Massive Data Discovery

A NYC law firm handling a class action was faced with 2 Terabytes of electronic financial data, millions of documents and emails as well as source code that ran on a legacy mainframe system. The data was supplied raw and no access was granted to the live system. The attorneys were faced with trying to sort through the raw data and gain an understanding of the process the system used. The job of quantifying damages amongst the vast quantity of data was overwhelming and the process was at a crawl.

GDF was called in and began the task of making the data usable. First all emails were extracted along with metadata and correlated into relevant groups using sophisticated link analysis tools developed by GDF. The documents’ metadata was also extracted and the documents were searched and divided into relevant batches and timelines and correlated with the emails giving the attorney the data they needed to follow the entire process of developing and patching the system involved as well as what was discussed, formally and informally within the opposing side’s team.

The email and document metadata, grouped records and correlated timelines helped counsel examine development and changes in the legacy system. The law firm continued to use GDF for discovery requests, deposition support and correlation of the electronic record.

This account focuses on making supplied data usable without access to the live mainframe. Reconstruction and correlation help explain the system and its records; a loss calculation also needs defined assumptions and business inputs, and any legal outcome belongs to the matter.