Description

Introduction of Relativity Fundamentals of eDiscovery

The legal landscape has shifted dramatically with the growing complexity of digital data. One of the most widely used platforms to manage and streamline the e-discovery process is Relativity. This course offers a comprehensive introduction to Relativity, a powerful tool that enables legal professionals to collect, review, and manage electronic evidence efficiently. By the end of this training, participants will gain foundational knowledge on how Relativity supports the entire e-discovery lifecycle, from data collection to final production, making legal workflows more efficient.

Learning Outcomes:

1. Understand the fundamentals of e-discovery and the role of Relativity in the process.
2. Learn key features and tools within Relativity for effective e-discovery management.
3. Navigate the Relativity interface and workflows, including document review, search functionalities, and data analysis.
4. Gain insights into best practices for e-discovery project management within Relativity.

Prerequisites of Relativity Fundamentals of eDiscovery

1. Basic knowledge of legal processes and litigation.
2. Familiarity with common terminology related to e-discovery (e.g., litigation hold, custodians, metadata).
3. Basic computer skills, including working with web-based applications.

Table of Contents  

1: Introduction to Relativity Fundamentals of eDiscovery

1.1 What is e-Discovery?
1.1.1 Overview of the e-discovery process.
1.1.2 Key terminology and concepts.
1.2 Introduction to Relativity
1.2.1 History and purpose of the platform.
1.2.2 Understanding the e-discovery lifecycle.
1.3 Relativity Interface Overview
1.3.1 Navigating the dashboard.(Ref: Navigating the Relativity Interface: For Beginner’s)
1.3.2 Key components and features.

2: Setting Up Workspaces and Projects

2.1 Creating a New Workspace
2.1.1 Defining workspaces in Relativity.
2.1.2 Workspace templates and customization.
2.2 Project Setup: Users, Roles, and Permissions
2.2.1 Managing user access and roles.
2.2.2 Assigning permissions for different teams.
2.3 Folder Structure and Organization
2.3.1 Best practices for document organization.
2.3.2 Creating folders for efficient data management.

3: Data Import and Processing in Relativity

3.1 Data Collection and Ingestion
3.1.1 Understanding data sources and types.
3.1.2 Ingesting data into Relativity.
3.2 Data Processing and Culling
3.2.1 Processing workflows.
3.2.2 Data reduction techniques (de-duplication, filtering).
3.3 Managing Metadata
3.3.1 Importance of metadata in e-discovery.
3.3.2 Metadata handling in Relativity.

4: Document Review and Coding

4.1 Search and Filtering Techniques
4.1.1 Basic and advanced search functionalities.
4.1.2 Keyword search and Boolean operators.
4.2 Document Review Workflow
4.2.1 Setting up review teams and batches.
4.2.2 Using coding fields for tagging documents.
4.3 Document Views and Layouts
4.3.1 Customizing review panes.
4.3.2 Batch review and coding strategies.

5: Analytics and Predictive Coding

5.1 Introduction to Analytics in Relativity
5.1.1 Using structured and conceptual analytics.
5.1.2 Email threading and near-duplicate detection.
5.2 Predictive Coding (Technology-Assisted Review)
5.2.1 Overview of TAR and its benefits.
5.2.2 Training Relativity to identify relevant documents.
5.3 Applying Analytics for Faster Review
5.3.1 Best practices for leveraging analytics.
5.3.2 Reducing review time with technology.

6: Production and Finalizing Projects

6.1 Preparing Data for Production
6.1.1 Production workflows and options.
6.1.2 Redacting sensitive information.
6.2 Exporting and Producing Data
6.2.1 Export formats (PDF, TIFF, native files).
6.2.2 Ensuring compliance with production standards.
6.3 Quality Control and Final Deliverables
6.3.1 Reviewing for accuracy and completeness.
6.3.2 Delivering the final production set to clients.

This session-based structure ensures a gradual, hands-on introduction to Relativity, enabling participants to grasp the critical aspects of e-discovery in a well-organized manner.

Reference