BlueData, provider of a leading Big-Data-as-a-Service (BDaaS) software platform, announced the new winter release for the BlueData EPIC software platform. This new release delivers several new enhancements for data science operations, bringing DevOps agility and collaboration to data science teams as well as support for new machine learning use cases.
data.world, the social network for data people, today announced it has closed $18.7 million in venture capital funding at double the valuation of its previous round. This second round brings the total amount of capital raised to $32.7 million and places data.world among the technology sector’s top-5 venture-backed Certified B Corporations of all time. The new capital will be used to fund rapid progress toward the company’s mission to build the most meaningful, collaborative, and abundant data resource in the world.
Data science software maker, Dataiku, recently completed a worldwide survey that asked thousands of companies: how does your organization put data science into production? The results show that most companies using data science have unique challenges that fall into four different profiles: Small Data Teams, Packagers, Industrialization Maniacs, and The Big Data Lab.
There’s a part of data science that you never hear about: the production. Everybody talks about how to build models, but not many people worry about how to actually use those models. Yet production issues are the reason many companies fail to see value come from their data science efforts. Dataiku, company that develops a collaborative […]
In this article, we’ll make sense of data science for those unacquainted with the field and outline a series of 7 easy steps to get up to speed with the technology. In doing so, we’ll highlight the integral steps in the “data science process,” so you can get a good grasp of how data science works and how it is of value to enterprises seeking to maximize the value of their data assets.
In this special technology white paper, The 5 Key Challenges to Building a Successful Data Science Lab & Data Team, you’ll learn how a Data Lab establishes an effort to answer business needs by making sense of raw information. Data labs are intended to create critical mass within the organization that enables them to reach the level of innovation required for new data-driven products.
World Programming, a leading industrial analytics and data science platform provider, unveiled new features for data scientists and data science teams including those working within life sciences, pharmaceuticals, and financial services.
In this special technology white paper, From Development to Production Guide – Finding the Common Ground in 9 Steps, you’ll learn how managing a successful data science project requires time, effort, and a great deal of planning. Defining the problems to solve and planning the project’s scope is just the tip of the iceberg, as team members need to fully understand all aspects of a project in order to effectively contribute.
Here’s a useful new book for data scientists looking to approach the field from a unique perspective that doesn’t include language heavyweights like R and Python. “Julia for Data Science,” by Zacharias Voulgaris, Ph.D. from Technics Publications, allows you to master the Julia language to solve business critical data science challenges. But why look to a relatively new language when you already have other commonly-used languages at your disposal?
Bigstep, the big data cloud provider, announced the launch of Bigstep DataLab, a solution designed to enable data science and analytics at scale. Bigstep DataLab is an enterprise-ready data research service that gives domain experts, data scientists and BI specialists instant access to powerful software like Apache Spark and Jupyter for easier, more flexible and collaborative ad-hoc data exploration and research.