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    Oracle Big Data Fundamentals Training & Placements in Chennai SQL STAR

    Oracle Big Data Fundamentals Ed 2

    (The Course materials and Course Completion Certificates are directly delivered from Oracle University to those seeking for Foreign Opportunity)

    (Government of India Approved Education Center)

    In the Oracle Big Data Fundamentals course, you learn to use Oracle's Integrated Big Data Solution to acquire, process, integrate and analyze big data. You will also learn about the Oracle Big Data Appliance, Oracle Big Data Cloud Service, and Oracle Big Data Cloud Service - Compute Edition.

    In the Oracle Big Data Fundamentals course, you learn about big data, the technologies used in processing big data and Oracle's solution to handle big data. You also learn to use Oracle Big Data Appliance to process big data, and obtain a hands-on experience in using Oracle Big Data Lite VM. You identify how to acquire the raw data from a variety of sources, and learn to use HDFS and Oracle NoSQL Database to store the data. You learn about data integration options available in Oracle Big Data. These include Oracle Big Data Connectors to move data to and from Oracle Database, Oracle Data Integrator and Oracle GoldenGate for Big Data which provide integration and synchronization capabilities for data unification of relational and Hadoop data, and Oracle Big Data SQL, which enables dynamic, integrated access for all of your data big data, whether it is stored in HDFS, NoSQL, or Oracle Database. Finally, you learn how to analyze your big data using Oracle Big Data SQL, Oracle Advance Analytics, and Oracle Big Data Spatial and Graph.

    Learn To:

    • Define Big Data.
    • DescribeOracle's Integrated Big Data Solution and its components.
    • Define Cloudera's distribution of Hadoop and its core components and theHadoop ecosystem.
    • Use the Hadoop Distributed File System (HDFS).
    • Acquirebig data using the Command Line Interface, Flume, and Oracle NoSQLDatabase.
    • Processbig data using MapReduce, YARN, Hive, Oracle XQuery for Hadoop,Solr, and Spark.
    • Integratebig data and warehouse data using Sqoop, Oracle Big DataConnectors, Copy to Hadoop, Oracle Data Integrator, and OracleGoldenGate for big data, and Oracle Big Data SQL.
    • Analyzebig data using Oracle Big Data SQL, Oracle Big Data Spatial andGraph, and Oracle Advanced Analytics technologies.
    • Useand manage Oracle Big Data Appliance.
    • Identifythe key features and benefits of Oracle Big Data Cloud Service.
    • Identifythe key features and benefits of Oracle Big Data Cloud Service -Compute Edition.

    Benefits To You

    You will benefit from this course as you define the term big data and discuss Oracle’s Big Data solution and use cases. You learn about Apache Hadoop and its core components: HDFS, YARN, and MapReduce. You will also learn about some of the major projects in the Hadoop ecosystem. You will learn how to acquire data into HDFS and Oracle NoSQL Database by using CLI, Flume, and Kafka. To process the data stored in HDFS, you run MapReduce and Spark jobs.

    You also explore a range of analysis options, including Oracle Advanced Analytics (OAA) (comprised of Oracle Data Mining and Oracle R Enterprise), and Oracle Big Data Spatial and Graph.

    You will learn about the Oracle Big Data Appliance, Oracle Big Data Cloud Service, and Oracle Big Data Cloud Service - Compute Edition. You will study case scenarios where Oracle Big Data stands as the perfect solution.

    Suggested Prerequisite

    • DatabaseBasics and Administration
    • Exposureto Big Data

    Audience

    • Application Developers
    • Database Administrators
    • Database Administrators
    • DatabaseDevelopers
    • DatabaseDevelopers

    Course Objectives

    • Define Big Data
    • DescribeOracle's Integrated Big Data Solution and its components
    • Define Cloudera's distribution of Hadoop and its core components and theHadoop ecosystem
    • Use the Hadoop Distributed File System (HDFS)
    • Acquirebig data using the Command Line Interface, Flume, and Oracle NoSQLDatabase
    • Processbig data using MapReduce, YARN, Hive, Oracle XQuery for Hadoop,Solr, and Spark
    • Integratebig data and warehouse data using Sqoop, Oracle Big DataConnectors, Copy to Hadoop, Oracle Data Integrator, and OracleGoldenGate for big data, and Oracle Big Data SQL
    • Analyzebig data using Oracle Big Data SQL, Oracle Big Data Spatial andGraph, and Oracle Advanced Analytics technologies
    • Useand manage Oracle Big Data Appliance
    • Identifythe key features and benefits of Oracle Big Data Cloud Service
    • Identifythe key features and benefits of Oracle Big Data Cloud Service -Compute Edition

