Editor’s note: The following article is written by one of the winners of the “Call for Papers” competition associated with the sixth annual Arizona State University-Arkfeld eDiscovery and Digital Evidence Conference. The article below was accepted as one of two winning papers.
Legaltech News readers are eligible for a 10 percent discount in registering for the event. Please use the following code: LTNASU2017.
Managing identification, collection and legal analysis for data contained within large corporate database systems is one of the biggest challenges in e-discovery. While high-value case information is often contained within such large enterprise systems, these data sources do not fit within the established discovery processes for traditional loose files and email content. The discovery process for enterprise database systems involves significant and unique challenges that require expert technical assistance in order to avoid errors, reduce costs and assure defensibility.
Organizations use enterprise systems to capture, store and transform data for core business functions such as finance, regulatory compliance, manufacturing, sales, and human resources. They also used to automate processes specific to a line of business, e.g., pharmaceutical companies have systems that manage information for clinical trials, complaint databases, adverse events and medical inquiries. The foundation of many enterprise systems are relational database management systems such as Oracle, SAS, SQL, IBM DB2, SAP and Lotus Notes/Domino.
Discovery Pitfalls: The discovery process for electronically-stored information (ESI) from enterprise systems is complex due to numerous factors, including but not limited to: