Learn Data Governance Workflows with Databricks Tools
Seven hours from the foundations of data governance to running governance workflows in Databricks - frameworks and policies, data quality and metadata, security and lineage, then real-world case studies.
26 short lessons: governance components and frameworks first, applied workflows and case studies second
Certificate included
Shareable on LinkedIn the day you finish
Graded, not just watched
7 assignments across the two modules
6 Lakh+learners on our Coursera courses
10+domains covered
280+courses
58+specializations
01 About the course
One course that goes from policy to platform.
Data governance is usually taught either as theory or as tooling. This one does both - the components, frameworks and roles first, then the same ideas applied inside Databricks.
2
Modules
Fundamentals to application
26
Video lessons
96 minutes of video in total
7
Assignments
Practice and graded quizzes
7h
Total learning time
Self-paced, flexible deadlines
Learn Data Governance Workflows with Databricks Tools is built to help you understand and implement efficient data governance in your organization. It starts with the key principles of data governance and the role Databricks plays in facilitating it, then goes deep into the core components - frameworks, policies, roles and regulatory considerations, alongside data quality management and metadata management.
The course is segmented into two distinct modules. Module 1 covers why data governance matters and what it is made of. Module 2 is the applied half: data management, governance workflows, cataloging and metadata, security and access control, data lineage and discovery, collaborative governance, and automation - closing on best practices and real-world case studies.
It is listed at Intermediate level with recommended experience, but prior knowledge of Databricks is not a prerequisite - which makes it workable for beginners as well as experienced professionals wanting to sharpen their governance skills.
For the people who have to make the data trustworthy.
Coursera names the audience directly: data professionals, data governance analysts, data stewards, IT managers, and anyone interested in improving their organization's data governance using Databricks.
Data professionals
You work with data every day
You already move and model data. This builds the governance knowledge around it, and shows how Databricks supports governance workflows rather than just pipelines.
Governance analysts
Governance is your actual job
Frameworks, policies, data quality and metadata management, covered as a set - plus what practical implementation looks like on a platform instead of in a document.
Data stewards
You own the quality of a domain
Learn how data quality, metadata, security and governance workflows fit together, and where cataloging and lineage make stewardship enforceable.
IT managers
You have to make it stick
Understand how governance practices and Databricks can support organizational data management - roles, responsibilities, regulatory considerations and automation.
03 What you'll learn
Four capabilities, in the order they build.
These are the four outcomes Coursera lists for the course - the first two are the foundation, the second two are the application.
Module 1
Understand data governance foundations
The essential components of data governance and its significance in modern organizations - plus the instrumental role Databricks plays, and the benefits and challenges of governing data with it.
Module 1
Manage data quality and metadata
Governance defined properly: frameworks, policies, roles and responsibilities, and regulatory and compliance considerations - then data quality management and metadata management as the two capabilities that carry it.
Module 2
Design governance workflows with Databricks
The practical applications: data management through ingestion, storage and processing; cataloging and metadata management; governance workflow design; and security and access control.
Module 2
Apply governance best practices
Data lineage and discovery, collaborative governance with notebooks and Delta Lake, automation - then best practices drawn from real-world case studies and industry-specific use cases.
1:1 coaching · optional add-on
Learn governance with someone in your corner.
A dedicated coach who does this work for a living - someone who can look at the policy you have been drafting for a week and tell you what will actually hold.
60-minute demo session · 100% refundable · no obligation to continue
Pressure-test your framework
The policy and role model you are drafting, reviewed by someone who has had to enforce one.
Your governance workflow reviewed
Not just whether it runs - whether it will survive an audit and the next reorg.
Practice beyond the quizzes
Cataloging, lineage and access-control scenarios set for you, then walked through.
Aim it at a role
Which path fits you - governance analyst, steward or data management - and what to learn next.
2,000+Industry coaches
16Domains covered
4.8/5Average coach rating
48,000+Sessions delivered
04 Syllabus
Two modules, fundamentals then application.
Coursera lists 7 hours to complete at course level, with each module at approximately 3 hours. Fully self-paced. Every module below lists its learning objectives, exactly what is inside it, and what you leave with.
