Assessing Data Privacy and Cybersecurity Risk

What are some of the biggest challenges companies face when it comes to data governance?

One of the biggest challenges companies face today is balancing the breadth and depth of secure data. On one hand, organizations want to generate and share as much data as possible with their clients; However, this ambition comes with significant risks.

1. Cost Management: Managing and storing large volumes of data can be financially burdensome, especially given the variable pricing models of many cloud service providers. These costs can adversely affect a company’s bottom line.
2. Performance Issues: A vast amount of data stored on a suboptimal management platform can lead to slow data retrieval, negatively impacting user experience.
3. Security Risks: More data often means more confidential and sensitive information. If a company’s infrastructure is compromised or if data is accidentally shared with unauthorized users, the risks increase significantly.
4. Enhanced Due Diligence: Enhanced due diligence on data sources will be even more important as we move forward. Companies will have to know dig into to understand the genesis of external data to make sure their data is accurate and appropriately sourced, how we do this will evolve, especially as more firm use AI to create or enhance data sets. The knee jerk reaction is to use AI to validate the incoming data, which causes a recursive paradox. 

Ultimately, the challenge lies in making informed decisions about how much data to manage, what to prioritize, how long to retain data, when and how to expose it, and ensuring that the data is accurate and secure. Finding the right answers to these questions is often more complex than it seems.

How do you think data governance will evolve in the next decade?

I believe we will see significant changes in data governance over the next 10 years:

1. Data Utilization from Source Systems: Legacy systems have struggled to expose their data via APIs, but with the rapid advancement of artificial intelligence, particularly generative AI, it will become easier to transform and utilize data directly from source systems. This shift will reduce the number of places data is stored, thereby minimizing exposure. However, it will also necessitate enhanced security for traditionally “back-of-house” systems.
2. Evolving Regulations: As data breaches become more frequent, regulations will need to adapt quickly. Tools that enhance data utilization can also be exploited by bad actors, making it crucial for…