How Leveraging Near-Duplicate Identification Can Reduce Review Costs

Computers inherently create mass amounts of duplicative data. In today’s age of massive data proliferation, duplicate and near-duplicate ESI have become big contributors to excessive data populations, rising legal cost, and even a decreased confidence in data for those without access to the appropriate technology to organize and search within this data. As a result, de-duplication and near-duplication identification have become standard workflows for most eDiscovery and review teams. 

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Understanding the Stages of the EDRM (Electronic Discovery Reference Model)

The EDRM (Electronic Discovery Reference Model) refers to both a conceptual framework for understanding the stages within the overall eDiscovery process, and also the EDRM organization and community behind this framework and other resources. The EDRM model consists of nine stages: information governance, identification, preservation, collection, processing, review, analysis, production, and presentation. It essentially serves as a map of the electronic discovery…

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Considerations During the Identification Stage of the EDRM

During the Identification Stage, the goal is to create and deploy a plan to identify, preserve, authenticate, and collect relevant ESI. Through identifying and defining preferred data sources that potentially hold relevant information, outlining defensible protocols to preserve and collect both structured and unstructured data, and establishing the context that this information is being used, legal teams can create a data map to aid in defining the scope of the case.

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Amazon Echo & Smart Devices: Considerations In Litigation And eDiscovery

In recent years the information requests from Law Enforcement have been rising dramatically, with the majority of these requests either being subpoenas, search warrants, and court orders. There has been a colossal increase of over 500% from 2019 to 2020, and then in just the first 6 months of 2021 there has been nearly as many information requests as there was in total in 2020.

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Upcoming Innovative & Virtual eDiscovery & Legal Tech Conferences (Fall 2021)

Events and conferences can be a great resource for further developing your career, whether it be your goal is building your network, furthering your industry-specific education, or any number of other motivators. One benefit or byproduct of the shift towards more remote work across the legal industry is the increased number of online events, webinars, educational resources, and digital content being produced.

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Powerful eDiscovery Analytics: Utilizing Cluster Wheel Visualization, Concept Searching, & More

Data analytics can play a huge part in reducing the overall size, time, and cost of a review project. When applied effectively, analytics not only help identify relevant data sets more efficiently but also aid in culling down data to a manageable size. With today’s evolving tech landscape , eDiscovery analytics tend to be powered by machine learning and AI technology.

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AI & Machine Learning in Document Review

Sooner or later, most e-discovery professionals have experienced the pressure of a slow-moving document review. Pressure to reduce time spent with review and cost control is a major reason that eDiscovery is prime real estate for the current blooming use of artificial intelligence (AI) in law.

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Tips for Social Media Discovery & Data Preservation Pt.2

Social media can house a wealth of evidence, it’s no longer just for personal use but has since been wide-spread adopted for institutional use. Corporations and small businesses alike have taken to social media to reach a new level of connection with their networks regardless of the industry.

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