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Oracle Big Data Fundamentals Ed 2
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...
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$5,000 USD
Duration
5 days
Course Code
D86900GC20
Available Formats
Classroom, Virtual
Overview
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.
- Describe Oracle's Integrated Big Data Solution and its components.
- Define Cloudera's distribution of Hadoop and its core components and the Hadoop ecosystem.
- Use the Hadoop Distributed File System (HDFS).
- Acquire big data using the Command Line Interface, Flume, and Oracle NoSQL Database.
- Process big data using MapReduce, YARN, Hive, Oracle XQuery for Hadoop, Solr, and Spark.
- Integrate big data and warehouse data using Sqoop, Oracle Big Data Connectors, Copy to Hadoop, Oracle Data Integrator, and Oracle GoldenGate for big data, and Oracle Big Data SQL.
- Analyze big data using Oracle Big Data SQL, Oracle Big Data Spatial and Graph, and Oracle Advanced Analytics technologies.
- Use and manage Oracle Big Data Appliance.
- Identify the key features and benefits of Oracle Big Data Cloud Service.
- Identify the 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.
A Live Virtual Class (LVC) is exclusively for registered students; unregistered individuals may not view an LVC at any time. Registered students must view the class from the country listed in the registration form. Unauthorized recording, copying, or transmission of LVC content may not be made.
Skills Gained
- Review Oracle’s Big Data Management Architecture and Engineered Systems
- Define Big Data
- Identify Big Data Use Cases
- Define the Hadoop ecosystem and its components
- Examine MapReduce programs and balance MapReduce jobs
- Use Oracle NoSQL Database
- Use Oracle XQuery for Hadoop
- Understand Oracle Big Data Cloud Service: Key Features Benefits
- Install
- use
- and administer the Oracle Big Data Appliance
- Provide data security and enable resource management
- Examine MapReduce programs and balance MapReduce jobs
- Use the Oracle BigDataLite Virtual Machine
Prerequisites
- Database Basics and Administration
- Exposure to Big Data
Course Details
Introduction
- Questions About You
- Course Objectives
- Course Road Map
- Oracle Big Data Lite (BDLite) Virtual Machine (VM) Home Page
- Starting the Oracle BDLite VM and accessing the Practice Files
- Reviewing the Available Big Data Documentation, Tutorials, and Other Resources
Introducing Oracle Big Data Strategy
- Characteristics of Big Data
- Importance of Big Data
- Big Data Opportunities: Some Examples
- Big Data Challenges
- Big Data implementation examples
- Oracle strategy for Big Data: combining Big Data Processing Engines: Hadoop / NoSQL / RDBMS
Using Oracle Big Data Lite Virtual Machine and Movieplex Application
- Oracle Big Data Lite VM Used in this Course
- Oracle Big Data Lite VM Home Page Sections
- Reviewing the Deployment Guide
- Downloading and installing Oracle VM VirtualBox and its Extension Pack
- Downloading and Running 7-zip Files to create Virtual Box Appliance File
- Importing the Appliance File
- Staring the Big Data Lite VM and Starting and Stopping Services
- Introducing the Oracle Movieplex Case Study
Introduction to the Big Data Ecosystem
- Computer Clusters and Distributed Computing
- Apache Hadoop
- Types of Analysis That Use Hadoop
- Types of Data Generated
- Apache Hadoop Core Components: HDFS, MapReduce (MR1), and YARN (MR2)
- Apache Hadoop Ecosystem
- Cloudera’s Distribution Including Apache Hadoop (CDH)
- CDH Architecture and Components
Introduction to the Hadoop Distributed File System
- Hadoop Distributed Filesystem (HDFS) Design Principles, Characteristics, and Key Definitions
- Sample Hadoop High Availability (HA) Cluster
- HDFS Files and Blocks
- Active and Standby Daemons (Services) Functions
- DataNodes (DN) Daemons Functions
- Writing a File to HDFS: Example
- Interacting With Data Stored in HDFS: Hue, Hadoop Client, WebHDFS, and HttpFS
Acquire Data using CLI, Fuse, Flume, and Kafka
- Reviewing the Command Line Interface (CLI)
- Viewing File System Contents Using the CLI
- FS Shell Commands
- Loading Data Using the CLI
- Overview of FuseDFS
- What is Flume
- Kafka topics
- Additional Resources
Acquire and Access Data Using Oracle NoSQL Database
- What is a NoSQL Database
- RDBMS Compared to NoSQL
- HDFS Compared to NoSQL
- Define Oracle NoSQL Database
- Oracle NoSQL models: Key-Value and Table
- Acquiring and Accessing Data in a NoSQL DB
- Accessing the CLIs (Data, Admin, SQL)
- Accessing the KVStore
Introduction to MapReduce and YARN Processing Frameworks
- MapReduce Framework Features, Benefits, and Jobs
- Parallel Processing with MapReduce
- Word Count Examples
- Data Locality Optimization in Hadoop
- Submitting and Monitoring a MapReduce Job
- YARN Architecture, Features, and Daemons
- YARN Application Workflow
- Hadoop Basic Cluster: MapReduce 1 Versus YARN (MR 2)
Resource Management Using Yarn
- Job Scheduling in YARN
- First In, First Out (FIFO) Scheduler, Capacity Scheduler, and Fair Scheduler
- Cloudera Manager Resource Management Features
