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Oracle Enterprise Data Quality 12c: Profile, Audit and Operate Ed 1 Course Overview

Oracle Enterprise Data Quality 12c: Profile, Audit and Operate Ed 1 Course Overview

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The Oracle Enterprise Data Quality 12c: Profile, Audit and Operate Ed 1 course is a comprehensive program designed to teach learners how to ensure the accuracy, integrity, and consistency of data within their organization using Oracle's Enterprise Data Quality platform. The course covers a broad spectrum of functionalities including data profiling, auditing, transforming, exporting, automated processing, and more, which are crucial for maintaining high-quality data.

Participants will gain hands-on experience with the Enterprise Data Quality Director User Interface, learning how to set up projects, and create and manage data stores, snapshots, and processes. They will also delve into profiling data to understand trends and outliers, auditing data quality, enriching data through transformations, and configuring jobs for automated processing. Moreover, the course provides insights into real-time processing via web services, managing data interfaces, and utilizing server console functionalities for job monitoring and scheduling.

By the end of the course, learners will be proficient in employing Oracle Enterprise Data Quality tools and techniques to enhance data management, leading to better decision-making and operational efficiency within their organizations. This skill set is invaluable in today's data-driven business environments, making the course beneficial for professionals in data management roles.

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Target Audience for Oracle Enterprise Data Quality 12c: Profile, Audit and Operate Ed 1

The Oracle Enterprise Data Quality 12c course equips professionals with data quality management skills.


  • Data Analysts
  • Data Stewards
  • Database Administrators
  • Business Intelligence Specialists
  • Data Quality Managers
  • IT Managers overseeing data governance
  • Data Integration Developers
  • Data Architects
  • Data Governance Professionals
  • ETL (Extract, Transform, Load) Developers
  • Master Data Management Professionals
  • Compliance Officers dealing with data quality regulations
  • CRM (Customer Relationship Management) System Administrators
  • ERP (Enterprise Resource Planning) Data Managers


Learning Objectives - What you will Learn in this Oracle Enterprise Data Quality 12c: Profile, Audit and Operate Ed 1?

  1. Introduction: The Oracle Enterprise Data Quality 12c: Profile, Audit and Operate Ed 1 course equips students with the knowledge to manage data quality, perform audits, and operationalize data processes efficiently.

  2. Learning Objectives and Outcomes:

  • Understand the fundamentals of Oracle Enterprise Data Quality and its high-level architecture.
  • Navigate and utilize the Director User Interface, including Process Canvas, Tool Palette, and Project Browser.
  • Perform data profiling using Quickstats, Frequency, Max/Min profilers, and assess data patterns and record completeness.
  • Implement data audits with Audit Processors and understand how to use flags and branch processes based on audit results.
  • Apply data transformation techniques, such as Lookup and Return, to enrich data and use Group and Merge processors for data consolidation.
  • Learn to write and export data effectively using the Writer setup and data export configuration.
  • Configure, schedule, and manage automated processing jobs for efficient data quality operations.
  • Reuse and repurpose work by publishing processors, creating packages, and copying existing setups.
  • Gain an understanding of the Customer Data Extension Pack, its installation, and application within data quality processes.
  • Set up and test real-time data processing using web services in Enterprise Data Quality.
  • Create and utilize data interfaces for improved data interaction and integration within processes.
  • Operate the Server Console to run, schedule, and monitor jobs, and manage data quality operations with Run Profiles.
  • Explore different data sampling options to optimize data quality assessments.
  • Get an overview of Case Management functionality to support data governance and remediation efforts.

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