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Oracle Big Data Essentials
Duration: 3 Days
What you will learn
This Oracle Big Data Essentials training deep dives into using the Oracle Big Data Solution. Through hands-on, interactive instruction and exercises, you'll develop the skills to acquire, organize, analyze and make key decisions based on the big data.
Learn To:
Define Big Data.
Understand Oracle's Integrated Big Data Solution.
Describe the Oracle Big Data Components.
Define Cloudera's distribution of Hadoop and its components.
Acquire raw data using Oracle NoSQL Database and HDFS.
Organize the collected data using Hive and Oracle Big Data Connectors.
Analyze big data using the Oracle Analytics tool.
Derive business decisions using Oracle BI tools.
Study the case-scenarios where Oracle Big Data is applied successfully.
Benefits to You
Use Big Data to utilize abundant resources to increase innovation, retain customers and increase operational efficiency.
If you're a Data Integration developer, you can use the ODI Application Adapter for Hadoop to integrate big data.
Enrolling in this course will help you explore the wide range of analysis options available in Oracle Analytics, allowing you to choose the analytics tool based on your requirement. Furthermore, taking this course will help you explore the integration options available in Oracle Big Data. You'll study the case scenarios where Oracle Big Data stands as the perfect solution.
Participate in Hands-On Exercises
This training will help you obtain hands-on experience using Oracle Big Data VM. In addition to direct instruction, expert Oracle University instructors will also help you apply your learning to practical tasks used in your daily job by engaging you in hands-on exercises. These hands-on exercises will help reinforce new concepts.
Audience
Application Developers Database Administrators
Related Training
Required Prerequisites
Basic knowledge in analyzing Big Data
Java programming
Suggested Prerequisites
Exposure to working in Multi-tier server environment
Introduction to Big Data
Course Objectives Define Big Data
Understand the Importance of Big Data Technologies
Obtain an insight of the current implementation details
Understand the Oracle Big Data Solution
Explore the Integration possibilities of Oracle Engineered Systems
Learn to use Oracle Big Data Appliance
Identify the hardware components and the software components of BDA
Understand Cloudera's distribution of Hadoop
Define Hadoop Ecosystem
Identify the two techniques used for acquiring big data
Compare and analyze the best way to acquire big data
Learn to use HDFS to acquire unstructured data
Understand the working of Oracle NoSQL Database
Understand the importance of organizing big data
Define Hive
Learn to create Hive database and external tables
Course Topics Introduction Course Objectives
Course Schedule Course Environment
Accessing the Labs Directory Additional Resources
Overview of Big Data Defining Big Data Big Data Technologies
Four characteristics of Big Data Business Value of Big Data Current Implementation Examples
Understanding Oracle's Solution for Big Data Overview of Oracle Engineered Systems
Understand the phases of Oracle Big Data Oracle Big Data Integration Process Benefits
Using Oracle Big Data Appliance Overview of BDA
Managing the Hardware Components Overview of the Software Components Networking Mechanisms
Configuration Mechanisms Installation guidelines Usage restrictions
Data Acquisition Options in BDA Overview of Oracle NoSQL Database Overview of Hadoop Framework Understand HDFS
NoSQL Versus HDFS Real-time scenarios
Using The Hadoop Distributed File System Define HDFS
Components Architecture List the benefits
Run a sample application to insert logs to HDFS
Using Flume in HDFS Define Flume
Understand the data flow mechanism of Flume Understand the configuration of Flume
List the advantages of using Flume Run a sample application
Using Oracle NoSQL Database Define Oracle NoSQL Database Components
Architecture
Define KVStore and KVLite List the benefits
Using Hive Overview of Hive Invoking Hive
Creating Hive database and tables Data manipulation in Hive
Creating partitioned tables for analyzing logs
Using Oracle Big Data Connectors
Get introduced to Oracle Big Data Connectors Connecting Oracle Exadata with BDA
MapReduce Process
Solving the WordCount problem using MapReduce
Using Oracle Loader for Hadoop OLH Architecture
Installing OLH OLH Modes
Loading from different input sources: OLH and input format Load Balancing while loading into partitioned tables Example to load data using OLH
Using Oracle Sql Connector for HDFS
Installing OSCH in a Hadoop Cluster and an Oracle Database Machine Role of External Table in OSCH
Creating External Tables in OSCH
Performance comparison of the connectors Loading data into the database using OSCH
Example to access data from HDFS using external table
Using ODI Application Adapter for Hadoop Overview of ODI
ODI Architecture and Agents ODI Knowledge Modules Topology setting
Reverse Engineering Hive Tables
Example to transform data within Hadoop using ODIAAH
Using Oracle R Connector for Hadoop
Example to access data from HDFS using external table List the ORCH packages
List the architectural components
Establish a connection with HDFS and Oracle Database Sample R program using ORCH
Using In-Database Analytics
Overview of Oracle In-Database MapReduce Overview of Oracle In-Database Analytics
Using Oracle Big Data Integration Options
Architecture and components of Oracle Big Data Solution Connecting Oracle exalytics with BDA
Integrating BDA results with OBIEE
Examining Big Data Use-cases
Use of Big Data in Manufacturing Industry Financial Services
Insurance Services Utilities Sector Telecom
Sentiment Analysis in Retail Industry