Challenge

After a major data breach, one of Australia’s largest healthcare providers faced the compromise of more than 200,000 sensitive records across 118 GB of data. The breach raised immediate concerns about patient confidentiality, regulatory compliance, and financial exposure, requiring a fast, defensible response under strict data-protection laws.

Key challenges included:

  • High-Volume, Unstructured Source Data: The breach spanned multiple datasets and formats, including Excel files with 17,000 records and a 195,000-record unstructured SQL database. This required specialised filtering and categorisation before accurate notification work could begin.
  • Data Integrity and Verification Risk: Inconsistent, incomplete, duplicate, and partially fragmented records across structured and unstructured sources made accurate verification of individual records difficult.
  • Accuracy Under Regulatory Obligations: Compiling a precise and defensible notification list required advanced filtering and anomaly‑detection techniques to ensure every affected individual was accurately identified without generating false notifications that could undermine operational efficiency and credibility.

Solution

Elevate applied a structured and data-driven approach to consolidate compromised data and produce an accurate, defensible notification list under strict regulatory timelines.

  • Extracted and cleaned unstructured SQL records using automated scripts and targeted manual workflows
  • Categorised patient and employee data to enable accurate and efficient downstream analysis
  • Standardised Excel datasets and applied robust deduplication logic to remove redundancies and correct inconsistencies
  • Used pattern recognition and anomaly-detection to identify all affected individuals
  • Prioritised high-risk records while maintaining complete coverage across the full dataset
  • Delivered a fully validated, regulator-ready notification list to support compliance disclosures and direct customer communication

Impact

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51% reduction in data volume, through structured data consolidation and advanced filtering

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52% lower review costs, driven by lower data volumes and a specialised India-based review team

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4x faster review cycles, without compromising accuracy or defensibility

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On-time delivery under strict deadlines, enabled by advanced data mining and structured review workflows

a large-scale breach demanded speed, accuracy, and compliance - infographic

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