Structured Analytics, Conceptual Analytics, and Sentiment Analysis are Relativity tools that enable you to categorize your documents and automate the review process while minimizing the time your review team would otherwise spend coding irrelevant documents in your document set.
Read an Analytics scenarioYou’re a system admin at a law firm and one of your clients, a construction company, is involved in litigation regarding the use of materials that they weren’t informed were potentially environmentally damaging when they purchased them from a major supplier.
In the past, you’ve conducted a linear review for projects of a similar nature. This case, however, is the largest you’ve seen, as it includes 7 TB of data comprised of 11.6 million documents. These documents are primarily email attachments, but they also include 20 MB of technical manuals related to construction practices and material handling.
Your goal is to organize and assess the semantic content of this large data set, saving your firm as much money as possible in the process. To do this, you’re going to leverage Relativity’s structured analytics options, build an Analytics profile, and create and build an Analytics index, which you’ll eventually use as the basis for an Assisted Review project.
Structured AnalyticsTextual near duplicate identification |
Conceptual Analytics |
Sentiment Analysis |
Knowledge base articlesAnalytics - creating an optimized index Sentiment Analysis Workflows and Fields Overview Estimating diskspace utilization for databases and indexes Use case for Analytics - clustering and categorization |
On-demand Analytics training webinarsAnalytics Index Building: Beyond the Basics Creating a Conceptual Analytics Index Discussion of Near Duplicate Identification Email Thread Visualization & Workflows Getting the Most out of Cluster Visualization Language and Repeated Content Identification |