    Course Topics

    Introduction

    • Reviewing the Available Big Data Document ation, Tutorials, and OtherResources
    • CourseRoad Map
    • Course Objectives
    • Starting the Oracle BDLite VM and accessing the Practice Files
    • QuestionsAbout You
    • OracleBig Data Lite (BDLite) Virtual Machine (VM) Home Page

    Introducing Oracle Big Data Strategy

    • BigData implementation examples
    • Importanceof Big Data
    • Oraclestrategy for Big Data: combining Big Data Processing Engines:Hadoop / NoSQL / RDBMS
    • Characteristics of Big Data
    • BigData Opportunities: Some Examples
    • BigData Challenges

    Using Oracle Big Data Lite Virtual Machine and Movieplex Application

    • Reviewing the Deployment Guide
    • OracleBig Data Lite VM Home Page Sections
    • Introducing the Oracle Movieplex Case Study
    • OracleBig Data Lite VM Used in this Course
    • Importing the Appliance File
    • Downloading and Running 7-zip Files to create Virtual Box Appliance File
    • Downloading and installing Oracle VM VirtualBox and its Extension Pack
    • Staring the Big Data Lite VM and Starting and Stopping Services

    Introduction to the Big Data Ecosystem

    • Cloudera’sDistribution Including Apache Hadoop (CDH)
    • ApacheHadoop
    • Types of Analysis That Use Hadoop
    • CDHArchitecture and Components
    • ApacheHadoop Ecosystem
    • ComputerClusters and Distributed Computing
    • Types of Data Generated
    • ApacheHadoop Core Components: HDFS, MapReduce (MR1), and YARN (MR2)

    Introduction to the Hadoop Distributed File System

    • SampleHadoop High Availability (HA) Cluster
    • HDFSFiles and Blocks
    • HadoopDistributed Filesystem (HDFS) Design Principles, Characteristics,and Key Definitions
    • Interacting With Data Stored in HDFS: Hue, Hadoop Client, WebHDFS, and httpFS
    • DataNodes(DN) Daemons Functions
    • Writing a File to HDFS: Example
    • Activeand Standby Daemons (Services) Functions

    Acquire Data using CLI, Fuse, Flume, and Kafka

    • Kafkatopics
    • AdditionalResources
    • Viewing File System Contents Using the CLI
    • Whatis Flume?
    • Overview of FuseDFS
    • Loading Data Using the CLI
    • Reviewing the Command Line Interface (CLI)
    • FSShell Commands

    Acquire and Access Data Using Oracle NoSQL Database

    • Oracle NoSQL models: Key-Value and Table
    • Accessing the KVStore
    • Whatis a NoSQL Database
    • Accessing the CLIs (Data, Admin, SQL)
    • Acquiring and Accessing Data in a NoSQL DB
    • HDFSCompared to NoSQL
    • Define Oracle NoSQL Database
    • RDBMSCompared to NoSQL

    Introduction to MapReduce and YARN Processing Frameworks

    • DataLocality Optimization in Hadoop
    • ParallelProcessing with MapReduce
    • YARNArchitecture, Features, and Daemons
    • HadoopBasic Cluster: MapReduce 1 Versus YARN (MR 2)
    • MapReduceFramework Features, Benefits, and Jobs
    • YARNApplication Workflow
    • WordCount Examples
    • Submitting and Monitoring a MapReduce Job

    Resource Management Using Yarn

    • StaticService Pools
    • ClouderaManager Dynamic Resource Management: Example
    • Working with the Fair Scheduler
    • ClouderaManager Resource Management Features
    • FirstIn, First Out (FIFO) Scheduler, Capacity Scheduler, and FairScheduler
    • Submitting and Monitoring a MapReduce Job Using YARN
    • JobScheduling in YARN
    • Using the YARN application Command

