Oracle Big Data Fundamentals Ed 2 Course Overview

To successfully undertake the Oracle Big Data Fundamentals Ed 2 course, students should have the following minimum required knowledge:

• Basic understanding of database concepts, including relational databases and SQL.
• Familiarity with command-line operations and navigation within a Unix or Linux environment.
• Fundamental knowledge of data processing concepts and data analytics.
• An awareness of distributed computing and storage principles is beneficial but not mandatory.
• Some exposure to programming or scripting languages (such as Java, Python, or Bash) can be helpful.
• It's advantageous to have a conceptual grasp of data warehousing and business intelligence, though not required.

Target Audience for Oracle Big Data Fundamentals Ed 2

The Oracle Big Data Fundamentals Ed 2 course is designed for professionals seeking to leverage big data technologies within Oracle's ecosystem.

• Data Scientists
• Data Analysts
• Business Intelligence Specialists
• Database Administrators
• Big Data Architects
• IT Managers overseeing data management teams
• Software Engineers and Developers with a focus on big data solutions
• Hadoop Developers and Administrators
• System Administrators and Engineers involved in big data infrastructure
• Data Warehousing Specialists transitioning to big data platforms
• Technical Consultants involved in big data projects
• Professionals responsible for data compliance and security within big data environments

Learning Objectives - What you will Learn in this Oracle Big Data Fundamentals Ed 2?

Introduction to Oracle Big Data Fundamentals Ed 2 Course Learning Outcomes:

Gain a comprehensive understanding of Oracle's Big Data solutions, including how to acquire, organize, and analyze large-scale data using key Oracle technologies and integrated tools.

Learning Objectives and Outcomes:

• Understand the characteristics, importance, and challenges of Big Data, and explore Oracle's strategy for managing Big Data.
• Acquire hands-on experience with the Oracle Big Data Lite Virtual Machine, including installation, configuration, and use of practice files.
• Gain knowledge of the Big Data ecosystem, including Hadoop and its core components such as HDFS and MapReduce, as well as YARN for resource management.
• Learn to acquire and process data using command line interface (CLI), Oracle NoSQL Database, Flume, and Kafka.
• Develop familiarity with MapReduce and YARN processing frameworks, understanding job scheduling, and monitoring within a Hadoop cluster.
• Explore Apache Spark for in-memory data processing to perform complex analytics faster and with more flexibility.
• Understand how to organize and query large-scale data using Apache Hive and the speed of Cloudera Impala for real-time query processing.
• Gain insights into Oracle XQuery for Hadoop for running complex queries and transformations on XML data.
• Learn the essentials of Apache Solr for indexing and searching large volumes of data to derive insights.
• Explore various data integration techniques like batch loading and real-time synchronization using Oracle Data Integrator and Oracle GoldenGate.
• Understand how to use Oracle Big Data SQL to virtualize data access across different data stores, optimizing query performance.
• Discover the capabilities of Oracle Big Data Spatial and Graph for analyzing relationships in data and Oracle Advanced Analytics for data mining techniques.
• Evaluate Oracle Big Data deployment options, including the Oracle Big Data Appliance and Oracle Big Data Cloud Service offerings.