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BI and E Discovery - Business Intelligence and E-Discovery...

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Volume 22 • Number 7 • July 2010 Intellectual Property & Technology Law Journal 1 Business Intelligence and E-Discovery By Nadia Brannon I n the modern and increasingly complex business environment, business intelligence (BI) platforms are becoming more prevalent, especially in large organizations. Adoption of BI technologies is likely to double in the next five years. Yet, in the e- discovery arena there is very little awareness of these massive sources of electronically stored information (ESI). Additionally, there are hardly any e-discovery tools that can access information contained in such BI sys- tems. This article explains what BI systems are, how they function, and the implications of BI technolo- gies for the e-discovery process. The Basics: Structured vs. Unstructured Data Enterprise data in general can be broken down into two broad categories: structured and unstruc- tured data. Structured data typically resides in databases. Such data is organized into tables with columns and rows of defined data types; relationships between vari- ous data fields and tables are clearly defined. Most common are relational database management sys- tems (RDBMS) that are capable of handling large volumes of data such as: • Oracle IBM DB2 • MS SQL Server • Sybase • Teradata Many organizations have an enterprise resource planning (ERP) system or systems that capture daily transactions (orders, shipments, inventory movement, etc.), contain business planning, human resources, accounting, and financial reporting components. They also might have a Web server with a database that is populated with transactions that are executed via the Web. In fact, most orga- nizations have multiple systems that talk to each other. This is particularly true for large entities that grew through multiple acquisitions and mergers. The data that resides outside of structured data- bases is called unstructured data . This includes: • Electronic documents • PowerPoint presentations • Spreadsheets • Email • Images • Schedules • IM logs, and • Multimedia files, etc. This data typically resides on individual computers or on file servers. In some cases, when the unstructured data is par- ticularly important to the company and it needs to be searchable or requires further analysis, it might be organized into a structured database and made avail- able as part of a business intelligence solution. There are a number of so-called content management sys- tems that are designed to organize unstructured data in order to help control and manage content, ver- sioning, and access rights. These systems include: • Microsoft SharePoint • LotusNotes • IBM FileNet • EMC Documentum Nadia Brannon is a data analytics and database forensics analyst at LECG. She may be contacted at [email protected] .
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2 Intellectual Property & Technology Law Journal Volume 22 • Number 7 • July 2010 How do organizations make sense out of all this data in order to gain the competitive edge? That is where business intelligence comes in.
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