{"id":2469,"date":"2017-02-07T00:00:00","date_gmt":"2017-02-07T00:00:00","guid":{"rendered":""},"modified":"2017-06-01T14:02:48","modified_gmt":"2017-06-01T14:02:48","slug":"meditations-on-data-science-sandbox-as-a-service","status":"publish","type":"post","link":"https:\/\/cazenasite.com\/?p=2469","title":{"rendered":"Meditations on our Data Science Sandbox as a Service"},"content":{"rendered":"

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Japanese rock gardens, or zen gardens, were first constructed centuries ago at temples as aids to meditation. Also called \u201cdry landscapes,\u201d zen gardens are often designed to be miniature representations of nature, albeit with some artistic liberties. Zen gardens are made with simple, available materials, primarily sand and rocks, with few plants. Flowing rivers become precisely parallel waving lines in the sand, dotted with carefully placed islands and rock mountains. Raw materials take on new meaning when arranged in different ways. That\u2019s why the zen garden, and the art of modeling a miniature and malleable world, seemed like a perfect image to launch our new Data Science Sandbox as a Service \u2013 and invitation to try a free week.<\/div>\n
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What is Cazena\u2019s Data Science Sandbox as a Service? Think of it as your teams\u2019 personal zen garden in the cloud \u2013 a powerful set of computing, storage and analytic resources all packaged up and delivered in a clean, easy interface. Load your data, and use R, Python or other popular tools for analysis. You\u2019ll get powerful performance, thanks to Spark and many other components in our platform. And with a free week, you can get hands on fast and see just how easy it is to use the cloud to create beautiful things with data.<\/div>\n
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Cazena\u2019s experienced team has put time into creating an intuitive user interface. Our comprehensive service is designed to help data science teams accelerate their work \u2013 without the time and resource constraints that often plague enterprises. We\u2019ve worked with analytics professionals to deliver a service that supports the tools and methods du jour \u2013 R and Python. We embedded analytics engines for better performance, including tools like RStudio Server Pro<\/a> (and others!) and added capabilities to make it easier to ingest data.<\/div>\n
\nHere are a few opportunities to learn more:
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