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Oracle 1z1-449

1z1-449

Exam Code: 1z1-449

Exam Name: Oracle Big Data 2017 Implementation Essentials

Updated: Aug 19, 2026

Q&A Number: 72 Q&As

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1z1-449 Online Test Engine

Understanding functional and technical aspects of Oracle Big Data 2017 Certification Implementation Specialist Certification Exam 1z0-449 Core Hadoop

The following will be discussed here:

  • Use Flume in the Hadoop Distributed File System
  • Oracle Loader for Hadoop
  • Explain the Hadoop Ecosystem
  • Describe the Impala real-time query and explain how it differs from Hive
  • Implement the data flow mechanism used in Flume
  • Move data from a database to a Hadoop Distributed File System using Sqoop
  • Explain the Oracle Loader for Hadoop
  • Cloudera Enterprise Hadoop Distribution
  • Describe Hadoop High Availability
  • Describe the architectural components of MapReduce
  • Implement the Hadoop Distributed File System
  • Load Hadoop Distributed File System Data into an Oracle database
  • Execute a Hive query
  • Create a database and table from a Hadoop Distributed File System file in Hive
  • Describe the importance of Namenode, Datanode, JobTracker, TaskTracker in Hadoop
  • Use Pig Latin to query data in HDFS
  • Implement the Oracle Table Access for a Hadoop Connector
  • Configure the online and offline options for the Oracle Loader for Hadoop
  • Core Hadoop
  • Describe the Hive architecture
  • Set up Hive with formatters and SerDe
  • Identify the benefits of the Hadoop Distributed File System (HDFS)
  • Describe the differences between MapReduce and YARN

Reference: https://education.oracle.com/oracle-big-data-2017-implementation-essentials/pexam_1Z0-449

Understanding functional and technical aspects of Oracle Big Data 2017 Certification Implementation Specialist Certification Exam 1z0-449 Oracle Data Integrator (ODI) and Hadoop

The following will be discussed here:

  • Use ODI to transform data from Hive to Hive
  • Explain the business drivers behind Big Data and NoSQL versus Hadoop Core Hadoop - Explain the Hadoop Ecosystem
  • Use Flume in the Hadoop Distributed File System
  • Xquery for Hadoop Connector
  • Implement the data flow mechanism used in Flume
  • Describe Hadoop High Availability
  • Describe the architectural components of MapReduce
  • Perform a simple Xquery using Oracle XQuery for Hadoop
  • Use ODI to move data from Hive to Oracle
  • Implement the Hadoop Distributed File System
  • Big Data Technical Overview - Describe the architectural components of the Big Data Appliance
  • Use Oracle Xquery with Hadoop-Hive to map an XML file into a Hive table
  • Use ODI to move data from an Oracle database to a Hadoop Distributed File System using sqoop
  • Describe the importance of Namenode, Datanode, JobTracker, TaskTracker in Hadoop
  • Identify and architect the services that run on each node in the Big Data Appliance, as it expands from single to multiple nodes
  • Describe the Big Data Discovery and Big Data Spatial and Graph solutions
  • Describe how Big Data Appliance integrates with Exadata and Exalytics
  • Set up Oracle Xquery for Hadoop connector
  • Identify the benefits of the Hadoop Distributed File System (HDFS)
  • Describe the differences between MapReduce and YARN
  • Configure the Oracle Data Integrator with Application Adaptor for Hadoop to interact with Hadoop
  • Oracle Data Integrator (ODI) and Hadoop

Understanding functional and technical aspects of Oracle Big Data 2017 Certification Implementation Specialist Certification Exam 1z0-449 Oracle NoSQL Database

The following will be discussed here:

  • Use an Oracle NoSQL database
  • Set up the KVStore
  • Oracle SQL Connector for Hadoop Distributed File System (HDFS)
  • Describe the Oracle R Advanced Analytics for a Hadoop connector
  • Describe the architectural components (Shard, Replica, Master) of the Oracle NoSQL database
  • Use Oracle R Advanced Analytics for a Hadoop connector
  • Oracle NoSQL Database
  • Use KVLite to test NoSQL applications
  • Implement an Oracle Database connection with Oracle R Enterprise
  • Describe the Oracle SQL Connector for Hadoop Connector
  • Integrate an Oracle NoSQL database with an Oracle database and Hadoop
  • Programming with R
  • Install the Oracle SQL Connector for Hadoop
  • Configure an external table for HDFS using the Oracle SQL Connector for Hadoop
  • Describe the architectural components of Oracle R Advanced Analytics for Hadoop

Understanding functional and technical aspects of Oracle Big Data 2017 Certification Implementation Specialist Certification Exam 1z0-449 Big Data Technical Overview

The following will be discussed here:

  • Big Data Technical Overview
  • Explain the business drivers behind Big Data and NoSQL versus Hadoop
  • Describe the architectural components of the Big Data Appliance
  • Identify and architect the services that run on each node in the Big Data Appliance, as it expands from single to multiple nodes
  • Describe the Big Data Discovery and Big Data Spatial and Graph solutions
  • Describe how Big Data Appliance integrates with Exadata and Exalytics

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Oracle 1z1-449 Exam Syllabus Topics:

SectionWeightObjectives
Oracle NoSQL Database20%- Integration with Oracle Database and Hadoop
- KVStore setup and configuration
- Architecture: Shard, Replica, Master
Advanced Analytics & Security20%- LDAP/Active Directory authentication
- Security and access control
- Oracle R Advanced Analytics for Hadoop
Big Data Technical Overview15%- Business drivers for Big Data and NoSQL
- Hadoop ecosystem fundamentals
- Big Data Appliance architecture and components
Big Data SQL & Integration20%- XQuery with Hadoop-Hive
- Oracle Loader for Hadoop
- Integration with Exadata and Exalytics
- Oracle Table Access for Hadoop Connector
Core Hadoop25%- Data ingestion with Flume and Sqoop
- HDFS architecture and high availability
- MapReduce vs YARN
- Hive, Impala, Pig usage

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