Description
Data Engineering Design Patterns. This course explores data engineering design patterns for transforming prototype projects into data products ready for real-world, commercial environments. This course is designed for those who want to move beyond simple prototype projects and gain the knowledge to design data products ready for real-world, operational environments. The course includes programming-focused lessons, hands-on exercises, and live debugging sessions to enable immediate implementation of data design principles in projects. In real-world work environments, data engineers must be able to manage complex queries, perform performance optimizations, and make informed design decisions. Learning how to measure features and analyze the differences between different design approaches is a skill that requires structured training and is essential for anyone building sustainable, maintainable data pipelines. Building a simple data pipeline that works is within everyone’s reach, but ensuring that it produces the right, maintainable data requires a thorough understanding of how to implement it to meet business needs. This course provides a step-by-step guide to solving business problems using technology to enable data-driven decision-making for any organization. Students learn how to demonstrate expertise by focusing on business implications and guide project stakeholders from simple requests to intuitive data products for decision-making. By learning key data engineering design patterns and how to coordinate them, individuals can build data pipelines that process and deliver data in a timely, high-quality, and cost-effective manner.
What you will learn
- Data Warehousing : Building tables that data analysts actually want to use in reports.
- Data Pipeline Design : Intelligent management of late events, backfills , and system errors.
- Data Flow or Medallion Architecture : Standardizing how data moves and processes throughout the system.
- Data Quality : Ensuring the complete accuracy and completeness of the data provided to the organization’s stakeholders.
- Scheduling and Orchestration Patterns : Creating data pipelines that produce outputs just in time.
- Data Storage Patterns : Choosing the best storage strategy to make analytics faster and more cost-effective.
- Distributed Data Processing Patterns : Reliable scalability of the data pipeline as data volumes grow.
This course is suitable for people who:
- Data Specialists : Those who have basic SQL skills and want to design data pipelines from scratch.
- Junior Data Engineers : Individuals looking to learn advanced design patterns to advance their careers.
- Data Analysts : Individuals who wish to develop their technical knowledge in the field of data infrastructure and architecture.
- Software developers : Those who plan to enter the field of data engineering and build data-based products.
- Career seekers: People who want to achieve high-paying career opportunities by focusing on business outcomes and solving real-world problems for organizations.
Data Engineering Design Patterns Course Details
- Publisher: startdataengineering
- Instructor: Joseph Machado
- Training level: Beginner to advanced
- Training duration: 13 hours and 15 minutes
- Number of lessons: 60
Course headings
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: None
Quality: 1080p
Download link
Rapidgator link
File(s) password: www.downloadly.ir
File size
3.4 GB