Oracle Big Data Essentials - EASYTEAM


Oracle Big Data Essentials

Prix: 2 031 €Durée: 3 joursCode de Réference: D79454 Catalogue

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.


Application Developers
Database Administrators
Related Training
Copyright © 2013, Oracle. All rights reserved. Page 1Required 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


Course Objectives
Copyright © 2013, Oracle. All rights reserved. Page 2Course 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

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
Real-time scenarios

Using The Hadoop Distributed File System

Define HDFS
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
Copyright © 2013, Oracle. All rights reserved. Page 3Define 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

Copyright © 2013, Oracle. All rights reserved. Page 4Architecture 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
Sentiment Analysis in Retail Industry

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