The Idea Center at Miami Dade College - Miami
There are many use cases where your data is bigger than a single machine and you may not have experience with Hadoop, MapReduce, Spark or others. This talk explores approaches for dealing with 'medium' and "large" sized datasets from a data scientist/data analyst perspective, or whoever is doing the analysis. We offer some practical considerations related to working with large data sets in R, and details some cloud technologies for big data that you can connect with R, like Spark and sparklyr (which is easy to use in the cloud with Azure Databricks).
Hosted by Cris and 3 others from Data Science Study Group: South Florida
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