Dataconomy

NOVEMBER 3, 2017

As a research scientist at the German online retail giant Zalando, Dr. Alan Akbik is an expert in Natural Language Processing and Data Extraction. In his work for the company, which at any given moment is handling massive numbers of online transactions in multiple languages, Akbik helps unveil unique insights. The post Data Science is Helping Zalando Learn Languages appeared first on Dataconomy.

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Dataconomy

OCTOBER 28, 2017

The standard user flows that currently dictate our interactions with computers are still quite limited, and are only a few years away from becoming unrecognizable. The process of changing this dynamic has already begun in the form of conversational interfaces. They will soon revolutionize how humans interact with machines. Just. The post Conversational commerce: from hype to reality appeared first on Dataconomy.

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Artificial Intelligence Artificial Intelligence Machine Learning Machine Learning 185

Dataconomy

OCTOBER 30, 2017

The Lufthansa Group is about much more than just transporting passengers and air freight from A to B. The subsidiary company I work for is called “Lufthansa Industry Solutions” (LHIND for short). As well as dealing with the exciting challenges faced by the airline industry within the Lufthansa Group, we. The post How Data Science is Serving Passengers at Lufthansa appeared first on Dataconomy.

Data Science 164

Data Science 164

Dataconomy

NOVEMBER 3, 2017

This article was originally published on cmo.com Every decade or so, a new, game-changing technology platform changes the way the world works. From the desktop, to mobile, and to the cloud, the landscape continues to advance. And now? We are knee-deep in the artificial intelligence (AI) revolution—one so big that. The post How 3 Brands Are Using AI For Enhanced Creativity appeared first on Dataconomy.

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Speaker: Chris Townsend, VP of Product Marketing, Wellspring

Over the past decade, companies have embraced innovation with enthusiasm—Chief Innovation Officers have been hired, and in-house incubators, accelerators, and co-creation labs have been launched. CEOs have spoken with passion about “making everyone an innovator” and the need “to disrupt our own business.” But after years of experimentation, senior leaders are asking: Is this still just an experiment, or are we in it for the long haul?

Dataconomy

NOVEMBER 1, 2017

By Dale T. Anderson, Talend Regional Manager, Customer Success Architect & Kent Graziano, Snowflake Senior Technical Evangelist So you want to build a Data Lake? Ok, sure let’s talk about that. Perhaps you think a Data Lake will eliminate the need for a Data Warehouse and all your business users will merely. The post Building a Governed Data Lake in the Cloud appeared first on Dataconomy.

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Data Lakes Data Warehouse Big Data Big Data 131

Dataconomy

NOVEMBER 2, 2017

Necessity might be the mother of all inventions, but it takes many forward-thinking minds to figure out what customers want before even they realize it. That’s the main reason why so many companies have been putting real money and resources behind setting up “innovation labs.” Indeed, a 2015 study by. The post Adobe and AI: Making Sense of Sensei appeared first on Dataconomy.

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