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Privacy, Governance, and Compliance: Data Classification and Inventory

سرفصل های دوره

Companies that drive revenue and growth based on user engagement also face challenges with data. The same data that enables these companies to build personalized features also needs protection from misuse and other security and privacy concerns. In this course, privacy and security leader and a digital product architect Nishat Bhajaria guides you through using a data governance architecture to classify and inventory your data and enforce data protection policies. Get an overview of the privacy landscape, including privacy regulations and laws. Learn about data classification, how it can help you, and some challenges and solutions associated with it. Explore data inventory and data governance, then deep dive into data inventory implementation, architecture, metadata, use cases, and more. Plus, get some practical advice on how to do data inventory in a way that works and makes sense for your organization.


01 - Introduction
  • 01 - Welcome
  • 02 - Who this course is for
  • 03 - Data classification as part of data governance

  • 02 - 1. The Privacy Landscape
  • 01 - The legal and regulatory landscape
  • 02 - Privacy regulations and ambiguity
  • 03 - Privacy laws and security
  • 04 - Privacy and the user
  • 05 - Challenge Data classification scenario
  • 06 - Solution Data classification scenario

  • 03 - 2. Data Classification
  • 01 - How classification reduces risk around unstructured data
  • 02 - How can data classification help you
  • 03 - Data classification as part of data governance
  • 04 - How to shape the data classification process
  • 05 - Challenges of data classification
  • 06 - Solutions for data classification
  • 07 - Thought experiment A sequential data classification

  • 04 - 3. An Inventory of Your Data and Risk
  • 01 - What is data inventory
  • 02 - Data inventory and data governance
  • 03 - How can you prep for data inventory

  • 05 - 4. A Deep Dive into Data Inventory
  • 01 - Data inventory using manual resources and automation
  • 02 - The technical implementation of data inventory
  • 03 - Data inventory architecture
  • 04 - Data inventory metadata
  • 05 - Data inventory and use cases
  • 06 - Evaluating data inventory outcomes

  • 06 - 5. Lessons from the Road How to Do Data Inventory Right
  • 01 - Centralized vs. decentralized
  • 02 - Data inventory successes
  • 03 - Data inventory challenges
  • 04 - Getting executive buy-in for data inventory

  • 07 - Conclusion
  • 01 - Next steps
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