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PRC1006 – Data & Analytics United: Certified Data & Analytics Tester (CDAT)

Description

PRC1006 – Data & Analytics United: Certified Data & Analytics Tester (CDAT)

Overview

The Certified Data & Analytics Tester (CDAT) program is a professional certification designed to validate participants’ competency in testing data-driven systems, analytics platforms, and reporting solutions. As organizations increasingly rely on data for decision-making, ensuring data accuracy, integrity, reliability, and usability has become critical. 

This program focuses on the principles, techniques, and best practices required to validate data pipelines, analytics applications, and business intelligence (BI) systems. Participants will gain structured knowledge in data testing fundamentals, data quality validation, analytics testing approaches, test data management, and governance considerations. The certification ensures that candidates are capable of validating data and analytics solutions in alignment with organizational objectives and regulatory requirements. 

  • 92% positive reviews (176)
  • 2012 students

This program can be tailored to your specific business needs.

A little bit of personalization goes a long way. Ask us for a no-obligation Training Needs Analysis (TNA) so we can tailor this, or any other CSG program to meet your learning outcomes.

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Objectives

At the end of the training, participants would be able to:

  • Understand the fundamentals of data and analytics testing
  • Apply data validation and data quality testing techniques
  • Test analytics reports, dashboards, and insights for accuracy and consistency
  • Validate data pipelines, transformations, and system integrations
  • Apply governance, risk, and compliance principles in data testing
  • Support reliable and trustworthy data-driven decision-making

4 Days

  • Data Testers
  • QA Engineers involved in data and analytics testing
  • BI and Analytics Testers
  • Data Analysts involved in validation and quality assurance
  • Professionals supporting data-driven systems

Modules:

Module 1: Introduction to Data & Analytics Testing
  • Overview of data and analytics systems
  • Role of testing in data-driven environments
  • Differences between application testing and data testing
  • Types of data (structured, semi-structured, unstructured)
  • Databases, data warehouses, and data lakes
  • Data flows and end-to-end data pipelines
  • Accuracy, completeness, consistency, timeliness, and validity
  • Defining data quality rules and checks
  • Source-to-target validation techniques
  • Transformation logic validation
  • Data reconciliation methods
  • Testing dashboards and analytical reports
  • KPI and metric validation
  • Managing aggregation and calculation logic
  • Test data requirements for analytics testing
  • Data sampling techniques
  • Managing large datasets for effective testing
  • Data privacy and protection considerations
  • Regulatory and compliance requirements
  • Auditability and traceability in data systems
  • End-to-end data testing scenarios
  • Defect identification, management, and reporting
  • Best practices for continuous data quality assurance

Program Methodology

  • Hands-on Activities: Practical exercises to reinforce theoretical concepts.
  • Group Discussions: Opportunities for peer-to-peer learning and exchange of ideas.
  • Role Plays: Simulations of realistic situations to build practical skills.
  • Feedback Sessions: Reviews and reflections to encourage improvement.
  • Problem-solving Exercises: Develop critical thinking and decision-making skills.
  • Experiential Learning: Learning by doing, promoting active involvement.
  • Interactive Lectures: Engaging presentations by experts in the field.
  • Case Studies: Real-world scenarios for learners to apply their knowledge.
  • Quizzes & Tests: Regular assessments to track learning progress.

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