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(This article was first published on <strong><a href="http://blog.revolutionanalytics.com/2017/09/knime-azure.html"> Revolutions</a></strong>, and kindly contributed to <a rel="nofollow" href="https://www.r-bloggers.com/">R-bloggers)</a> </div>
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<p>Version 3.4 of the Knime Analytics Platform, the open-source data science workflow toolbox, was <a rel="nofollow" href="https://www.knime.com/whats-new-in-knime-34" target="_blank">released back in July</a>. With that release came new integrations with Azure and Microsoft R Server, which were highlighted in a <a rel="nofollow" href="https://www.knime.com/blog/a-touch-of-azure" target="_blank">recent blog post</a>. With Knime 3.4, you can use Microsoft R Server packages in an R node, and connect to data services in Azure.</p>
<p>Knime 3.4 includes a new example: <a rel="nofollow" href="https://www.knime.com/nodeguide/partners/microsoft/predict-departuredelays-with-microsoftr" target="_blank">predicting departure delays from the Airlines data set</a>. To run this example, you'll need to configure Knime to make Microsoft R Client or Microsoft R Server the default R engine used by Knime. With that change made, you can access the built-in airlines data set, and used the <a rel="nofollow" href="https://docs.microsoft.com/en-us/r-server/r/how-to-revoscaler-logistic-regression" target="_blank">rxLogit function</a> in the RevoScaleR library to fit a logistic regression model, even though the data is larger than could normally be accommodated by R. You can see the process demonstrated in the video below.</p>
<p><iframe width="450" allowfullscreen="" src="https://www.youtube.com/embed/HtlpvydyZD0" height="282"></iframe></p>
<p>This update also provides several example workflows for accessing data in various Azure services including:</p>
<ul>
<li><a rel="nofollow" href="https://www.knime.com/nodeguide/partners/microsoft/sql-server-indb-processingazure" target="_blank">SQL Server on Azure</a>, with in-database processing</li>
<li><a rel="nofollow" href="https://www.knime.com/nodeguide/partners/microsoft/sqlserver-blobstorage-andknimemodels" target="_blank">Azure Blob Storage</a></li>
<li><a rel="nofollow" href="https://www.knime.com/nodeguide/partners/microsoft/hdi-hive-knime" target="_blank">Hive on HDInsight</a></li>
<li><a rel="nofollow" href="https://www.knime.com/nodeguide/partners/microsoft/hdi-hive-spark" target="_blank">Spark on HDInsight</a></li>
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<p>Knime users can find these workflows in the Knime Examples Server, and you can find further details at the link below.</p>
<p>Knime blog: <a rel="nofollow" href="https://www.knime.com/blog/a-touch-of-azure" target="_blank">A Touch of Azure in Your KNIME Workflow</a></p>
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