Assessing Data Classification: Weighing the True Costs of Building vs. Buying

Accurate data classification is the bedrock of a robust data security program. It supports DLP, identity security, privacy compliance, and AI governance. However, the rise of cloud environments and diverse data types complicates maintaining this foundation, making it a pressing challenge for enterprises. The critical consideration is no longer about whether to classify data, but rather if in-house efforts can truly deliver sustainable results compared to specialized solutions. Join Technical Data & AI Evangelist Joe Tustin on June 10th to delve into this topic. Key Takeaways:

• The escalating costs associated with classification debt and maintaining accuracy at scale.
• Blind spots of homegrown classification: why generic LLMs miss crucial proprietary data.
• Identifying AI risks linked to incomplete classification and governing access.
• Gaining clarity in decision-making through purpose-built classification solutions.