By completing this course, learners will be able to identify core ETL concepts, analyze data structures, apply CloverETL tools, construct metadata definitions, process JSON and XML formats, design optimized workflows, and evaluate real-world fraud detection case studies. Through a blend of foundational training and advanced projects, participants will gain hands-on expertise in building reliable data pipelines and solving complex integration challenges.
CloverETL: Design, Analyze & Optimize Workflows
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Gain insight into a topic and learn the fundamentals.
7 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Identify ETL concepts, analyze data structures, and apply CloverETL tools.
Design workflows, process JSON/XML, and validate schemas with metadata.
Build fraud detection pipelines and evaluate integration in real-world scenarios.
Skills you'll gain
Details to know
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Recently updated!
September 2025
Assessments
11 assignments
Taught in English
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There are 3 modules in this course
This module introduces learners to the fundamentals of CloverETL, focusing on the core ETL (Extract, Transform, Load) concepts, workflow structures, and the designer tools that power seamless data integration. Learners will explore how to build efficient ETL pipelines, create structured metadata, and perform basic file conversions—equipping them with the practical skills to handle diverse data sources and streamline data processing.
What's included
10 videos4 assignments1 plugin
This module dives into advanced data processing techniques using CloverETL, focusing on handling complex JSON and XML formats and mastering data mapping between sources and targets. Learners will explore how to parse and transform nested JSON data, resolve field mismatches through effective mapping, and implement XML extraction, validation, and writing workflows. By the end of the module, learners will be equipped to process hierarchical data structures, ensure schema compliance, and deliver structured outputs for seamless data integration.
What's included
9 videos3 assignments
This module introduces the Credit Card Fraud Detection (CCFD) case study in CloverETL, focusing on foundational concepts and the workflow design. Learners will explore flow diagrams, metadata editing, and dataset construction, gaining a clear understanding of how to standardize and integrate multiple data sources for fraud detection.
What's included
7 videos4 assignments
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