    Overview of Apache Spark

    • Benefitsof Using Spark
    • Running a Spark Application on YARN (yarn-cluster Mode)
    • SparkInteractive Shells: spark-shell and pyspark
    • SparkApplication Components: Driver, Master, Cluster Manager, andExecutors
    • Monitoring Spark Jobs Using YARN's ResourceManager Web UI
    • WordCount Example by Using Interactive Scala
    • SparkArchitecture
    • ResilientDistributed Dataset (RDD)

    Overview of Apache Hive

    • Whatis Hive?
    • Howis Data Stored in HDFS?
    • BigData SQL on Top of Hive Data
    • Organizing and Describing Data With Hive
    • Defining Tables Over HDFS
    • UseCase: Storing Clickstream Data
    • HiveQueries
    • HadoopArchitecture

    Overview of Cloudera Impala

    • Hadoop:Some Data Access/Processing Options
    • ClouderaImpala: Programming Interfaces
    • HowImpala Works with Hive
    • ClouderaImpala
    • HowImpala Fits Into the Hadoop Ecosystem
    • Overview of Cloudera Impala
    • ClouderaImpala: Supported Data Formats
    • ClouderaImpala: Key Features

    Using Oracle XQuery for Hadoop

    • XQueryTransformation and Basic Filtering
    • XMLReview
    • Viewing the Completed Query in YARN's ResourceManager
    • Running an OXH Query
    • OXHFeatures
    • OracleXQuery for Hadoop (OXH)
    • Using OXH: Installation, Functions, Adapters, and Configuration Properties
    • OXHData Flow

    Overview of Solr

    • ClouderaSearch: Features
    • Overview of Solr
    • ApacheSolr (Cloudera Search)
    • ClouderaSearch Tasks
    • Indexing in Cloudera Search
    • Types of Indexing
    • Thesolrctl Command
    • ClouderaSearch: Key Capabilities

    Integrating Your Big Data

    • Comparing Big Data Processing Engines
    • Unifying Data: A Typical Requirement
    • Introducing Data Unification Options
    • WhenTo Use These Options?

    Batch Loading Options

    • OracleCopy to Hadoop
    • OracleLoader for Hadoop
    • ApacheSqoop

    Using Oracle SQL Connector for HDFS

    • Using OSCH
    • PerformanceTuning
    • Loading:Choosing a Connector
    • Parallelismand Performance
    • Batchand Dynamic Loading: Oracle SQL Connector for HDFS
    • OSCHArchitecture
    • Features
    • KeyBenefits

    Using Oracle Data Integrator and Oracle GoldenGate for Big Data

    • OracleGoldenGate for Big Data
    • ODI’sDeclarative Design
    • Using ODI with Big Data Heterogeneous Integration with HadoopEnvironments
    • Using ODI Studio
    • ODIStudio: Big Data Knowledge Modules
    • ETLand Synchronization: Oracle Data Integrator
    • ODIKnowledge Modules (KMs)Simpler Physical Design / ShorterImplementation Time
    • ODIStudio Components: Overview

    Using Oracle Big Data SQL

    • QueryPerformance Overview
    • Benefits:Virtualizes data access across Oracle Database, Hadoop and NoSQLstores
    • Overcoming Big Data Barriers
    • Barriersto Effective Big Data Adoption
    • OracleBig Data SQL: The Hybrid Solution
    • DeploymentOptions
    • Using Oracle Big Data SQL

    Using Oracle Big Data Spatial and Graph

    • BDSG:Graph Analysis
    • MultimediaAnalytics Framework
    • DeploymentOptions for Oracle BDSG
    • OracleBDSG: Spatial Analysis
    • Graphand Spatial Analysis: All About Relationships
    • AdditionalResources
    • Strategy(supported platforms, etc)
    • Whatis Oracle Big Data Spatial and Graph (BDSG)?

    Using Oracle Advanced Analytics

    • OAA:Oracle Data Mining
    • OAA:Oracle R Enterprise
    • OracleAdvanced Analytics (OAA)

    Oracle Big Data Deployment Options

    • BDAHardware and Integrated and Optional Software
    • Introduction to the Oracle Big Data Cloud Service – Compute Edition
    • Running the Oracle BDA Configuration Generation Utility
    • Administering and Securing the Oracle BDA
    • Introduction to the Oracle Big Data Appliance
    • OracleBDA Mammoth Software Deployment Bundle
    • Introduction to the Oracle Big Data Cloud Service
    • Using the Oracle BDA mammoth Utility

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