DAU - CDAT

DAU Certified Data & Analytics Tester

설명

Data & Analytics United - Certified Data & Analytics Tester (DAU - CDAT) is a 2-day interactive certification course to help you develop the skills and knowledge to survive as a tester in a data and analytics environment. Participants will learn how to utilize embedded structured testing in order to reach and improve the quality goals in their everyday work.

A Certified Data & Analytics Tester is not only able to define a vision and test strategy, but also apply it to an efficient test approach in data-oriented environments and projects. They are also familiar with the essential test specification techniques that are required in data and analytics projects.

Successful DAU - CDAT participants are able to distinguish between different data quality attributes, measure these differences and apply essential data profiling techniques. They will also understand the intricate privacy aspects of the data that is associated with the given test environments and apply this to their data and analytics testing

Chapter 1: Introduction to Business Intelligence (BI) and Data & Analytics (DA)

Chapter 2: Data & Analytics Testing Strategy

Chapter 3: Test Techniques

Chapter 4: BI Testing

Chapter 5: Data Quality

Chapter 6: Environmental Needs

대상 사용자

DAU Certified Data & Analytics Tester has been designed for test engineers, test coordinators, business analysts, data leads, data warehouse developers and business intelligence consultants.

요구 사항

Although there aren't any mandatory prerequisites:

for Testers and QA Professionals: you will get a lot more from the course if you have already hold the ISTQB Certified Tester Foundation Level (CTFL) certificate - as this course will not cover the fundamentals and terminology of testing. This practical certification course will take your unterstanding of testing a step further and provide you with a variety of approaches and techniques that are essential for data and analytics testing.
for Business Analysists and BI Consultants: we recommend that you already have experience dealing with (big) data.