Informatica Data Quality for Analysts 10.2x Course Overview

To ensure a successful learning experience in the Informatica Data Quality for Analysts 10.2x course, it is essential that participants have a foundational understanding and minimum prerequisites that include:

• Basic understanding of data management concepts, such as data quality, data profiling, and data cleansing.
• Familiarity with core database concepts, including tables, relationships, and SQL (Structured Query Language).
• An ability to navigate computer systems and software, as well as the capacity to work with files and directories.
• Some exposure to or experience with data analysis, which can be helpful in understanding the context and objectives of data quality activities.

These prerequisites are intended to provide a baseline from which students can build their skills in Informatica Data Quality. No advanced technical skills are required, and learners from various backgrounds who meet these criteria are encouraged to enroll.

Target Audience for Informatica Data Quality for Analysts 10.2x

The Informatica Data Quality for Analysts 10.2x course is designed for professionals involved in data management and quality improvement.

Job roles and audience for the course include:

• Data Analysts
• Business Analysts
• Data Quality Specialists
• Data Stewards
• Data Governance Professionals
• Informatica Developers
• Business Intelligence Professionals
• Data Management Consultants
• IT Professionals working on data projects
• Quality Assurance Engineers working with data
• Project Managers overseeing data quality initiatives

Learning Objectives - What you will Learn in this Informatica Data Quality for Analysts 10.2x?

Introduction to Learning Outcomes and Concepts:

This course equips students with a comprehensive understanding of Informatica Data Quality (IDQ) for Analysts 10.2x, focusing on the management of data quality, profiling techniques, and collaboration strategies.

Learning Objectives and Outcomes:

• Comprehend the common data quality problems and the importance of data quality services within an organization.
• Understand the data quality management process to maintain accurate and consistent data.
• Navigate effectively through the Analyst Interface of Informatica Data Quality.
• Establish connections and manage projects within the Informatica Analyst tool.
• Work with Analyst Objects and develop Mapping Specifications for data management.
• Perform data profiling to analyze the content, structure, and quality of data.
• Create and implement profiling rules and scorecards to assess data quality.
• Manage and utilize Reference Tables for maintaining data standards.
• Discover and define Data Domains using advanced data profiling techniques.
• Develop and validate rule logic, test rules, and generate Rules Mapplets for data quality improvement.
• Facilitate project collaboration with features like adding tags, comments, and ensuring effective communication between data analysts and developers.