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Infographic: The Data Scientist Shortage

Statistics point to a promising career in data science for anyone with the skills and interest to pursue this field in the 21st Century, whether one wishes to start from the first year of university or redirect his or her track midway. Given the current employment crisis featured in the infographic below, developed by our friends over at the University of California, Riverside, even individuals who have pursued programming and technical programs at high school could be thrust into more demanding positions in the work place.

Building a Winning Data Science Team

In this contributed article, Brad Cordova, co-founder and CTO of TrueMotion, discusses the importance of building a winning data science team, including actionable tips drawn from his own experience on structure, investment and building a culture where data science thrives.

The Speed of Data: A Survey of Data Decision Makers

Streamlio, the intelligent platform for fast data, announced results of a new “Speed of Data” survey conducted with Dimensional Research. The survey of hundreds of corporate decision makers worldwide found near universal agreement about the criticality of faster data processing, along with a huge gap between where companies need to be and where they are today.

Best of arXiv.org for AI, Machine Learning, and Deep Learning – July 2018

In this recurring monthly feature, we will filter all the recent research papers appearing in the arXiv.org preprint server for subjects relating to AI, machine learning and deep learning – from disciplines including statistics, mathematics and computer science – and provide you with a useful “best of” list for the month.

Coursera Expands Coursera for Business Features, Launches AI-powered Skills Benchmarking Tool

Coursera, an online learning leader, announced the launch of Skills Benchmarking, a powerful new Coursera for Business tool that enables organizations to measure how their talent stacks up against others in their industry as well as identify top performing individuals in a given competency area.

Where Do World Leading Companies Get Their AI Expertise From?

In this contributed article, Anna Klimenko, a technical writer at Greenice, discusses a topic on the mind of many companies – how to find AI technology talent. With the deficiency of AI specialists, there are several ways to build AI expertise in a big company. The most prominent university students, graduates and professors become targets for headhunters. Hiring rare specialists, educating own employees, acquiring AI startups and creating ML-as-a-service systems are the main methods that allow companies to get artificial intelligence expertise.

Fast Machine Learning for Smart Cities: RocketML at Global Tech Jam

In this video from the Global Tech Jam 2018 conference on Smart Cities, Santi Adavani from RocketML describes how the company’s innovative software speeds Machine Learning. “To find the best model for a problem, data scientists try out different algorithms. With RocketML, they don’t have to. It is like a Hyperloop solution to go from point A to point Z. Simplified workflow yields new benefits.”

2018 Executive Round Up: The Rise of AI and Machine Learning

Welcome to our 2018 insideBIGDATA Executive Round Up, a quarterly feature showcasing the insights of thought leaders on the state of big data, data science, machine learning, AI and deep learning, and where these trending technologies are headed. Weighing in with their thought-leadership predictions are some of the industry’s biggest players. We’re honored to pass along these comments to our valued audience.

New Study Reveals Enterprises Risk Missing Out on 547% ROI on Data Initiatives

Our friends over at SnapLogic, a leader in self-service application and data integration, released “The 2018 Data Value Report,” a new study that reveals enterprises expect to generate a 547% return on their data investments, increasing revenue by an average $5.2 million as a result of using data more effectively. However, businesses have only scratched the surface in realizing data’s potential: On average, organizations are using only half (51%) the data they collect or generate, and data drives less than half (48%) of decisions.

AI and the Emerging Crisis of Trust

In this guest article, Doug Bordonaro, Chief Data Evangelist at ThoughtSpot, explores the role trust plays in adoption of AI in the home, our jobs and beyond.