Introduction of Data Engineering in KNIME

The L4-DE: Data Engineering in KNIME Analytics Platform training is designed for data engineers and analysts who want to develop, manage, and optimize data pipelines using KNIME. This course covers data integration, transformation, performance optimization, automation, and best practices for building scalable data workflows. Participants will gain hands-on experience in handling large datasets, working with databases, and automating ETL processes in KNIME.

Prerequisites

• Familiarity with KNIME Analytics Platform
• Basic knowledge of SQL, databases, and data transformation
• Understanding of ETL concepts and data workflows

Table of Contents

1. Introduction to Data Engineering in KNIME

• 1.1 Overview of KNIME for Data Engineering
• 1.2 Key Features and Components
• 1.3 Understanding Data Pipelines and Workflow Automation

2. Data Access and Integration

• 2.1 Connecting to Databases (SQL, NoSQL)
• 2.2 Working with Cloud Storage and APIs
• 2.3 Handling Structured and Unstructured Data

3. Data Transformation and Processing

• 3.1 Data Cleaning and Preprocessing
• 3.2 Advanced Data Manipulation Techniques
• 3.3 Handling Missing Data and Outliers

4. Performance Optimization in KNIME

• 4.1 Workflow Optimization Strategies
• 4.2 Parallel Processing and Execution Performance
• 4.3 Memory Management and Caching

5. Automation and Workflow Orchestration

• 5.1 Scheduling and Automating Workflows
• 5.2 KNIME Server for Workflow Deployment
• 5.3 Monitoring and Managing Data Pipelines

6. Data Engineering Best Practices

• 6.1 Version Control and Collaboration in KNIME(Ref: L4-TP: Text Processing in KNIME Analytics Platform)
• 6.2 Ensuring Data Quality and Governance
• 6.3 Logging, Debugging, and Error Handling

7. Real-World Use Cases and Hands-On Scenarios

• 7.1 Building Scalable ETL Pipelines
• 7.2 Integrating Machine Learning Models into Data Pipelines
• 7.3 Case Studies in Finance, Healthcare, and E-commerce

8. Certification Preparation and Final Assessment

• 8.1 Key Topics for Certification
• 8.2 Practice Exercises and Mock Tests
• 8.3 Final Review and Capstone Project

Conclusion

This L4-DE: Data Engineering in KNIME course equips participants with the skills to build, optimize, and automate data pipelines using KNIME Analytics Platform. By mastering data integration, transformation, and workflow automation, learners will be well-prepared for real-world data engineering challenges and certification exams.

Reference