- Static Service Pools
- Working with the Fair Scheduler
- Cloudera Manager Dynamic Resource Management: Example
- Submitting and Monitoring a MapReduce Job Using YARN
- Using the YARN application Command
Overview of Apache Spark
- Benefits of Using Spark
- Spark Architecture
- Spark Application Components: Driver, Master, Cluster Manager, and Executors
- Running a Spark Application on YARN (yarn-cluster Mode)
- Resilient Distributed Dataset (RDD)
- Spark Interactive Shells: spark-shell and pyspark
- Word Count Example by Using Interactive Scala
- Monitoring Spark Jobs Using YARN's ResourceManager Web UI
Overview of Apache Hive
- What is Hive
- Use Case: Storing Clickstream Data
- Hadoop Architecture
- How is Data Stored in HDFS
- Organizing and Describing Data With Hive
- Big Data SQL on Top of Hive Data
- Defining Tables Over HDFS
- Hive Queries
Overview of Cloudera Impala
- Overview of Cloudera Impala
- Hadoop: Some Data Access/Processing Options
- Cloudera Impala
- Cloudera Impala: Key Features
- Cloudera Impala: Supported Data Formats
- Cloudera Impala: Programming Interfaces
- How Impala Fits Into the Hadoop Ecosystem
- How Impala Works with Hive
Overview of Solr
- Overview of Solr
- Apache Solr (Cloudera Search)
- Cloudera Search: Key Capabilities
- Cloudera Search: Features
- Cloudera Search Tasks
- Indexing in Cloudera Search
- Types of Indexing
- The solrctl Command
Integrating Your Big Data
- Unifying Data: A Typical Requirement
- Comparing Big Data Processing Engines
- Introducing Data Unification Options
- When To Use These Options
Batch Loading Options
- Apache Sqoop
- Oracle Loader for Hadoop
- Oracle Copy to Hadoop
Using Oracle Data Integrator and Oracle GoldenGate for Big Data
- ETL and Synchronization: Oracle Data Integrator
- ODI’s Declarative Design
- ODI Knowledge Modules (KMs)Simpler Physical Design / Shorter Implementation Time
- Using ODI with Big Data Heterogeneous Integration with Hadoop Environments
- Using ODI Studio
- ODI Studio Components: Overview
- ODI Studio: Big Data Knowledge Modules
- Oracle GoldenGate for Big Data
Using Oracle Big Data SQL
- Barriers to Effective Big Data Adoption
- Overcoming Big Data Barriers
- Oracle Big Data SQL: The Hybrid Solution
- Benefits: Virtualizes data access across Oracle Database, Hadoop and NoSQL stores
- Using Oracle Big Data SQL
- Query Performance Overview
- Deployment Options
Using Oracle Big Data Spatial and Graph
- Graph and Spatial Analysis: All About Relationships
- What is Oracle Big Data Spatial and Graph (BDSG)
- Strategy (supported platforms, etc)
- BDSG: Graph Analysis
- Oracle BDSG: Spatial Analysis
- Multimedia Analytics Framework
- Deployment Options for Oracle BDSG
- Additional Resources
Using Oracle Advanced Analytics
- Oracle Advanced Analytics (OAA)
- OAA: Oracle Data Mining
- OAA: Oracle R Enterprise
Oracle Big Data Deployment Options
- Introduction to the Oracle Big Data Appliance
- Running the Oracle BDA Configuration Generation Utility
- Oracle BDA Mammoth Software Deployment Bundle
- Using the Oracle BDA mammoth Utility
- BDA Hardware and Integrated and Optional Software
- Administering and Securing the Oracle BDA
- Introduction to the Oracle Big Data Cloud Service
- Introduction to the Oracle Big Data Cloud Service – Compute Edition
Using Oracle Advanced Analytics
- Oracle Advanced Analytics (OAA)
- OAA: Oracle Data Mining
- OAA: Oracle R Enterprise
Oracle Big Data Deployment Options
- Introduction to the Oracle Big Data Appliance
- Running the Oracle BDA Configuration Generation Utility
- Oracle BDA Mammoth Software Deployment Bundle
- Using the Oracle BDA mammoth Utility
- BDA Hardware and Integrated and Optional Software
- Administering and Securing the Oracle BDA
- Introduction to the Oracle Big Data Cloud Service
- Introduction to the Oracle Big Data Cloud Service – Compute Edition
Schedule
2 options available
-
Jun 16, 2025 - Jun 20, 2025 (5 days)
Live Virtual | 9:00AM – 5:00PM EDT Language English Select from 1 options below Live Virtual |9:00AM – 5:00PM EDT- Enroll
- Enroll Add to quote
-
Sep 15, 2025 - Sep 19, 2025 (5 days)
Live Virtual | 9:00AM – 5:00PM EDT Language English Select from 1 options below Live Virtual |9:00AM – 5:00PM EDT- Enroll
- Enroll Add to quote
FAQ
Does the course schedule include a Lunchbreak?
Classes typically include a 1-hour lunch break around midday. However, the exact break times and duration can vary depending on the specific class. Your instructor will provide detailed information at the start of the course.
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Reviews
the interface was super easy to use and the instructions to get ready for the course was also very simple and easy to understand.
The class was very vast paced however the teacher was very good at checking in on us while giving us time to complete the labs.
ExitCertified was a great. They gave me all the materials and information I needed ahead of time to prepare for the course.
This was a good program to get prepared for the solutions architect associate exam.
Overall it was a good bootcamp. A lot to cover so it is understandable that the pace had to be a little fast.
