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.
Proprietary solutions, once the mainstay of enterprise data science, are now being eclipsed by open source projects like R, Spark, and TensorFlow. There are several reasons for this trend: Open source tools offer endless opportunities for collaboration and contribution, and many have been built out to the point that they provide very real value, even at […]
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.”
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.
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.
At The Data Incubator we pride ourselves on having the latest data science curriculum. Much of our course material is based on feedback from corporate and government partners about the technologies they are looking to learn. This report is the second in a series analyzing data science related topics. We thought it would be useful to the data science community to rank and analyze a variety of topics related to the profession in a simple, easy to digest cheat sheet, ranking, or report. It’s our way of practicing what we teach.
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, 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.
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.