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Operationalizing Data Science

In the video presentation below, Joel Horwitz, Vice President, Partnerships, Digital Business Group for IBM Analytics, discusses what it means to “operationalize data science” – basically what it means to harden the ops behind running data science platforms.

Research of 1,001 Data Scientist LinkedIn Profiles

Data science is a super-hot topic and the data scientist job is the sexiest job of the 21st century according to the Harvard Business Review. But how does one actually become a data scientist? 365 DataScience gathered data from 1,001 publicly listed LinkedIn profiles of data scientists and prepared a compelling report “Studying 1,001 Data Scientist LinkedIn Profiles.”

Trifacta Expands Data Wrangling on the Cloud with Additional Support of Amazon Web Services and Availability on AWS Marketplace

Trifacta, a leader in data wrangling, announced expanded support for Amazon Web Services (AWS) and the availability of Wrangler Edge and Wrangler Enterprise on AWS Marketplace, allowing organizations to deploy Trifacta in less than an hour. Trifacta has also earned AWS Machine Learning (ML) Competency status. This achievement recognizes that Trifacta has demonstrated success in helping customers deploy their ML workloads on AWS.

Sentenai Delivers Automated Data Engineering for Data Science and Machine Learning Applications

Sentenai, an emerging sensor data technology company, announced the availability of its flagship product, the Sentenai Sensor Data Cloud. By going beyond the initial harnessing of machine-based data and understanding the information that data provides, organizations can streamline their operational processes and develop predictive maintenance solutions that decrease unplanned downtime.

The Myth of Entry-level Data Science

In this special guest feature, Kevin Safford, Sr. Director of Engineering for Umbel offers a no-nonsense look at how to answer the proverbial question “How can I become a data scientist.” To understand how to become a data scientist, it’s best to get on the same page on what data science is. And if this is your career path, get accustomed to always defining your domain before you begin.

The Practical Guide to Managing Data Science at Scale

Our friends over at Domino Data Lab, Inc. have written a new whitepaper “The Practical Guide to Managing Data Science at Scale” that aims to demystify and elevate the current state of data science management. They identify consistent struggles around stakeholder alignment, the pace of model delivery, and the measurement of impact. The root cause of these challenges can be traced to a set of particular cultural issues, gaps in process and organizational structure, and inadequate technology.

The Proliferation of Data Science Tools & Technology

In this special guest feature, Matthew Mahowald, Lead Data Scientist and Software Engineer for Open Data Group, shares his perspectives on how the speed at which tech and tools have been developed, has caused problems with the way analytic deployment is made possible.

AI is Inspiring the Next Wave of Healthcare Advancement

Advancements in artificial intelligence, or AI, are revolutionizing healthcare and leading to breakthrough results in prediction and prevention. A new report from HPE focuses on how tech tools like GPUs and deep learning platforms are changing and advancing the health care industry.

Intel’s New Processors: A Machine-learning Perspective

Machine learning and its younger sibling deep learning are continuing their acceleration in terms of increasing the value of enterprise data assets across a variety of problem domains. A recent talk by Dr. Amitai Armon, Chief Data-Scientist of Intel’s Advanced Analytics department, at the O’reilly Artificial Intelligence conference, New-York, September 27 2016, focused on the usage of Intel’s new server processors for various machine learning tasks as well as considerations in choosing and matching processors for specific machine learning tasks.

MapR Delivers Self-Service Data Science for Leveraging Machine Learning and Artificial Intelligence

MapR Technologies, Inc., a pioneer in delivering one platform for all data, across every cloud, announced the MapR Data Science Refinery, a new solution that provides data scientists an easy way to access and analyze all data in-place, to collaborate, build and deploy machine learning models on the MapR Converged Data Platform.