Master Data Extraction, Transformation, and Loading (ETL) Processes
About the course
ETL (Extract, Transform, Load) is a crucial process in data engineering that enables businesses to integrate, clean, and prepare data for analytics and decision-making. This course provides a comprehensive understanding of ETL processes, covering data extraction, transformation techniques, data loading, automation, and best practices.
Led by Kumar, an expert mentor with over 10 years of real-time industry experience, this course covers end-to-end ETL solutions. Whether you are a data engineer, database professional, or business intelligence analyst, this course will help you build expertise in data pipelines, ETL automation, and cloud-based ETL frameworks.
What is ETL?
ETL is a process used in data warehousing and data integration that consists of three main phases:
Understanding ETL Concepts & Workflows – Learn data extraction, transformation, and loading principles.
Building ETL Pipelines – Create robust data pipelines using industry-standard ETL tools.
ETL Automation & Scheduling – Implement workflows for efficient data movement.
Data Cleaning & Transformation – Apply cleansing, mapping, and enrichment techniques.
Working with ETL Tools – Hands-on experience with SSIS, Talend, Apache NiFi, and Informatica.
Cloud ETL & Big Data Integration – Implement ETL in cloud environments like AWS Glue, Google Dataflow, and Azure Data Factory.
What will you learn
This course covers everything from ETL fundamentals to advanced data integration techniques. By the end of the course, you’ll be proficient in:
Understanding ETL Concepts & Workflows – Learn data extraction, transformation, and loading principles.
Building ETL Pipelines – Create robust data pipelines using industry-standard ETL tools.
ETL Automation & Scheduling – Implement workflows for efficient data movement.
Data Cleaning & Transformation – Apply cleansing, mapping, and enrichment techniques.
Working with ETL Tools – Hands-on experience with SSIS, Talend, Apache NiFi, and Informatica.
Course content
The course is structured into comprehensive modules that ensure a step-by-step learning approach.
Importance of ETL in Data Warehousing
ETL vs. ELT: Understanding Key Differences
Common ETL Use Cases in Enterprises
Connecting to Databases (SQL, NoSQL, Cloud APIs)
Extracting Data from Flat Files (CSV, JSON, XML)
Real-Time Data Streaming (Kafka, Spark, Flume)
Data Normalization & Standardization
Handling Missing Data & Duplicates
Data Mapping & Schema Design
Aggregation & Filtering Techniques
Loading Data into Relational Databases
ETL Performance Optimization
Incremental vs. Full Load Strategies
SSIS (SQL Server Integration Services) Basics
Talend & Apache NiFi Workflows
Implementing Cloud ETL (AWS Glue, Azure Data Factory, Google Dataflow)
Scheduling & Monitoring ETL Jobs
Handling Large-Scale Data Processing
ETL Security & Compliance
Real-World ETL Projects in Finance, Healthcare, and E-Commerce
What will you learn
✨ Learn from Industry Expert: Kumar, with 10+ years of real-time experience, will guide you through practical applications and real-world scenarios.
✨ Hands-On Learning: Practical assignments and case studies ensure an in-depth understanding.
✨ Comprehensive Curriculum: Covers beginner to advanced concepts with step-by-step explanations.
✨ Career-Oriented Training: Gain skills that boost your resume and job prospects.
About the Mentor
This course is mentored by Kumar, a highly experienced Data Engineer with over 10 years of real-time industry experience. Kumar has worked on various ETL and data integration projects across industries, including finance, healthcare, e-commerce, and supply chain management. His expertise includes data pipeline development, ETL automation, cloud ETL solutions, and performance tuning.
Having trained over 5,000 professionals, Kumar has a proven track record of mentoring students and professionals to master ETL processes and secure high-paying jobs in the industry. His real-world insights and project-based training approach ensure that learners gain practical exposure to industry challenges and solutions.
Data Warehouse
Gain expertise in data warehousing, including dimensional modeling, OLAP, cloud data storage, and performance tuning. This course is perfect for BI professionals and data engineers.
