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Certified Data & Analytics Tester

Accredited learning for the Data & Analytics United - Certified Data & Analytics Tester (DAU-CDAT) exam

istqb-certification

Designed for test engineers, test coordinators, managers, business analysts, data leads, data warehouse developers and BI consultants, this dynamic and interactive class is designed to help students learn the practical skills necessary to effectively work with (big) data.

Full Description and Outline

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Mode
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Price
Jun 08—Jun 09, 2025
Public Classroom
Seattle, WA
Seattle, WA at AI Con USA
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Select a learning mode button (Public, Live Virtual, etc.) for pricing, details, and a downloadable fact sheet.
Description
  • 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
Motivated to create awareness, knowledge and experience in Data & Analytics testing among people and organizations all over the world, Data & Analytics United is a Special Interest Group supported by the team at Brightest.

Questions? 929.777.8102 [email protected]
Course Outline
Introduction to Business Intelligence (BI) and Data & Analytics (DA)
Business Intelligence 
Challenges when turning corporate data into information 
Data Warehouse
Data Mart 
Data Lake 
Data Analytics
Big Data 
Data Mining 
OLTP vs OLAP
Reporting and Data Visualization 
Data Modeling 
The ETL-Process 
Internationalization and Localization 
 
Data & Analytics Testing Strategy
Testing and Test Methodologies
BI & DA Testing in a traditional approach
BI & DA Testing in an agile approach
Risk based Testing in a BI & DA environment
Testing Roles and Skills
Set-up a test-strategy and approach in a BI environment
Data & Analytics Test Techniques 
What are test techniques
Different techniques
Mapping techniques on a BI & DA Environment
 
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
 

 

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✓ = Guaranteed to Run
Dates
Mode
Location
Price
Jun 08—Jun 09, 2025
Public Classroom
Seattle, WA
Seattle, WA at AI Con USA
Request a Quote
ATTEND
Download Fact Sheet
Course Duration: 2 Days
Description
  • 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, 

Questions? 929.777.8102 [email protected]
Course Outline
Introduction to Business Intelligence (BI) and Data & Analytics (DA)
Business Intelligence 
Challenges when turning corporate data into information 
Data Warehouse
Data Mart 
Data Lake 
Data Analytics
Big Data 
Data Mining 
OLTP vs OLAP
Reporting and Data Visualization 
Data Modeling 
The ETL-Process 
Internationalization and Localization 
 
Data & Analytics Testing Strategy
Testing and Test Methodologies
BI & DA Testing in a traditional approach
BI & DA Testing in an agile approach
Risk based Testing in a BI & DA environment
Testing Roles and Skills
Set-up a test-strategy and approach in a BI environment
Data & Analytics Test Techniques 
What are test techniques
Different techniques
Mapping techniques on a BI & DA Environment
 
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 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.
 
Class Fee Includes
• Tuition
• Course notebook
• Letter of completion
Instructors
Armando Dörsek

Armando Dörsek

Armando Dörsek has more than two decades of experience in the field of software development, operations, and human development. He has first-hand experience in testing data warehouse and analytics projects and serves as a Test Consultant and Quality Manager in large-scale projects in the Netherlands and in international programs including...Learn More

Rogier Ammerlaan

Rogier Ammerlaan

Rogier Ammerlaan has more than 20 years of experience in the financial banking and technical automation industry, working for a number of Dutch and international companies specializing in test process improvement (TPI and TMM) and in developing complex test strategies. He holds the ISTQB CTFL credential and is a certified...Learn More

Don't see a date that fits your schedule? Contact us for scheduling options at 929.777.8102
Download Fact Sheet
Price: $1,495 USD
Course Duration: 3 Days
Description
  • 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
Motivated to create awareness, knowledge and experience in Data & Analytics testing among people and organizations all over the world, Data & Analytics United is a Special Interest Group supported by the team at Brightest.

