DataClass: The Path to Data Remediation

The path to data remediation

Day-to-day legal, storage, and compliance challenges are forcing companies to seek data remediation solutions to help them gain control and understand what data they have and how, where, and why they're maintained. To master unstructured and uncontrolled data, Deloitte has created a data remediation framework that has four stages.

• Cloud platform setup. We work with your IT teams to identify data locations, platforms, and estimated volumes; we connect to directory, legal hold, and HR data sources; and we gather internal records schedules, acceptable use, and other related policy documents to support our efforts.
• Rules and planning. An internal review of your company policies is performed, we generated initial taxonomies to establish baseline categorization rules. We construct an augmented data map that helps drive a strategic approach to data remediation.
• Categorization. Data-scanning tools are deployed to extract metadata needed for categorization. Machine learning, natural language processing, and Deloitte’s industry accelerators drive speed and efficiencies. We then work with businesses to confirm categorization and to gain insights into uncategorized data and identify data that don’t need to be kept and are free of legal and regulatory obligations.
• Classification. For data that require classification, we use standard and custom unsupervised and supervised machine learning models and leverage robust data sampling tools that support records storage and advanced searching to identify valuable business data.
  

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Five insights into data remediation

Unstructured data are also easily lost and forgotten. Lots of data. Duplicate documents, ancient project iterations, and the digital detritus of departed employees, among others, all contribute to confusion, cost, and legal and regulatory liability.

Data remediation can help organizations improve the disposition and, more broadly, the management of runaway data volumes. By employing data segmentation and classification tools and techniques, remediation can guide decisions on what to collect, what to keep, where to keep it, and what data can be defensibly deleted from legal and regulatory compliance perspectives. Read here five insights on data remediation:

• Unstructured data are everywhere, and often not valid for business use
• Data demands compel tough choices
• Segmentation breeds understanding
• Classification creates order
• A strategic approach, defensibility, and certain capabilities are essential

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