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The world is becoming more and more digital every passing day. As a result, people and companies are creating data at an aggressive pace—a trend that’s bound to continue in the coming years.
For this reason, legal teams need to have a comprehensive eDiscovery system to process and analyze data efficiently. Suffice it to say that data processing is a critical part of eDiscovery, and can make all the difference during fast-moving legal cases.
Read on to learn what data processing means in eDiscovery, how it fits into a robust eDiscovery strategy, why it’s important, and more.
What Is eDiscovery Data Processing?
At a high level, eDiscovery data processing involves analyzing and preparing data for use in a legal environment. It’s a big part of the early case assessment (ECA) process and something that all legal teams must handle. Advanced data processing may also be necessary after an ECA.
One of the top reasons legal teams need to process data is that they typically deal with large, complex datasets. Legal teams sometimes need to sort through millions of documents before a case kicks off in court—an overwhelming task that takes considerable time and effort.
In addition, data is often incomplete before a trial. To illustrate, a company may have data sitting in multiple storage locations, so it may be necessary to extract information and string together different data points to make or defend a case. Sometimes, you have to do some digging and assembly before you get the insights that you need.
Through automated eDiscovery data processing, legal teams can efficiently analyze their data and reduce unnecessary information. In addition, it’s a way for legal teams to make sure the information they make available is accurate, secure, and relevant for the particular case at hand.
How Data Processing Fits in the eDiscovery Pipeline
It’s important to realize that data processing is one step in the larger eDiscovery process. Each step is a part of the eDiscovery framework.
Here’s a breakdown of the eDiscovery pipeline, according to the popular Electronic Discovery Reference Model (EDRM)—a legal framework that many firms use to guide their eDiscovery strategy.
Identification involves locating potential sources of electronically stored information (ESI). This step is all about determining data sources, depth, and breadth.
The preservation stage ensures that ESI remains safe from alteration or destruction. It’s necessary to preserve data just as you do with physical evidence.
Collection entails gathering ESI for use in the eDiscovery process. In other words, you need to collect data before you can move it onto processing, review, or analysis.
Data processing primarily involves reducing ESI volumes. In some cases, it’s also necessary to convert data into different forms for review and analysis.
Reviewing is the process of evaluating ESI for use in a legal case. During the review period, you typically assess ESI for relevance and privilege.
ESI analysis involves evaluating ESI for content and context. In other words, you may look for patterns, individuals, and topics related to the case.
Production involves delivering ESI to other legal stakeholders. This may require presenting information in a specific form or using a certain delivery mechanism.
At the end of the process, you present or display ESI to audiences. For example, this could be during a hearing or a trial.
Data Processing and FRCP Rule 34
Rule 34 of the Federal Rules of Civil Procedure (FRCP) says that a party may serve any other party a request within the scope of Rule 26(b).
As a result, all documents and ESI are fair game during eDiscovery. For example, this may include writings, drawings, charts, graphs, photographs, images, and sound recordings, among other items.
For this reason, it’s necessary to have a comprehensive data processing system in place for reviewing any type of ESI. During reviews, your team should be able to move quickly between data types and handle multiple forms of information simultaneously.
How Does eDiscovery Data Processing Work?
No two datasets are exactly alike. As a result, you need to assess each set carefully before handling them. Here’s a basic overview of what happens during a typical eDiscovery data processing framework.
Reducing Data Volumes
One of the primary goals of data processing is to narrow down your data to what’s essential. In other words, it’s important to cull your data and avoid providing too much or too little information.
When culling data, it’s also necessary to keep information available for future potential requests. An opposing party may request additional information during a trial—and you need to be ready to provide it when that happens.
Data is a bit like crude oil. Before you use it, you have to refine or clean it. This involves scanning for duplicate entries, removing errors and inconsistencies. Cleaning data also makes it easier to generate accurate and impactful reports.
In some cases, you may need to convert data from one form to another. One of the most common examples is changing a document from a Word file to a PDF.
During the initial meet and confer session, it’s a good idea to determine whether you should share information in its native format or a different one. This saves time and effort during a hearing or a trial.
What Are the Benefits of Optimizing eDiscovery Data Processing?
Legal professionals who are new to eDiscovery sometimes balk at the idea of data processing. At first glance, eDiscovery data processing may seem risky and even pointless. But as it turns out, data processing is an integral part of eDiscovery. In fact, it’s necessary even when you are certain about the data you are working with.
Here are some of the unexpected benefits of optimizing your eDiscovery data processing strategy.
Data is very expensive to own and manage. For this reason, it’s important to try and reduce costs wherever possible. A comprehensive data processing strategy lowers eDiscovery costs considerably. This enables legal teams to allocate more capital to some other areas of need.
Legal teams need to move efficiently during ECAs and eDiscovery requests. Being able to process data quickly is necessary for keeping legal processes moving forward. The faster you can analyze and understand data, the easier time you’ll have strategizing and planning.
Cybercriminals are actively targeting law firms in search of sensitive data. With this in mind, data is a massive liability—and law firms must go to great lengths to protect it.
By optimizing your eDiscovery processing strategy, you can avoid holding onto unnecessary information and reduce your attack surface considerably. At the same time, you gain a better understanding of the data you are holding. This lets you identify and protect high-risk data.
How Venio Systems Helps with Data Processing
Venio Systems offers a centralized platform for eDiscovery data processing, analysis, and review. This purpose-built platform centralizes eDiscovery and helps teams avoid using multiple tools and widgets to accomplish the same tasks.
Venio also uses artificial intelligence (AI) and automation to expedite data processing. With Venio, legal data reviews become faster, less risky, and more effective. Venio Systems is also user-friendly, meaning all types of users—from novices to experts—can jump in and use the platform for eDiscovery in no time at all.
To experience Venio Systems in action and learn more about the easiest way to expedite data processing in eDiscovery, request a demo today.
About the Author
Justin Reynolds & Akshita Singhal
This post was written by Justin Reynolds. Justin is a freelance writer who enjoys telling stories about how technology, science, and creativity can help workers be more productive. In his spare time, he likes seeing or playing live music, hiking, and traveling. This post was reviewed and published by Akshita, Sr. Marketing Manager at Venio.