data Lab

Also, clearly there’s no “one size fits all” educational model for data science. Laura Noren, who runs the Data Science Community Newsletter , presented her NYU postdoc research at JuptyerCon 2018, comparing infrastructure models for data science in research and education. The Berkeley model addresses large university needs in the US.

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Themes and Conferences per Pacoid, Episode 12

Domino Data Lab

Meanwhile, many organizations also struggle with “late in the pipeline issues” on model deployment in production and related compliance. Having participated in several Foo Camps—and even co-chaired the Ed Foo series in 2016-17— most definitely, a Foo will turn your head around. Do those concerns sound familiar?