Deciding Between Building or Buying Data Classification: Understanding DIY Costs

Accurate data classification serves as the cornerstone of any robust data security program, impacting DLP, identity security, privacy compliance, and AI governance. As cloud environments expand and data types multiply, ensuring precise classification becomes increasingly challenging for enterprises. The key question now isn't whether to classify data, but rather if maintaining this capability in-house is feasible or if a specialized solution outperforms it. Join Technical Data & AI Evangelist Joe Tustin on June 10th for insights on this critical topic. Key Takeaways:

• Understanding the true costs of classification debt and maintaining accuracy at scale.
• Identifying gaps in homegrown classification systems, particularly concerning proprietary and unstructured data.
• Recognizing AI risks stemming from incomplete data classification.
• Gaining decision clarity through purpose-built classification solutions.