Have you ever wondered how major companies and organizations manage all of the massive amounts of data they collect? The answer is Big Data technology, and Big Data engineers are in big-time demand. Major employers like Amazon, eBay, and NASA JPL use Apache Spark to extract data sets across a fault-tolerant Hadoop cluster. Sound complicated? That's why you should take this course, to learn these techniques and more, using your own system at home.
- Access 46 lectures & 5 hours of content 24/7
- Learn the concepts of Spark's Resilient Distributed Datastores
- Develop & run Spark jobs quickly using Python
- Translate complex analysis problems into iterative or multi-stage Spark scripts
- Scale up to larger data sets using Amazon's Elastic MapReduce
- Understand how Hadoop YARN distributes Spark across computing clusters
- Learn about other Spark technologies, like Spark SQL, Spark Streaming, & GraphX
Frank Kane spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. Frank holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology, and teaching others about big data analysis.