26 videos7 readings7 assignments≈ 7 hoursDownload full syllabus
Learning objectives - by the end of this module you can:
Explain what data governance is and why it matters in modern organizations
Describe Databricks' role in facilitating data governance, and the benefits and challenges of it
Define data governance and its key components, and establish frameworks, policies, roles and responsibilities
Account for regulatory and compliance considerations, data quality management and metadata management
What's inside
13 videos46 min
3 readings40 min
3 assignments90 min
1 plugin15 min
Videos · 13
Introduction to the Course2 min
Career and Scope3 min
What you will learn in this lesson2 min
Introduction to Data Governance3 min
Understanding the importance of data governance in modern organizations4 min
Introduction to Databricks4 min
Benefits and challenges of implementing data governance with Databricks5 min
What you will learn in this lesson2 min
Defining data governance and its key components8 min
Establishing data governance frameworks and policies3 min
Roles and responsibilities in data governance5 min
Regulatory and compliance considerations2 min
Data quality management and metadata management2 min
Readings · 3
Further Reads on Data Governance and Databricks15 min
Learn more about Data Governance15 min
Tell us what you think!10 min
Assignments · 3
Practice Quiz - Data Governance and Databricks15 min
Practice Quiz - Data Governance15 min
Graded Quiz - Data Governance and Databricks60 min
Plugin · 1
Quick Course Check-In15 min
Topics covered
Data governance fundamentalsKey componentsFrameworks & policiesRoles & responsibilitiesRegulatory & complianceData quality managementMetadata managementIntroduction to Databricks
You leave with: a fundamental understanding of data governance and of the Databricks features that support governance initiatives.
Learning objectives - by the end of this module you can:
Manage data in Databricks across ingestion, storage and processing
Use Databricks for data cataloging and metadata management, and set up security and access control
Design governance strategies and workflows, and work with data lineage and data discovery
Collaborate on governance with notebooks and Delta Lake, automate governance processes, and apply best practices from real-world cases
What's inside
13 videos50 min
4 readings45 min
4 assignments105 min
Videos · 13
What you will learn in this lesson2 min
Data management with Databricks: Data ingestion, storage, and processing6 min
Using Databricks for data cataloging and metadata management5 min
Security and access control in Databricks3 min
What you will learn in this lesson2 min
Designing effective data governance strategies with Databricks3 min
Data lineage and data discovery in Databricks6 min
Collaborative data governance with Databricks notebooks and Delta Lake8 min
Automating data governance processes and workflows3 min
What you will learn in this lesson2 min
Examining successful data governance implementations with Databricks4 min
Industry-specific use cases and their data governance challenges5 min
Lessons learned and best practices from real-world scenarios2 min
Readings · 4
Further Reads on Leveraging Databricks15 min
Further Reads on Best Practices for Data Governance10 min
Case Studies10 min
Provide your feedback!10 min
Assignments · 4
Practice Quiz - Leveraging Databricks15 min
Practice Quiz - Best Practices for Data Governance15 min
Case Studies and Real-World Examples practice quiz15 min
Graded Quiz - Data Governance and Databricks - Application60 min
Topics covered
Data managementData catalogingMetadata managementSecurity & access controlGovernance workflow designData lineage & discoveryDelta Lake & notebooksAutomationReal-world case studies
You leave with: the ability to apply what you have learned to actual scenarios - managing data, implementing governance workflows and ensuring security in Databricks.
05 Tools & skills
The tool you work in, and the skills you leave with.
Coursera lists one tool for this course, and five skills. Both are below, unedited.
The platform
Databricks
The primary tool used in the course to explore practical data governance workflows, data management, cataloging, metadata management and security.
Skills you leave with
The five capabilities Coursera lists for this course, grouped the way the work actually splits - governing the data, trusting it, and protecting it.
Governing data
The frameworks, policies and roles that make data someone's responsibility.
Data Governance
Data Management
Trusting data
Knowing what a field means, where it came from and whether it is right.
Data Quality
Metadata Management
Protecting data
Who can see what, and being able to show it.
Data Security
Certificate
Proof you can link to.
Complete the course and earn a shareable certificate through Coursera - with a one-click path onto your LinkedIn profile.
Coursera lists a shareable certificate for this course, issued on completion.
On your profile in one click
Filed under Licenses & Certifications, where recruiters actually look.
Shareable, and verifiable
Coursera issues it with its own link, so anyone you send it to can check it.
Earned, not attended
There are 7 assignments across the two modules - practice quizzes and graded quizzes.
Two names on it
Board Infinity as the provider, Coursera as the platform.
06 Career impact
Governance is what makes data usable at scale.
These are the roles built around the skills this course teaches - data governance, data management, data quality, metadata management and data security.
Where these skills are the work
Data Governance Analyst
The direct path. Module 1 is the frameworks, policies, roles and regulatory considerations; module 2 is what implementing them looks like on a platform.
Data Steward
Stewardship is data quality, metadata, security and governance workflow in one job. Cataloging and lineage in Databricks are how it becomes checkable.
Data Management Professional
Ingestion, storage and processing with Databricks, governed rather than ad hoc - which is the difference between a data platform and a data swamp.
Data Quality Analyst
Data quality management is one of the five skills Coursera lists here, and metadata management is what tells you which fields to trust in the first place.
