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Big Data Fundamentals Training

Course Summary

Our Big Data fundamentals training course lets you master the technique of Big Data processing, storing, and deploying in an enterprise scenario. We provide the best online classes to learn Hadoop ecosystem, HDFS, MapReduce, Hive, Sqoop, Pig, Sqoop, Spark, Storm, ZooKeeper. Work on critical Big Data real world projects.


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    Course Syllabus

    Big Data Fundamentals Course Content

    Introduction Big data
    Big Data and its importance, What is Distributed system
    Examples of Big Data
    Characteristics of Big Data, Introduction to Hadoop and its works, Examples of Big Data
    Hadoop Uses
    What is Hadoop and How Hadoop work
    Installation Hadoop
    Installation of Single Node Apache Hadoop
    Hadoop Architecture
    Session 1What is HDFSSession 2Planning Hadoop cluster & Hardware ConsiderationsSession 3Hadoop Cluster Maintenance
    Mapreduce
    What is map reduce, Example program: Word count, Map phase, Shuffle and sort, Reduce phase, Name node
    Hive
    Hive introduction, What is Hive, Origin of Hive, Hadoop based system, Where we not use
    Mahout
    Session 1Intro to Mahout, Fundamentals of Machine LearningSession 2What is Classified, Classification, Clustering, Recommendation, Pattern Mining
    Cassandra
    Session 1What is Cassandra, Who develop Cassandra, Non-relational, What is eventually consistentSession 2Intro to No Sql and comparison with RDBMS, Comparison of RDMS and problems of RDBMS
    SAP HANA
    OLTP, OLAP, SAP BW, SAP BW with BWA, SAP In memory Strategy, SAP HANA compare with BWA
    Spark
    What is Spark and Architecture of Spark, Use of Spark, Component of Spark, Comparison with hadoop
    Scala
    Session 1What is Scala, Uses of ScalaSession 2Advantage of Scala, How scala solve problems of Java and C etc, Architecture of Scala, Spark coding using scala
    Splunk
    What is splunk?, Splunk latest version & OS supported., What does splunk do?, What does splunk provide?


Course Fee:
USD 41

Course Type:

Self-Study

Course Status:

Active

Workload:

1 - 4 hours / week

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