Oracle Big Data Essentials

Transcription

1 Oracle University Contact Us: Local: Intl: 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 Copyright 2013, Oracle. All rights reserved. Page 1

2 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 Copyright 2013, Oracle. All rights reserved. Page 2

3 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 Copyright 2013, Oracle. All rights reserved. Page 3

4 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 Copyright 2013, Oracle. All rights reserved. Page 4

5 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 Copyright 2013, Oracle. All rights reserved. Page 5