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New Research Proves Increased Awareness in the Value of Open Data Science, but Enterprises are Slow to Respond

New research announced by Continuum Analytics, the creator and driving force behind Anaconda, a leading Open Data Science platform powered by Python, finds that 96 percent of data science and analytics decision makers agree that data science is critical to the success of their business, yet a whopping 22 percent are failing to make full use of the data available. These findings are included in Continuum Analytics’ new eBook, Winning at Data Science: How Teamwork Leads to Victory.

Open Source Tools for Enterprise Data Science

Learn about open source tools for enterprise data science by downloading the new white paper, “DataScience Trends Report: Open Source Tools for Enterprise Data Science” by DataScience, Inc. The white paper looks at activity data from the most popular GitHub repositories to identify trends in data visualization tools, deep learning libraries, and open source licensing using the interactive DataScience Trends tool.

Should You Use Python or R for Your Programming Language?

In this contributed article, technology writer and blogger Kayla Matthews discusses the age-old “R vs. Python” debate that has circulated around in the data science community for the past few years. “When it comes to choosing a programming language, there really are only two choices if you’re working with data. For data science, machine learning, statistics, IoT technology and even automation, the two best languages to use are Python and R.”

How Data Science Can Help You Not to be Blindsided in Decision-Making

In this contributed article, Analyst Mohammad Farooq discusses four important ways that data science affects every business function and can help you not to be blindsided in decision-making. The power of data science lies in the ability to take data and transform it into actionable insights. It can help in decision making. Besides, data science is not limited to extracting data.

Quantifying Data Science

Our friends over at The Data Incubator just released a new series of data-driven ranking reports that showcase the quantitative methodologies the data science fellowship, hiring and training company uses to actively teach their fellows. The idea was to develop a more data-driven approach to what the company should be teaching in their data science corporate training and their free fellowship for masters and PhDs looking to enter data science careers in industry.

Dataiku DSS 4.0 Enables Scalable Data Science Team Collaboration and Production

Dataiku, the maker of the enterprise-grade platform for data teams, Dataiku Data Science Studio (DSS), has announced the release of Dataiku DSS 4.0, which introduces new functionalities that improve the production, development, and management of enterprise data science projects.

Alooma Live Provides Real-Time Visualization of Cloud Data Streams

Alooma, the modern data pipeline company, announced Alooma Live, a real-time visualization tool that enables data scientists and engineers to monitor data streams in transit. It allows enterprises to monitor behavior and identify discrepancies to correct data integrity problems before they can impact data warehouse and business intelligence (BI) applications.

Cloudera to Accelerate Data Science and Machine Learning for the Enterprise with New Data Science Workbench

Cloudera, the provider of a leading platform for machine learning and advanced analytics built on the latest open source technologies, today unveiled Cloudera Data Science Workbench, a new self-service tool for data science on Cloudera Enterprise which is currently in beta.

Making the Leap from Data Science Hopeful to Practitioner

It’s a familiar dilemma. You’ve done your research, read some books, taken some online classes – and at long last, you’re finally ready to get real-life work experience as a Data Scientist. In this contributed article, Dan Saber, Data Science Hiring Manager at Coursera, offers three important steps for successfully transitioning into a data science career.

Interview: Emily Glassberg Sands, Data Science Manager at Coursera

I recently caught up with Emily Glassberg Sands, Data Science Manager at Coursera, to talk about applying machine learning, neural networks, natural language processing, and big data analytics to the retail industry. Emily leads an awesome team of data scientists and data science managers working on growth, discovery, the learning experience, and a new enterprise offering. The team’s job is to help build a better Coursera through data-driven decisions and products.