Managing electronic information and identifying hidden relationships in the data for legal investigations and litigation can be daunting in our digital age. Corporations, law firms, and government agencies are all facing the sheer volume and complexity of data generated across a variety of digital platforms, increasing the need for more efficient and effective eDiscovery solutions.
In this article, we’ll examine the main challenges relating to the eDiscovery practice, then outline what an ideal and future-proof eDiscovery solution would look like and explore the benefits of graph technology in this perspective.
What is eDiscovery?
First things first, let’s make sure we all agree on the terms. Electronic discovery, (also known as eDiscovery or e-Discovery), refers to the process of identifying, collecting, and producing electronically stored information (ESI) for legal investigations or litigation. Businesses increasingly rely on digital communication and information storage. A single case might involve terabytes of electronic data in various forms, presenting significant challenges for legal teams and investigators. eDiscovery involves analyzing data from various sources, including emails, social media, databases etc. and uncover meaningful relationships between data points to form key insights that can be used as evidence in legal proceedings.
From data complexity to digital evidence: the challenges of eDiscovery
As technology continues to advance, so does the scale and diversity of electronic data sources. Emails, social media posts, instant messages, documents, and databases all contribute to the ever-growing pool of potentially relevant information in legal matters. The task of identifying, collecting, processing, and reviewing this vast amount of electronic evidence has become increasingly difficult. Legal professionals are confronted with the challenge of extracting pertinent data efficiently, ensuring its integrity, navigating through intricate webs of interconnected information and identifying hidden relationships to surface evidence and build a solid case.
The eDiscovery process comes with several significant challenges:
Coping with an increasing volume of data: The volume of electronic data continues to grow rapidly, making it increasingly difficult for eDiscovery teams to manage, analyze, and review all the data within a reasonable timeframe.
Dealing with data diversity: Like we’ve mentioned, electronic data can come in many different forms, including emails, text messages, social media posts, documents, audio and video files, and more. Each of these forms of data requires specialized tools and techniques to manage and analyze.
Handling data complexity: Electronic data can be complex, with metadata, hidden data, and encryption adding layers of complexity that can be difficult to navigate.
Performing easily link analysis: Investigating potentially massive amount of electronic data and making sense of it means following the tracks to surface hidden connections and understanding the context around the data. It requires time, expertise and powerful tools.
Managing the cost: eDiscovery can be expensive, with the costs of processing, analyzing, and reviewing electronic data adding up quickly.
Working with time constraints: eDiscovery timelines can be tight, with deadlines for document production and review often set by courts or regulators. This puts pressure on teams of analysts or investigators to work quickly and efficiently while still ensuring accuracy and completeness.
Maintaining and developing technical expertise: eDiscovery requires specialized technical expertise, including knowledge of data management, database technology, and data analytics.
A changing technology landscape: Technology is constantly evolving, with new tools and techniques emerging all the time. eDiscovery teams must stay up-to-date with the latest technology trends and developments in order to remain effective and competitive.
The eDiscovery practice is a complex and challenging field, involving intricate technical, legal, and organizational issues. However, by embracing new tools and techniques, eDiscovery teams can gain a competitive advantage and stay ahead of the curve in this rapidly evolving field.
What does a powerful eDiscovery solution look like?
Until a decade ago, eDiscovery was still largely a manual process. But eDiscovery software solutions now play a crucial role in enabling legal teams to tackle these challenges head-on. They provide a systematic approach to managing electronic data for legal purposes because they offer advanced capabilities and functionalities that enable professionals to streamline the entire process, saving time, reducing costs, and ensuring compliance with legal obligations.
In particular, they can help to:
Manage vast volumes of data: Powerful eDiscovery tools can handle large-scale data collection, organization, and analysis, allowing professionals to sift through extensive datasets quickly and effectively.
Handle complex data sources: Electronic data comes from various sources, often siloed. Powerful eDiscovery tools have the capability to handle diverse data formats and sources. They can extract and consolidate information from different platforms, ensuring that no valuable evidence is overlooked.
Perform in-depth data analysis and review: The ideal eDiscovery tools offer advanced search, filtering and powerful analytics, including anomalies detection capabilities, automated data exploration and powerful link analysis features allowing professionals to quickly and easily identify patterns, uncover relationships, and gain insights from the data.
