Best Practices for eDiscovery Data Processing

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Legal teams often run into unanticipated problems during eDiscovery after they go through the initial data collection stage. At this point, it’s necessary to sort through the information, understand what you’re working with, and move the data forward for use in a legal setting. Unfortunately, this can be an overwhelming and difficult experience that slows down your entire operation.

If you’re struggling to understand eDiscovery data processing, you’ve come to the right place. Read on to learn what data processing entails during eDiscovery, why it’s important, and some best practices to make it easier and more efficient.

What Is eDiscovery Data Processing?

At a high level, eDiscovery data processing involves analyzing, reviewing, reducing, and preparing data for use in a legal setting such as a court case or audit. 

Data processing is a critical part of eDiscovery that you can’t skip over. It is necessary regardless of whether you’re working with large or small data sets. Before you make information available for review, you must first understand where the data came from and what it contains. In addition, you may need to reduce the data in the collection. 

Data processing serves a few different purposes. First and foremost, it prevents overloading legal teams with too much data. This expedites the legal process and reduces eDiscovery costs. At the same time, it protects your client by ensuring that only necessary and relevant information becomes discoverable. 

Continue reading at the link below:

How Does eDiscovery Data Processing Work?


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