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.
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Automate Data Onboarding, Validate, and Govern
本课程是 GenAI Deployment & Governance 专项课程 的一部分

位教师:John Whitworth
包含在 中
您将学到什么
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
您将获得的技能
- Expense Management
- AI Enablement
- Extract, Transform, Load
- Scalability
- Data Management
- Data Maintenance
- MLOps (Machine Learning Operations)
- Automation
- Data Storage
- Data Quality
- Metadata Management
- Data Processing
- Compliance Management
- General Data Protection Regulation (GDPR)
- Data Storage Technologies
- Data Governance
- Data Architecture
- Data Validation
- Data Integration
要了解的详细信息
了解顶级公司的员工如何掌握热门技能

积累特定领域的专业知识
- 向行业专家学习新概念
- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 获得可共享的职业证书

该课程共有3个模块
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.
涵盖的内容
2个视频1篇阅读材料2个作业
Learners will master the systematic evaluation of data retention policies to ensure regulatory compliance while optimizing storage costs through strategic lifecycle management.
涵盖的内容
3个视频2篇阅读材料2个作业
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.
涵盖的内容
2个视频2篇阅读材料3个作业
获得职业证书
将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。
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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.
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.
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.
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¹ 本课程的部分作业采用 AI 评分。对于这些作业,将根据 Coursera 隐私声明使用您的数据。








