Privacy, Governance, and Compliance: Data Sharing

Course details

Companies that drive revenue and growth based on user engagement also face challenges sharing data. From re-identification to exfiltration to unmanaged access, data sharing presents several privacy risks. In this course, privacy and security executive Nishant Bhajaria helps data-driven innovators understand key technologies and players that are involved in the data sharing space. As part of a "shift left" governance strategy, find out how to perform a cost-benefit analysis around data sharing and its use cases. Learn to apply data-driven tests to measure privacy risks around data sharing. Explore ways to solve the privacy risks around data sharing at all levels: data, access, identity, transport, and storage. Contextualize data sharing in terms of user footprint digitally versus in real life. After this course, you will be able to enforce data protection policies throughout the data sharing process.

Concepts

0. Introduction

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

1. Data Sharing - Risks and Possibilities

04 - How data sharing works - The ads use case
05 - How data sharing can go wrong
06 - Data sharing risks - A case study
07 - When data sharing should raise red flags
08 - Valid reasons for data sharing

2. Solving for Data Sharing

09 - Techniques to minimize privacy risk
10 - Anonymization concepts
11 - Anonymization techniques
12 - Encryption

3. k-Anonymity and Data Sharing

13 - What is k-anonymity
14 - k-Anonymity - A use case
15 - k-Anonymity - With very coarse data
16 - k-Anonymity - With very granular data
17 - k-Anonymity - Industry best practice

4. l-Diversity

18 - How l-diversity helps privacy
19 - k-Anonymity vs. l-diversity

5. The Challenge of Privacy - Your Digital Fingerprint

20 - Your physical fingerprint
21 - Your digital fingerprint
22 - The power of joining outside data

Conclusion

23 - Next steps