Udemy – Data Architecture for Data Engineers: Practical Approaches 2024-12

Udemy – Data Architecture for Data Engineers: Practical Approaches 2024-12 Downloadly IRSpace

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Apr 18, 2025 - 18:10 Updated: Aug 17, 2025 - 18:16
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Udemy – Data Architecture for Data Engineers: Practical Approaches 2024-12
Udemy – Data Architecture for Data Engineers: Practical Approaches 2024-12

Data Architecture for Data Engineers: Practical Approaches. This course provides a comprehensive overview of data architecture concepts and techniques. You will be introduced to different types of data architecture, including data warehouses, datalakes, and the emerging datalakehouse approach. Distributed and cloud-based architectures are also explored, along with practical applications of each for different data needs. Key topics such as data modeling, data governance, and security are covered, with an emphasis on practical techniques for real-world implementation. Starting with fundamentals such as data quality, scalability, security, and cost-efficiency, we will guide you in designing robust data stacks, understanding ETL and ELT processes, and integrating batch and real-time data processing. With dedicated sections on AWS, Azure, and hybrid/multi-cloud architectures, you will gain practical insights into using cloud tools for scalable data solutions.

This course also prepares you for a career change and provides guidance on the skills, certifications, and steps to becoming a data architect. Through case studies, quizzes, and real-world examples, you will be able to make strategic architectural decisions and apply best practices across industries. By the end, you will have a comprehensive toolkit for designing and implementing effective data architectures that align with business goals and emerging data needs.

What you will learn in the Data Architecture for Data Engineers: Practical Approaches course:

  • Evaluate and select data architectures based on specific business needs and data characteristics.
  • Design data models and implement database strategies for structured and unstructured data.
  • Build scalable and fault-tolerant data stacks using ETL/ELT processes and real-time data processing.
  • Implementing cloud-based data solutions on AWS, Azure, and multi-cloud environments.
  • Distinguish between modern data architectures, including data lakes, warehouses, and lakehouses, for optimal data storage.
  • Apply best practices for data governance, security, and compliance within data architecture frameworks.
  • Analyze and select appropriate data integration and management tools for hybrid and multi-cloud strategies.
  • Career path planning from data engineer to data architect, including key skills and certifications.

This course is suitable for people who:

  • Data engineers and early-stage analysts who are looking to advance their careers by strengthening their skills in data architecture principles, design, and cloud technologies.
  • Forward-thinking data architects seeking a comprehensive and practical foundation in data architecture concepts, including data modeling, data governance, and cloud-based solutions.
  • Technology professionals in data-related roles such as business intelligence (BI) engineers, data analysts, or software engineers who want to transition into data engineering or architecture roles.
  • IT managers and team leaders looking to enhance their teams’ data capabilities and understand broader architectural decisions that impact data strategy.

Course details: Data Architecture for Data Engineers: Practical Approaches

  • Publisher:  Udemy
  • Instructor:  Manas Jain
  • Training level: Beginner to advanced
  • Training duration: 3 hours and 55 minutes
  • Number of lessons: 41

Course topics

 Data Architecture for Data Engineers: Practical Approaches

Prerequisites for the Data Architecture for Data Engineers: Practical Approaches course

  • Basic Understanding of Data Concepts: Familiarity with data structures, databases, and general data processing will make it easier to follow along with the technical aspects.
  • Knowledge of SQL and Data Storage: Some experience with SQL and an understanding of different types of data storage (eg, relational databases, cloud storage) would be helpful, though not essential.
  • Interest in Data Architecture and Cloud Platforms: Curiosity about data architecture frameworks and cloud platforms like AWS, Azure, or Google Cloud will make the course content more engaging and relevant.
  • No specific tools or advanced skills are required for beginners; the course is designed to introduce you to key concepts and guide you through practical data architecture approaches step-by-step. If you are motivated to learn and eager to apply new skills, this course is for you!

Course images

Data Architecture for Data Engineers: Practical Approaches

Sample course video

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