Why you should use Gandiva for Apache Arrow

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InfoWorld Big Data and Analytics Report

Nov 07, 2018
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Review: MXNet deep learning shines with Gluon

With the addition of the high-level Gluon API, Apache MXNet rivals TensorFlow and PyTorch for developing deep learning models Read More

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Why you should use Gandiva for Apache Arrow
How to add sparklines to R tables
Best practices for developing data-integration pipelines
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R tip: Quick Interactive Tables
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Why you should use Gandiva for Apache Arrow

An execution engine for Arrow-based in-memory processing, Gandiva brings dramatic performance improvements to analytical workloads Read More

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How to add sparklines to R tables

When you want to visualize results in each row—such as when each row of data is a trend over time—you can do that inside a new table column with mini inline graphs called sparklines Read More

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Best practices for developing data-integration pipelines

Because data and analytics are more critical to business operations, it’s important to engineer and deploy strong and maintainable data pipelines Read More

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How to use Knime for data science

Free, open-source Knime allows you to visually assemble data processing “nodes” into machine learning, deep learning, and other analytics workflows Read More

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R tip: Quick Interactive Tables

See how to create an interactive HTML table with one line of code. Plus, plenty of customizations Watch Now

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