Questions? 929.777.8102 [email protected]
Course Outline
Introduction to Business Intelligence (BI) and Data & Analytics (DA)
Business Intelligence 
Challenges when turning corporate data into information 
Data Warehouse
Data Mart 
Data Lake 
Data Analytics
Big Data 
Data Mining 
OLTP vs OLAP
Reporting and Data Visualization 
Data Modeling 
The ETL-Process 
Internationalization and Localization 
 
Data & Analytics Testing Strategy
Testing and Test Methodologies
BI & DA Testing in a traditional approach
BI & DA Testing in an agile approach
Risk based Testing in a BI & DA environment
Testing Roles and Skills
Set-up a test-strategy and approach in a BI environment
Data & Analytics Test Techniques 
What are test techniques
Different techniques
Mapping techniques on a BI & DA Environment
 
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 Schedule
Day 1: 12:00pm-5:00pm ET/9:-0am-2:00pm PT
Day 2: 12:00pm-5:00pm ET/9:-0am-2:00pm PT
Day 3: 12:00pm-5:00pm ET/9:-0am-2:00pm PT
Times represent the typical daily schedule. Please confirm class schedule at registration.
 
Class Fee Includes
  • Easy course access: Attend training right from your computer. Easy and quick access fits today’s working style and eliminates expensive travel and long days in the classroom.
  • Live, expert instruction: Instructors are sought-after practitioners, highly-experienced in the industry who deliver a professional learning experience in real-time.
  • Valuable course materials: Courses cover the same professional content as our classroom training, and students have direct access to valuable materials.
  • Rich virtual learning environment: A variety of tools are built in to the learning platform to engage learners through dynamic delivery and to facilitate a multi-directional flow of information.
  • Hands-on exercises: An essential component to any learning experience is applying what you have learned. Using the latest technology, your instructor can provide hands-on exercises, group activities, and breakout sessions.
  • Real-time communication: Communicate real-time directly with the instructor. Ask questions, provide comments, and participate in the class discussions.
  • Peer interaction: Networking with peers has always been a valuable part of any classroom training. Live Virtual training gives you the opportunity to interact with and learn from the other attendees during breakout sessions, course lecture, and Q&A.
  • Small class size: Live Virtual courses are limited in small class size to ensure an opportunity for personal interaction.
Instructors
Armando Dörsek

Armando Dörsek

Armando Dörsek has more than two decades of experience in the field of software development, operations, and human development. He has first-hand experience in testing data warehouse and analytics projects and serves as a Test Consultant and Quality Manager in large-scale projects in the Netherlands and in international programs including...Learn More

Rogier Ammerlaan

Rogier Ammerlaan

Rogier Ammerlaan has more than 20 years of experience in the financial banking and technical automation industry, working for a number of Dutch and international companies specializing in test process improvement (TPI and TMM) and in developing complex test strategies. He holds the ISTQB CTFL credential and is a certified...Learn More

Bring this course to your team at your site. Contact us to learn more at 929.777.8102.

✓ = Guaranteed to Run
Dates
Mode
Location
Price
Call to Schedule
Anytime
On-Site / Private
Your Location
Your Location
Request a Quote
Contact Us
Download Fact Sheet
Course Duration: 2 Days
Description
  • 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
Motivated to create awareness, knowledge and experience in Data & Analytics testing among people and organizations all over the world, Data & Analytics United is a Special Interest Group supported by the team at Brightest.

Questions? 929.777.8102 [email protected]
Course Outline
Introduction to Business Intelligence (BI) and Data & Analytics (DA)
Business Intelligence 
Challenges when turning corporate data into information 
Data Warehouse
Data Mart 
Data Lake 
Data Analytics
Big Data 
Data Mining 
OLTP vs OLAP
Reporting and Data Visualization 
Data Modeling 
The ETL-Process 
Internationalization and Localization 
 
Data & Analytics Testing Strategy
Testing and Test Methodologies
BI & DA Testing in a traditional approach
BI & DA Testing in an agile approach
Risk based Testing in a BI & DA environment
Testing Roles and Skills
Set-up a test-strategy and approach in a BI environment
Data & Analytics Test Techniques 
What are test techniques
Different techniques
Mapping techniques on a BI & DA Environment
 
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 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.
 
Class Fee Includes
• Tuition
• Course notebook
• Letter of completion
Instructors
Armando Dörsek

Armando Dörsek

Armando Dörsek has more than two decades of experience in the field of software development, operations, and human development. He has first-hand experience in testing data warehouse and analytics projects and serves as a Test Consultant and Quality Manager in large-scale projects in the Netherlands and in international programs including...Learn More

Rogier Ammerlaan

Rogier Ammerlaan

Rogier Ammerlaan has more than 20 years of experience in the financial banking and technical automation industry, working for a number of Dutch and international companies specializing in test process improvement (TPI and TMM) and in developing complex test strategies. He holds the ISTQB CTFL credential and is a certified...Learn More

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