Do I need to apply? What are the admission criteria?

No. This Course accepts all applicants regardless of experience and specific background.

What are the prerequisites for enrollment?

Successful learners should have intermediate Python skills including: Data structures and data types, Control flow using for, while, and if statements, Jupyter notebooks, pandas and NumPy, Machine learning frameworks, Calculus, and Linear algebra.

How is this course structured?

This course is comprised of content and curriculum to support one project. We estimate that students can complete the program in one month. The project will be reviewed by the Udacity reviewer network and platform. Feedback will be provided and if you do not pass the project, you will be asked to resubmit the project until it passes.

How long is this course?

Access to this course runs for the length of time specified in the payment card above. If you do not graduate within that time period, you will continue learning with month to month payments. See the Terms of Use and FAQs for other policies regarding the terms of access to our programs.

Can I switch my start date? Can I get a refund?

Please see the Udacity Program Terms of Use and FAQs for policies on enrollment in our programs.

What software and versions will I need in this course?

Learners will need access to the internet and a 64 bit computer. No additional software or hardware is required.

Introduction to Data Governance

Course

Learn how to design a data governance solution that meets an enterprise’s needs.

Enroll Now

Estimated time
1 month
Enroll by
June 14, 2023
Get access to classroom immediately on enrollment
Skills acquired
Master Data Management, Data Quality Assessment, Metadata Management

What You Will Learn

Introduction to Data Governance
1 month to complete
Learn how to design a data governance solution that meets a company’s needs. First, learn about the different types of metadata and how to build a metadata management system, enterprise data model, and enterprise data catalog. Next, dive deep into data profiling, remediation options for data quality, data quality scores, thresholds, dashboards, exception, and data trend reports. Finally, learn the concepts of master data, golden record creation, master data management architectures, and master data governance processes.
Prerequisite knowledge
Basic SQL, ETL, Relational Database Basics
1. Introduction to Data Governance
  Understand what data governance is and its importance and learn about the different disciplines of data governance. Understand the different stakeholders involved in data governance projects.
2. Metadata Management
  Understand the different types of metadata as well as the components and capabilities of a metadata management system. Create conceptual and logical enterprise data models and create an enterprise data catalog.
3. Data Quality Management
  Perform data profiling using various techniques using data quality dimensions. Identify remediation options for data quality issues. Measure data quality using data quality scores and thresholds. Monitor data quality using dashboards, exception, and trend reports.
4. Master Data Management
  Understand the concepts of master data and golden record. Understand different types of master data management architectures. Create a golden record using various match and merge techniques. Understand data governance processes for authoring, monitoring, and approval of master data.
5. Course Project: Data Governance at SneakerPark
  Implement data governance solutions for an online shoe reseller to better manage their data now and in the future. Create an enterprise data model that provides a holistic view of all the data in their systems. Next document the metadata in an enterprise data catalog and profile the data in their systems to identify data quality issues, suggest remediation strategies for each of these issues, and design a data quality dashboard. Finally, you will sketch out a proposed MDM implementation architecture, define a set of matching rules for the creation of customer and item master data, and define the data governance roles and responsibilities that are necessary to oversee this data governance initiative.

All Our Courses Include

Real-world projects from industry experts
With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.
Real-time support
On demand help. Receive instant help with your learning directly in the classroom. Stay on track and get unstuck.
Workspaces
Validate your understanding of concepts learned by checking the output and quality of your code in real-time.
Flexible learning program
Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.

Course offerings

Class content
- Real-world projects
- Project reviews
- Project feedback from experienced reviewers
Student services
- Student community
- Real-time support

Succeed with personalized services.

We provide services customized for your needs at every step of your learning journey to ensure your success.

Experienced Project Reviewers
Real-Time Support

Get timely feedback on your projects.

Personalized feedback
Unlimited submissions and feedback loops
Practical tips and industry best practices
Additional suggested resources to improve

1,400+
project reviewers
2.7M
projects reviewed
88/100
reviewer rating
1.1 hours
avg project review turnaround time

Learn with the best.

Vijaya Nelavelli
Founder & Principal Data Architect
Vijaya is the Founder and Principal Data Architect for Great View Data Corp., which provides Data Architecture consulting and implementation services. Vijaya has extensive experience with creating architecture strategy and roadmaps, establishing frameworks and best practices, and Data Management.