One of the most interesting technologies to emerge from the Hadoop ecosystem is Spark. Spark presents tools to manage and blend massive datasets using both SQL including R data frames approaches via Spark and Spark new DataFrame data structure. In extension, through its MLlib library, Spark provides the strength to quickly scale auspicious and other forward algorithms immediately in the cluster, avoiding the data latency inherent in moving data to separate data analysis tools. In this presentation, we will provide an overview of Spark and its capabilities, and explain how these abilities can be located in Alteryx via easy to use tools that will be close to all Alteryx users. We will also describe the underlying structure used to connect Alteryx to a Spark group.
Alteryx Analytics now investigators with an automatic workflow for superior analytics and data blending which point to a deeper knowledge in hours, not the week’s typical of common ways. Alteryx Analytics set the power of the new policy of using predictive analytics and data towards the hands of each analyst.
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