The Modern Data Imperative whitepaper explains how exploding data volumes, diverse formats, and regulatory pressures make eDiscovery costly and inefficient. Traditional workflows repeatedly re-review the same data, trapping insights and driving waste. Using big data analytics and AI, organizations can pre-classify privileged or sensitive content, reuse prior coding decisions, and eliminate non-responsive “junk” documents. A case study showed a pharmaceutical company saved over $1M in review costs by cutting 350K unnecessary documents and improving privilege detection. The paper stresses adopting scalable analytics for cross-matter insights, risk mitigation, and consistent, defensible outcomes.

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