NoSQL, Big Data and Spark Fundamentals

Differentiate between the four main categories of NoSQL repositories and work hands-on with MongoDB, Cassandra and IBM Cloudant. ,Apply your knowledge of the characteristics, features, benefits, limitations, and applications of the more popular Big Data processing tools, including Hadoop, HDFS, Hive and HBase. ,Describe parallel programming using Resilient Distributed Datasets (RDDs), DataFrames and SparkSQL. Understand how Catalyst and Tungsten benefit Spark programmer and see how ETL work using DataFrames. ,Acquire real-world data engineering and machine learning skills using Spark Structured Streaming, DataFrames, GraphFrames, Spark ML, Regression, Classification, and clustering, including the k-means algorithm and ETL using Spark. ,Gain hands-on experience using SparkSQL, Apache Spark on IBM Cloud. ,Learn about scaling out using the IBM Spark Environment in Watson Studio, running Spark on Kubernetes, setting Spark configurations, and performing monitoring and performance tuning.