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Glossary of Digital Terminology for Career Relevance

Rocket-Powered Data Science

7) Security (airports, shopping malls, entertainment & sport events). Autonomous Vehicles: Self-driving (guided without a human), informed by data streaming from many sensors (cameras, radar, LIDAR), and makes decisions and actions based on computer vision algorithms (ML and AI models for people, things, traffic signs,…).

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How Svevia connects roads, risk, and refuse through the cloud

CIO Business Intelligence

Taking out the trash Division Drift has been key to disruptively digitize Svevia’s remit with the help of the internet of things (IoT), data collection, and data analysis. Not for experiments For a company like Svevia, there’s no room for experimentation, underlines Wester. “We

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Ready Players Win: Leaders of the Future Enterprise

CIO Business Intelligence

To outpace these events, CIOs need to leverage resilience capabilities as a competitive advantage. Even the very nature of disruption is evolving, with challenges such as talent gaps and inflationary pressures frequently demanding our immediate attention. Whereas digital transformation in its earliest iteration—digital transformation 1.0—focuses

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Interview with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity

Corinium

Ahead of the Chief Data Analytics Officers & Influencers, Insurance event we caught up with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity to discuss how the industry is evolving. And more recently, we have also seen innovation with IOT (Internet Of Things).

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Amazon Kinesis Data Streams: celebrating a decade of real-time data innovation

AWS Big Data

NHL EDGE technology in the puck and players’ sweaters (jerseys) generate thousands of data points every second for the NHL, which can be analyzed by AWS to predict likely outcomes for key events like face-offs. As more events get captured and streamed, customers want their data streams to scale elastically without any operational overhead.

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Top 10 Data Innovation Trends During 2020

Rocket-Powered Data Science

MLOps takes the modeling, algorithms, and data wrangling out of the experimental “one off” phase and moves the best models into deployment and sustained operational phase. However, it is far from perfect, since it certainly does not have reasoning skills, and it also loses its “train of thought” after several paragraphs (e.g.,

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Themes and Conferences per Pacoid, Episode 9

Domino Data Lab

Several technology conferences all occurred within four fun-filled weeks: Strata SF , Google Next , CMU Summit on US-China Innovation, AI NY , and Strata UK , plus some other events. They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have.