Sunday, June 8, 2025 - 8:30am to Monday, June 9, 2025 - 5:00pm
Certified Data & Analytics Tester
- Explore the specific aspects of testing in a BI & DA environment and how these compare to traditional testing
- Gain insight in and learn to apply different test techniques in a BI & DA environment
- Understand the difference between quality attributes for system requirements and the specific quality attributes applied to data environments
- Understand and assess risk analysis and how to apply this in a BI & DA environment given e specific aspects of the environment
- Understand the effects of privacy and data protection regulations for testing in DA projects
As the prioritization of data grows, so does the importance of test and quality in supplying and evaluating reliable, complete, and continuous on-time information delivery. This dynamic and interactive course is designed to help students learn the practical skills necessary to fully understand the complexity and elements in a Business Intelligence (BI) & Data Analytics (DA) environment and the specific aspects of testing in a BI & DA environment.
Throughout this course, participants gain insights in the different skillsets required and the diversity of test roles/skills in a BI & DA environment and learn to apply different test techniques specific to this environment. They also gain valuable insights about the different test aspects of a BI & DA environment compared to traditional testing, e.g., testing of transformations, completeness, and visualizations.
Participants discover the differences between quality attributes for system requirements and the specific quality attributes applied to data environments. They also experience risk analysis and how to apply the specific aspects throughout the BA and DA environment.
DAU-CDAT participants will be able to assess the complexity of data and understand its importance in data analytics. They gain first-hand knowledge about the complexity of DTAP environments (Development, Test, Acceptance and Production) within a BI & DA environment and important awareness about the effects of privacy and data protection regulations for testing in DA projects.
Interactive exercises practice in the following:
- Establishing a Risk-based testing strategy
- Applying various test design techniques, eliciting test cases relevant for the Data & Analytics environment
- Assessing Data Completeness using basic using database routines
- Performing data profiling tasks to an example data set
- Establishing Data Quality using the correct terminology
Who Should Attend
This certification program is designed for test engineers, test coordinators, managers, business analysts, data leads, data warehouse developers and BI-consultants, and those charged with improving the quality of (big) data used in data and analytics projects. Although there are no mandatory prerequisites, please note the following recommendations:
- Test and QA professionals: ISTQB Certified Tester Foundation Level (CTFL) certificate or equivalent experiences, as this course will not cover the fundamentals and terminology of testing. This practical certification course will take your understanding of testing a step further and provide you with a variety of approaches and techniques that are essential for data and analytics testing.
- Business Analysts and BI Consultants: Previous experience with (big) data.
About Data & Analytics United
Data & Analytics United is a Special Interest Group focused on creating awareness, knowledge, and experience in Data & Analytics testing among people and organizations all over the world,
BI Testing
Reports- and Dashboards Testing
Testing of OLAP Cubes
Testing the Data Model
Testing in Data Mining
Completeness Testing
Transformation Testing
E2E testing
Data Quality
Quality
Quality Characteristics (ISO/IEC 25010)
Data Quality Characteristics
Data Profiling
Environmental Needs
Test environments according to DTAP
Multidimensional DTAP in a BI environment
Impact of Security Standards like ISO/IEC 27001 on Analytics Testing
Impact of Privacy Regulations on Testing in the Analytics Environment
Encryption methodologies for Anonymization and Pseudonymization
Common Pitfalls using Production Data
Class Daily Schedule
Sign-In/Registration 7:30 - 8:30 a.m.
Morning Session 8:30 a.m. - 12:00 p.m.
Lunch 12:00 - 1:00 p.m.
Afternoon Session 1:00 - 5:00 p.m.
Times represent the typical daily schedule. Please confirm your schedule at registration.
Training Course Fee Includes
• Tuition
• Course notebook
• Letter of completion