Oracle 19c Big Data

Oracle 19c Big Data

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3 Days

Certified Instructor

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Course Description

Course Overview

The Oracle 19c Big Data course provides comprehensive training on Oracle’s big data solutions, including Oracle Big Data Appliance and Oracle Big Data Cloud Service. Participants will gain an understanding of the underlying technologies and tools for managing and analyzing big data, such as Apache Hadoop, Apache Spark, and Oracle NoSQL Database. The course covers topics ranging from data ingestion and processing to data storage and analytics, enabling participants to leverage Oracle’s big data platform effectively.


To make the most of this course, participants should have a basic understanding of database concepts and familiarity with SQL. Additionally, prior knowledge of big data technologies and concepts, such as Hadoop and Spark, would be beneficial but not mandatory.


The course employs a combination of theoretical instruction, demonstrations, and hands-on labs. Participants will receive detailed explanations of big data concepts and technologies, followed by practical demonstrations of their implementation. They will also have the opportunity to apply their learning in hands-on labs, gaining practical experience with Oracle’s big data solutions. The course is delivered through instructor-led sessions, allowing participants to interact, ask questions, and engage in discussions.

Course Outline

Introduction to Big Data

Understanding the characteristics and challenges of big data

Introduction to Oracle’s big data solutions

Overview of Apache Hadoop and Spark

Oracle Big Data Architecture

Introduction to Oracle Big Data Appliance and Oracle Big Data Cloud Service

Understanding the components of the Oracle big data platform

Overview of Oracle NoSQL Database

Data Ingestion and Processing

Importing and processing data using Apache Sqoop

Extracting and transforming data with Apache Hive

Introduction to Apache Spark and its integration with Oracle big data solutions

Data Storage and Management

Overview of Hadoop Distributed File System (HDFS)

Storing and managing data in Hadoop using HDFS

Introduction to Oracle NoSQL Database and its features

Big Data Analytics with Oracle

Introduction to Oracle Big Data SQL

Integrating and analyzing data from diverse sources

Performing complex analytics using SQL and Oracle Advanced Analytics

Real-Time Data Processing

Introduction to Apache Kafka and its integration with Oracle big data solutions

Processing and analyzing streaming data with Apache Kafka and Spark Streaming

Implementing real-time data pipelines

Big Data Security and Governance

Securing big data environments using authentication and authorization mechanisms

Implementing data privacy and compliance measures

Data governance and metadata management in big data environments

Big Data Deployment and Operations

Deploying and managing Oracle Big Data Appliance and Oracle Big Data Cloud Service

Monitoring and troubleshooting big data environments

Implementing high availability and disaster recovery measures

Course Outcome

By the end of the course, participants will:

  • Understand the concepts and technologies underlying big data.
  • Be familiar with Oracle’s big data solutions, including Big Data Appliance and Big Data Cloud Service.
  • Have the skills to ingest, process, store, and analyze big data using Oracle’s big data platform.
  • Be proficient in utilizing Apache Hadoop, Spark, and NoSQL Database in the context of big data.
  • Understand how to perform real-time data processing and analysis.
  • Possess knowledge of big data security, governance, and operational considerations.

Course Labs

The course includes hands-on labs that provide participants with practical experience in working with Oracle’s big data solutions. The labs cover various scenarios, allowing participants to practice data ingestion and processing, data storage and management, big data analytics, real-time data processing, and security and governance measures. The labs are designed to reinforce the concepts learned during the theoretical instruction and help participants build confidence in their big data skills.

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