This course provides a foundational understanding of analytics engineering, focusing on building end-to-end data solutions. It teaches essential skills for designing, implementing, and optimizing analytics systems, from data ingestion to visualization. The course will enhance your ability to apply best practices in data modeling, cloud analytics, and collaborative workflows, all while building scalable and reliable data platforms. With the guidance of industry experts, learners will gain the knowledge to transition from data analysis to analytics engineering.
Fundamentals of Analytics Engineering
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Design and implement data pipelines from ingestion to serving data
Apply best practices for data modeling and schema design
Scale data processing using cloud-based analytics platforms
Details to know
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Recently updated!
March 2026
Assessments
14 assignments
Taught in English
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There are 14 modules in this course
In this section, we explore the role of analytics engineers in modern data strategies, comparing ETL and ELT workflows and clarifying their distinct responsibilities from data analysts and engineers.
What's included
2 videos1 reading1 assignment
In this section, we explore the Modern Data Stack (MDS), its key differentiators from legacy systems, and its advantages and limitations for data management.
What's included
1 video2 readings1 assignment
In this section, we will learn about data ingestion pipelines, including eight essential steps and scalable solutions.
What's included
1 video7 readings1 assignment
In this section, we examine the evolution of data warehousing, cloud migration, and key components of cloud data warehouses, focusing on practical applications and market leaders.
What's included
1 video10 readings1 assignment
In this section, we examine data modeling techniques, focusing on normalization, dimensional modeling, and data vault approaches to ensure data integrity, scalability, and efficient system design.
What's included
1 video10 readings1 assignment
In this section, we explore data transformation techniques, scalable data modeling, and best practices to enhance data usability and support analytics.
What's included
1 video6 readings1 assignment
In this section, we explore how data becomes useful through dashboarding, BI tools, and data products, emphasizing accessibility, trust, and actionable insights for effective decision-making.
What's included
1 video5 readings1 assignment
In this section, we explore practical analytics engineering by implementing ELT workflows with Airbyte Cloud, modeling data using dbt Cloud, and visualizing insights with Tableau to solve real-world business problems.
What's included
1 video9 readings1 assignment
In this section, we explore data quality challenges in source systems, pipelines, and governance, and introduce observability, data catalogs, and semantic layers as solutions to ensure reliable and consistent data.
What's included
1 video8 readings1 assignment
In this section, we explore version control, coding standards, and code reviews to enhance team collaboration and ensure code quality and maintainability in shared environments.
What's included
1 video12 readings1 assignment
In this section, we will learn about data orchestration, CI/CD pipelines, and their implementation in dbt Cloud.
What's included
12 readings1 assignment
In this section, we explore translating business needs into analytics, scoping use cases with stakeholders, and ensuring adoption through incremental delivery and communication.
What's included
2 readings1 assignment
In this section, we will learn about data governance, ownership, quality, and its role in data management.
What's included
4 readings1 assignment
In this section, we review core analytics insights and explore strategies for career growth, emphasizing continuous learning, networking, and portfolio development for long-term success.
What's included
1 reading1 assignment
Instructor
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Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.
More questions
Financial aid available,