Facilitate collaboration and case management: eDiscovery often involves multiple stakeholders, including attorneys, paralegals, and IT professionals. Future-proof tools facilitate collaboration by providing centralized platforms for communication, document sharing, and task management. These tools enhance teamwork, ensuring that all team members have access to relevant information and can work together seamlessly.
Ensure compliance and data security: In the field of eDiscovery, professionals must comply with legal and regulatory requirements when handling electronic data. Their tools should offer robust security measures, including encryption, access controls, and audit trails, to protect sensitive information. They should also help professionals track and document the chain of custody, ensuring that data is admissible in court.
Over the last few years, new technology such as graph technology, AI or machine learning have emerged and are driving a paradigm shift in the field of eDiscovery, becoming powerful allies for legal professionals to push boundaries and unlock new possibilities.
Follow the tracks: Why graph technology is an essential component of any future-proof eDiscovery solution
Graph technology has swiftly emerged as an indispensable asset. Pairing graph visualization and analytics software such as Linkurious Enterprise and a graph database offers a unique approach to data visualization and analysis by focusing on the intricate relationships between data points. By organizing information as interconnected nodes and edges, graph technology provides a comprehensive view of data relationships, uncovering hidden connections, and revealing critical evidence that traditional methods may overlook, empowering legal teams to easily navigate complex networks, quickly visualize data relationships, and enhance investigative efficiency.
The power of relationship mapping and networks
By natively structuring data as a network (or a graph), one of the primary benefits of graph technology in the eDiscovery practice is relationship mapping. By mapping relationships between different data points, such as people, organizations, and documents, eDiscovery teams can generate networks of information to identify patterns of communication and collaboration between individuals, uncover hidden connections, and identify relevant documents faster. Relationship mapping can be especially valuable in cases where multiple parties are involved, or when dealing with large, complex datasets.
Faster link analysis
Graph technology can also be used to identify links between different pieces of information, such as email addresses, phone numbers, or physical locations. By analyzing these links and following the tracks, eDiscovery teams can identify bad actors in a case, track the flow of information, and uncover previously unknown relationships.
The best of both worlds: machine learning and graph
Graph technology can easily be integrated with machine learning algorithms to help eDiscovery teams identify patterns in the data that might otherwise be missed. Machine learning can help predict which documents are most relevant to a case, classify documents based on content, and identify trends and patterns across large datasets.
In real life: How Deloitte Switzerland enhanced forensics and eDiscovery practice with graph technology
Since 2021, Deloitte Switzerland has been partnering with Linkurious to deliver powerful investigative technology to Deloitte clients fighting against financial and economic crime. At the same time, Deloitte’s own forensic analytics and financial crime teams in Switzerland have also adopted Linkurious Enterprise to deliver top solutions for investigations, internal audits, AML alerts review, KYC activities, and more.
Deloitte frequently deals with highly interconnected data stored across multiple siloed IT systems. With traditional relational databases, the relationships between data points are not apparent and need to be reconstructed to obtain meaningful insights. When a problem requires analyzing large volumes of connections with multiple levels of separation, solving that problem becomes too complex with traditional databases. Linkurious has provided an ideal solution to help Deloitte surface hidden connections.
“Linkurious can really help organizations to refocus their resources on high-value operations and spend more time on actual investigations”, explains Christophe da Silva, Director of Data Analytics and eDiscovery at Deloitte Switzerland.
The need for more powerful eDiscovery solutions has become increasingly evident in today's digital landscape. The challenges of managing vast volumes of diverse and complex electronic data have propelled the demand for efficient and effective solutions. Future-proof eDiscovery solutions should integrate new technology such as graph technology and machine learning to enable professionals to handle large-scale data, diverse data sources, and perform in-depth analysis. These new technologies have the potential to revolutionize the eDiscovery practice by enabling more efficient and effective searches, uncovering hidden connections, and providing exceptional analytical capabilities.
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At Linkurious, we provide the next generation of data visualization and analytics solutions powered by graph technology. We help teams of analysts and investigators swiftly and accurately find insights otherwise hidden in complex connected data so they can make more informed decisions, faster.