Oracle 1z1-449 : Oracle Big Data 2017 Implementation Essentials

  • Exam Code: 1z1-449
  • Exam Name: Oracle Big Data 2017 Implementation Essentials
  • Updated: Aug 30, 2026     Q & A: 72 Questions and Answers

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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:

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

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

The following will be discussed here:

  • Set up and configure Oracle Big Data SQL
  • Use LDAP and the Active directory for Hadoop access control
  • Access NoSQL and Hadoop data using a Big Data SQL query
  • Set up Hive and Impala access security using Apache Sentry
  • Set up the Hadoop Distributed File System to use Access Control Lists
  • Big Data SQL
  • Set up Kerberos security in Hadoop
  • Demonstrate Big Data SQL syntax used in create table statements
  • Securing Hadoop
  • Explain how Big Data SQL is used in a Big Data Appliance/Exadata architecture
  • Describe Oracle Big Data Appliance security and encryption features

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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:

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

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

What is Implementation Essentials 1z0-435 Certification Exam and Retake policy

Oracle Certification can help you gain a competitive advantage by developing a skill set that's in demand, worldwide. You will get to join the 80% of Oracle certification holders who reported a promotion, salary increase or other career improvements. It will give you access to secure digital badge that you can add to your social media profiles.

Cloud Certification for Oracle credentials are valid for a period of 18 months from the date you earn the credential. The credential will become inactive at the end of 18 months. Oracle requires candidates to hold an active credential in order to access certain certification benefits including, without limitation, use of Oracle certification logos, e-Certificates, score reports, digital badges and certification verification.

All the candidates must wait 14 days before retaking a failed proctored exam. (Registration will be allowed on the 14th day). Candidates may not retake a passed exam at any time and may not retake a beta exam at any time. Also, candidates are only allowed 4 attempts to pass an exam in a 12-month period.

Oracle certifications need a periodic recertification in order for Oracle to recognize them as active. For this, you must upgrade to a current version within twelve (12) months following Oracle's credential retirement to keep your certification in active status so that you can have access to certain certification benefits including, without limitation, use of Oracle certification logos, eCertificates, score reports, digital badges and certification verification.

Oracle 1z1-449 Exam Syllabus Topics:

SectionObjectives
Topic 1: Data Analytics and Querying- Analytical tools and querying
  • 1. Big Data SQL concepts
    • 2. Hive query concepts
      Topic 2: Big Data Storage- HDFS and storage systems
      • 1. Data locality principles
        • 2. HDFS architecture and replication
          Topic 3: Data Ingestion and Integration- Data ingestion frameworks
          • 1. Sqoop data transfer concepts
            • 2. Flume event ingestion basics
              Topic 4: Big Data Fundamentals- Big Data concepts and architecture
              • 1. 3 Vs of Big Data (Volume, Velocity, Variety)
                • 2. Hadoop ecosystem overview
                  Topic 5: Data Processing- Batch and stream processing
                  • 1. Spark-based processing concepts
                    • 2. MapReduce processing model
                      Topic 6: Security and Administration- Security and cluster management
                      • 1. Authentication and authorization in Hadoop
                        • 2. Cluster monitoring and administration

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