Data Virtualization with Denodo Platform Training Course

Duration

14 hours (usually 2 days including breaks)

Requirements

  • An understanding of data management
  • Familiarity with SQL

Audience

  • Architects
  • Developers
  • Administrators

Overview

Denodo is a data virtualization platform for managing big data, logical data warehouses, and enterprise data operations.

This instructor-led, live training (online or onsite) is aimed at architects, developers, and administrators who wish to use Denodo Platform to optimize and accelerate data management through data virtualization.

By the end of this training, participants will be able to:

  • Install and configure Denodo Platform.
  • Understand the features and architecture of Denodo Platform.
  • Understand the key concepts, benefits, and use cases for data virtualization.
  • Learn how to configure and manage the Denodo Platform server.
  • Implement data security, user access, and services authentication.
  • Apply the tools and techniques for operations monitoring and performance optimization.

Format of the Course

  • Interactive lecture and discussion.
  • Lots of exercises and practice.
  • Hands-on implementation in a live-lab environment.

Course Customization Options

  • To request a customized training for this course, please contact us to arrange.

Course Outline

Introduction

  • Denodo Platform vs TIBCO Data Virtualization
  • Overview of Denodo Platform features and architecture

Understanding Data Virtualization

  • What is data virtualization?
  • Key concepts and benefits
  • Data virtualization use cases

Getting Started

  • Installing and configuring Denodo Platform
  • Updates, deployments, and clustering
  • Connecting to databases

Server Administration and Security

  • LDAP, SSO, Kerberos
  • Authentication in data services
  • Role management
  • Database management
  • Scheduler, jobs, and handlers
  • Error analysis

Data Services and Management

  • Virtual views (basic vs derived)
  • Union and join views
  • Compound types and flatten views
  • Accessing files
  • Aggregating data
  • Data services (JSON, XML, and Web services)

Backup, Monitoring, and Performance

  • Backup and migration best practices
  • Diagnostic tool and auditing
  • Query monitor and optimizer
  • Static vs dynamic optimizer
  • Cache and memory usage
  • Resolving bottlenecks
  • High availability

Troubleshooting

Summary and Next Steps

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