When will I have access to the lectures and assignments?

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Automate Data Onboarding, Validate, and Govern

This course is part of GenAI Deployment & Governance Specialization

Instructor: John Whitworth

Included with

Learn more

3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Systematic metadata analysis maintains data quality and helps control storage costs in large-scale AI environments.
Effective data retention balances regulatory compliance, business requirements, and long-term cost optimization.
Automated data onboarding ensures consistency, quality, and scalability as enterprise data volumes increase.
Proactive data governance prevents downstream issues and accelerates AI development and deployment cycles

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Build your subject-matter expertise

This course is part of the GenAI Deployment & Governance Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 3 modules in this course

Transform your approach to enterprise data governance in AI-driven environments. In today's data-intensive landscape, organizations struggle with metadata chaos, compliance gaps, and manual onboarding bottlenecks that slow AI innovation. This course empowers ML and AI professionals to tackle these critical challenges head-on.

This Short Course was created to help machine learning and artificial intelligence professionals accomplish systematic data governance that enables scalable AI operations. By completing this course, you'll be able to eliminate data redundancy through systematic metadata analysis, ensure bulletproof compliance with GDPR and industry regulations while optimizing storage costs, and implement automated workflows that transform manual data chaos into streamlined, validated pipelines. By the end of this course, you will be able to: • Analyze metadata catalogs to identify redundant or stale datasets • Evaluate data retention policies for regulatory compliance and storage cost optimization • Create standardized processes to automate data onboarding, validation, and classification This course is unique because it bridges the gap between data governance theory and practical AI operations, providing hands-on experience with real-world tools like DataHub workflows and GDPR compliance frameworks that you'll encounter in enterprise environments. To be successful in this course, you should have a background in data management concepts, basic understanding of regulatory frameworks, and familiarity with enterprise data systems.

Module details

Learners will master the systematic analysis of enterprise metadata catalogs to identify redundant datasets, assess data staleness, and implement optimization strategies that reduce storage costs while improving data quality.

What's included

2 videos1 reading2 assignments

Learners will master the systematic evaluation of data retention policies to ensure regulatory compliance while optimizing storage costs through strategic lifecycle management.

What's included

3 videos2 readings2 assignments

3 videosTotal 20 minutes

GDPR Compliance Failures and Enterprise Risk4 minutes
Regulatory Framework Analysis for Data Retention9 minutes
Cost Optimization Through Strategic Data Lifecycle Management7 minutes

2 readingsTotal 13 minutes

GDPR and Industry-Specific Retention Requirements8 minutes
Retention Policy Assessment and Documentation Framework 5 minutes

2 assignmentsTotal 18 minutes

Compliance Gap Analysis and Policy Reconciliation Project15 minutes
Regulatory Compliance Knowledge Check3 minutes

Learners will design and implement comprehensive automated data onboarding processes that ensure consistency, quality, and scalability while reducing manual overhead and accelerating AI development cycles.