Are you interested in becoming a highly skilled Data Engineer in the fast-growing data industry? Look no further, because this comprehensive training program will equip you with the knowledge and skills needed to excel in this field. Let's dive into the modules and topics covered in this program:

Module 1: Overview of the Data Industry and Data Engineer

- Gain an understanding of the data industry and its significance in today's world.

- Explore the role and importance of Data Engineers.

- Learn about the future development of Data Platforms.

Module 2: Building the Foundation

- Master programming fundamentals with Python, an essential language for data engineering.

- Familiarize yourself with the Linux Operating System, commonly used in data engineering.

- Explore Docker and its applications in data engineering, including containerization.

Module 3: Data Sources and Data Stores

- Learn SQL, including SQL Server, Postgre, and MySQL, for efficient data storage and retrieval.

- Explore NoSQL databases like MongoDB, which are widely used for handling unstructured data.

- Discover how to approach and process data from systems like SAP, Oracle, and Odoo.

Module 4: Data Integration and Data Pipeline

- Dive into the world of web scraping and learn how to extract data from websites.

- Understand Application Programming Interfaces (APIs) and their role in data integration.

- Learn how to manage workflows with Airflow, a powerful tool for orchestrating data pipelines.

Module 5: Cloud Computing for Data Engineers

- Get familiar with cloud computing concepts and understand their relevance in data engineering.

- Explore popular cloud platforms like AWS, Azure, and GCP.

- Learn how to deploy and manage data engineering workflows and optimize costs in the cloud (specifically Google Cloud Platform).

Module 6: Big Data Technologies

- Understand the Hadoop ecosystem, a powerful framework for distributed storage and processing of big data.

- Explore Spark, another powerful framework for big data processing and analytics.

- Discover CDAP, a Google BigData tool for managing and processing large datasets.

Module 7: Streaming and Real-time Processing

- Learn about real-time data processing and streaming and their importance in today's data-driven world.

- Dive into Apache Kafka, a popular tool for building streaming systems.

Module 8: Data Warehouse

- Understand the concepts of data warehousing and its significance in storing and analyzing data.

- Learn how to design and implement data warehouses for efficient data management.

Module 9: Data Visualization

- Master PowerBI, a popular data visualization tool used for creating interactive dashboards and reports.

- Understand the DAX language for advanced calculations and data modeling.

- Explore different types of charts and their applications in visualizing data.

Module 10: Data Quality and Data Governance

- Learn about data quality frameworks and techniques for ensuring data accuracy and consistency.

- Understand the importance of data governance in managing and securing data.

Module 11: Final Project

- Apply your skills and knowledge gained throughout the program in a real-world project.

- Build a business intelligence system or a big data system to showcase your expertise.