Qlik Talend Data Integration certification exams measure your skills to ensure that you have the knowledge to successfully implement quality projects.
This certification exam covers the knowledge and skills necessary to use cloud-based and on-premises services to monitor and assess data quality and to analyze and align data for accuracy to identify and resolve data integrity issues.
Certification Exam details
Duration: 90 minutes
Number of questions: 45
Passing score: 65%
Exam content is updated periodically. The number and difficulty of questions may change. The passing score is adjusted to maintain a consistent standard.
Recommended experience
At least six months of experience using Talend products Experience with data preparation, data stewardship, data inventory, and data analysis in Talend Cloud Thorough knowledge of data processing and management Familiarity with data quality features within Talend Studio
Preparation
To prepare for this certification exam, Qlik recommends:
Taking the Talend Cloud Trust Score, Talend Cloud Data Preparation, Talend Cloud Data Stewardship, and Talend Data Quality Essentials learning paths Studying the material in the Talend Data Quality Certified Implementer preparation training module Reading the product documentation:
You should be comfortable using the Qlik Talend Help Center to search for documents that correspond with the exam topics Reading Qlik Community knowledge base articles
For more information about the recommended learning plans, go to the Qlik Learning Catalog.
Badge
After passing this certification exam, you are awarded the Talend Data Quality Certified Implementer badge. To learn more about the criteria to earn this badge, refer to the Qlik Badging program page.
Certification Exam topics
Work with data using Talend Cloud Data Inventory
Define Talend Cloud Data Inventory in context Differentiate between the supported connection types Access datasets using data crawler Access datasets using an API Describe the advantages and disadvantages of applying semantic types (DP, DI, and DS) Describe the dimensions used to calculate data trust Use Talend Trust Score
Work with data using Talend Cloud Data Preparation
Define Talend Cloud Data Preparation in context Prepare data using Data Inventory and Data Preparation Manage Data Preparation components in Talend Studio Transform raw data into suitable analysis in Data Preparation
Work with data using Talend Cloud Data Stewardship
Define Talend Cloud Data Stewardship in context Differentiate between predefined roles and role-based access Manage campaigns and tasks in Talend Cloud Data Stewardship Build resolution campaigns Manage data quality rules in Data Stewardship
Overview of data quality
Define data quality in context Differentiate between the types of data quality analyses Monitor data movement and automate data quality checks (Business rules) Perform data reconciliations between source and target
Data quality cleansing and transformations
Use data quality components (Profiling, Standardization, Matching, and Consolidations) Implement data quality transformations Establish data auditing processes Describe the use of data privacy components