IT Manager
Security and access control, roles and responsibilities, and automating governance processes - the parts of governance that land on IT to operate.
Data professionals generally
Coursera names this audience first. If you already work with data, governance is the layer that decides whether anyone else can rely on what you build.
The honest comparison
Data governance material is free to read. So what is this?
Every topic in this course exists free somewhere on the internet - vendor docs, governance blogs, conference talks. Nobody is pretending otherwise. What a course adds is the order you learn it in, the checking that makes it stick, and something to show at the end.
What you get
This course
Scattered free resources
A sequenced pathFundamentals → applied Databricks workflows
2 modules that build on each other
Whatever the algorithm shows you
Someone checkingLearning that sticks
7 practice and graded quizzes
You never find out what you missed
It gets specificGovernance on an actual platform
Cataloging, lineage, access control and automation in Databricks
Usually stops at definitions
Grounded in practiceWhat worked, and where it broke
Real-world case studies and industry-specific use cases
Advice without the context it came from
Proof for recruitersShareable, on LinkedIn
Shareable certificate through Coursera
Nothing to show
07 Where to go next
Governance is the layer. Here is what sits either side of it.
This course stands on its own. These are Board Infinity courses on Coursera that pair naturally with it.
Everything learners ask before enrolling, answered plainly.
About the course
It is about understanding and implementing effective data governance, with Databricks as the platform where the governance work actually happens - which is how Coursera describes it too. Across 2 modules, 26 video lessons, 7 readings and 7 assignments you cover governance fundamentals - key components, frameworks, policies, roles, regulatory considerations, data quality and metadata management - then apply them in Databricks through data management, cataloging, security, lineage, collaboration, automation and real-world case studies.
No. Coursera states that prior knowledge of Databricks is not a prerequisite, which makes the course suitable for beginners as well as experienced professionals looking to enhance their skills. It is still listed at Intermediate level with recommended experience, so a working familiarity with data and how organisations use it will help you move faster.
Coursera's course-level metadata says 7 hours to complete, and that is the figure used throughout this page. Each of the two modules is listed individually as approximately 3 hours. One thing worth flagging rather than quietly smoothing over: the FAQ on the Coursera course page currently says approximately 6 hours. The two numbers on Coursera do not agree, so we are showing you both instead of picking one. Either way it is self-paced, and the real total depends on how long you spend on the readings and quizzes.
Module 1, Data Governance and Databricks - Fundamentals (approximately 3 hours), covers data governance and its importance in modern organizations, an introduction to Databricks, and the benefits and challenges of implementing governance with it. It then defines data governance and its key components, establishing frameworks and policies, roles and responsibilities, regulatory and compliance considerations, and data quality and metadata management. It contains 13 videos, 3 readings, 3 assignments and 1 plugin.
Module 2, Data Governance and Databricks - Application (approximately 3 hours), is the practical half: data management through ingestion, storage and processing; cataloging and metadata management; security and access control; designing governance strategies; data lineage and data discovery; collaborative governance with Databricks notebooks and Delta Lake; automating governance processes and workflows; then best practices and real-world case studies including industry-specific use cases. It contains 13 videos, 4 readings and 4 assignments.
The price is shown at checkout on the Coursera course page and can vary by region. It's included at no extra cost with a Coursera Plus subscription, and Coursera's financial aid is available to eligible learners.
Career & certificate
Yes. Coursera lists a shareable certificate for this course. Complete the course and earn a shareable certificate through Coursera, which can be added to the Licenses & Certifications section of your LinkedIn profile in one click.
Yes. Coursera lists a flexible schedule and learning at your own pace, and its own FAQ confirms the course is designed for self-paced learning so you can progress at a pace that suits your schedule.
Coursera's own answer: you'll learn to manage data, design governance workflows, ensure security, and apply best practices using Databricks, with real-world examples. The applied material sits in module 2, and what you are assessed on is 7 assignments - a mix of practice quizzes and graded quizzes - across the two modules.
Yes - this page is Board Infinity's own overview of our course. Enrollment, payment, video lessons, grading and the certificate all happen on Coursera, where the course is hosted. Think of this page as the detailed tour before you head there. Note there is a separately named course, Data Governance with Databricks, which is not this one; the course this page describes is Learn Data Governance Workflows with Databricks Tools.
It depends where you're aiming. To keep working on governance and cataloging on a different platform, Managing Data Lakes & Pipelines with Google Cloud Dataplex is the closest next step. To strengthen the SQL and data management underneath governance, Mastering SQL and Data Management with Teradata covers it. To communicate what governed data actually says, Data Visualization and Storytelling with Plotly in Python. The Where to go next section links all three.
Want someone building this with you?
Board Infinity 1:1 coaching pairs you with a practitioner while you take the course.
