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IBM Data Privacy for Information Architecture

Approx. 10 hours to complete

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Course Summary

Learn about data privacy and protection laws, regulations, and best practices with this IBM course. Explore the importance of data privacy, how to implement it, and the consequences of not doing so.

Key Learning Points

Understand the importance of data privacy and protection in today's digital landscape
Learn about the various data privacy laws and regulations around the world
Implement data privacy best practices to protect personal and sensitive information

Learning Outcomes

Understand the importance of data privacy and protection in today's digital world
Learn about the various data privacy laws and regulations around the world
Implement data privacy best practices to protect personal and sensitive information

Prerequisites or good to have knowledge before taking this course

Basic understanding of data management and security
Access to a computer with internet connection

Course Difficulty Level

Intermediate

Course Format

Self-paced
Online
Video lectures

Similar Courses

Data Protection and Privacy
Data Privacy and Ethics

Related Education Paths

Notable People in This Field

IAPP - International Association of Privacy Professionals
GDPR - General Data Protection Regulation

Related Books

Description

Data privacy controls how information is collected, used, shared, and disposed of, in accordance with policies or external laws and regulations. In this course, students will gain an understanding of what data privacy is along with how to identify and understand typical data protection and privatization objectives that an enterprise may have, and how to choose a data protection approach. The student will gain a background in multiple data privacy mechanisms and practices, and learn how to grow their data protection toolkit. The IBM DataFirst method will be the backbone of the discussion.

Outline

IBM DataFirst Data Privacy introduction
Meet Christopher Giardina
Meet Tim Davis
Meet Paul Christensen
Transforming your business with modern data and AI architectures
What is an IBM DataFirst engagement?
Course disclaimer
IBM DataFirst Data Privacy introduction

Data governance and organizational structures
Data governance and organizational structures introduction
DataFirst
Structures and roles
Organization governance structures
Use case example
Questions to consider
Data governance and organizational structures

Dealing with regulation
Introduction to considering data privacy rights
Data protection, privacy and regulations overview
Example of a deployment
Data privacy regulations and initiatives
Exploring regulations
What is personal data?
Core Principles
A "Privacy Principles" approach
Getting started
Demonstrating compliance
Dealing with regulation - Practice quiz
Dealing with regulation

Data governance intersections
Data governance intersections introduction
Why data governance?
Private data, use case types, and governance building blocks
Key governance components: Who and what?
What is metadata?
Key governance components: Where, why, how?
Data Privacy policies and procedures examples
Example assessment guidance
Questions to consider
ODPi Egeria
Data governance intersections

Data privacy vs security
Data privacy vs security introduction
Underlying principles
The difference between data privacy and security
Privacy mechanisms
Security mechanisms
Governance driven protection and use case introduction
Test data management use case
Analytics and data science use case
Summary
An end-to-end framework for privacy at scale
Data privacy vs security

Data privatization mechanisms
Data privacy and the changing landscape
Data privatization mechanisms introduction
Personal data privatization vs. privatization of personal data
Personal data categories
Data topologies, use cases, and the data strategy perspective
Typical mechanisms overview
Data masking
Tokenization
Anonymization
Data fabrication
Personal data re-identification risk assessment
Other related approaches
Choosing privatization techniques and considerations
Data privatization mechanisms

Conducting the workshop
Conducting the workshop introduction
DataFirst engagement
The agenda
The participants
Day one
Days two and three
Days four and five
Typical work products and deliverables
High level data flow approach
Breakdown of processes approach
People, process, and technology views
Drill down approach
Roadmap guidance example
Conducting the workshop

Summary of User Reviews

The IBM Data Privacy course on Coursera has received positive reviews overall. Many users appreciated the practical examples provided throughout the course, making it easier to understand complex concepts.

Key Aspect Users Liked About This Course

Practical examples provided throughout the course

Pros from User Reviews

Clear and concise explanations of complex concepts
Engaging and interactive assignments
Expert instructors with real-world experience
Useful tips and best practices for data privacy management

Cons from User Reviews

Some users found the course content to be too basic or introductory
The pace of the course may be too slow for more experienced individuals
Limited opportunities for peer interaction or collaboration

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