Advanced eDiscovery (classic)
Advanced eDiscovery (classic) will be permanently retired on December 31, 2020.
As we continue to invest in newer versions of Advanced eDiscovery, we're announcing the permanent retirement and removal of cases and case data from Advanced eDiscovery (classic). If you're still using Advanced eDiscovery (classic), also known as Advanced eDiscovery v1.0, please transition your usage to Advanced eDiscovery v2.0 (also known as the Advanced eDiscovery solution in Microsoft 365) as soon as possible. In preparation for the removal of all cases and case data, you can archive case data by exporting data from a case. Advanced eDiscovery v2.0 contains similar functionality found in Advanced eDiscovery v1.0, but also offers many new features such as custodian management, communications management, and review sets. To learn more about the previous retirment phases of Advanced eDiscovery v1.0, see Retirement of legacy eDiscovery tools.
With Advanced eDiscovery, you can better understand your data and reduce your eDiscovery costs. Advanced eDiscovery helps you analyze unstructured data, perform more efficient document review, and make decisions to reduce data for eDiscovery. You can work with data stored in Exchange Online, SharePoint Online, OneDrive for Business, Skype for Business, Microsoft 365 Groups, and Microsoft Teams. You can perform an eDiscovery search in the security and compliance center to search for content in groups, individual mailboxes and sites, and then analyze the search results with Advanced eDiscovery. When you prepare search results for analysis in Advanced eDiscovery, Optical Character Recognition enables the extraction of text from images. This feature allows the powerful text analytic capabilities of Advanced eDiscovery to be applied to image files.
Advanced eDiscovery streamlines and speeds up the document review process by identifying redundant information with features like Near-duplicates detection and Email Thread analysis. The Relevance feature applies predictive coding technology to identify relevant documents. Advanced eDiscovery learns from your tagging decisions on sample documents and applies statistical and self-learning techniques to calculate the relevance of each document in the data set. This enables you to focus on key documents, make quick yet informed decisions on case strategy, cull data, and prioritize review.
Why advanced eDiscovery? Advanced eDiscovery builds on the existing set of eDiscovery capabilities in Office 365. For example, you can use the Search feature in the Security & Compliance Center to perform an initial search of all the content sources in your organization to identify and collect the data that may be relevant to a specific legal case. Then you can perform analysis on that data by applying the text analytics, machine learning, and the Relevance/predictive coding capabilities of Advanced eDiscovery. This can help your organization quickly process thousands of email messages, documents, and other kinds of data to find those items that are most likely relevant to a specific
Advanced eDiscovery requires an Office 365 E3 with the Advanced Compliance add-on or an E5 subscription for your organization. If you don't have that plan and want to try Advanced eDiscovery, you can sign up for a trial of Office 365 Enterprise E5. case. The reduced data set can then be exported out of Office 365 for further review.
The quickest way to get started with Advanced eDiscovery is to create a case and prepare search results in Security & Compliance Center, load those results in Advanced eDiscovery, and then run Express analysis to analyze that case data and then export the results for external review.
Get a quick overview of the Advanced eDiscovery workflow
Set up users and cases for Advanced eDiscovery by creating a case, assigning eDiscovery permissions, and adding case members, all by using the Security & Compliance Center
Prepare and load search data in to the case in Advanced eDiscovery
Load non-Office 365 data in to a case to analyze it in Advanced eDiscovery
Use Express analysis to quickly analyze the data in a case and then easily export the results
After search data is loaded into the case in Advanced eDiscovery, you'll use the Analyze module to start analyzing it. The first part of the analysis process consists of organizing files into groups of unique files, duplicates, and near-duplicates (also know as document similarity). Then you organize the data again into hierarchically structured groups of email threads and themes and, optionally, set ignore text filters to exclude certain text from analysis. Then you run the analysis and view the results.
Learn about document similarity to prepare you for analyzing data in Advanced eDiscovery
Set up the options for near-duplicates, themes, and email threading and then run the Analyze module
Set up Ignore Text filters to exclude text and text strings from being analyzed; these filters will also ignore text when you run Relevance analysis
View the results of the analysis process
Configure advanced settings for the analysis process
Set up Relevance training
Predictive coding (called Relevance) in Advanced eDiscovery lets you train the system on what you're looking for by letting you to make decisions (about whether something is relevant or not) on a small set of documents.
Learn about setting up Relevance training , tagging files that are relevant to a case, and defining case issues
Define case issues and assign each issue to a user who will train the files
Add imported files to current or new load that will be added to the Relevance training. A load is a new batch of files that are added to a case and then used for Relevance training
Define highlighted keywords that can be added to the Relevance training. This helps you better identify files that are relevant to a case
Run the Relevance module
After set up training, you're ready to run the Relevance module and assess the effectiveness of the training settings. This results in a relevance ranking that helps you decide if you need to perform additional training or if you're ready to start tagging files as relevant to your case.
Learn about the Relevance process and the iterative process of assessment, tagging, tracking, and retraining based on sample set of files
Learn about assessment , where an expert familiar with the case reviews a set of case files and determines the effectiveness of the Relevance training
Assess case files to calculate the effectiveness (called *richness) of training settings, and then tag files as relevant or not relevant to your case. This helps you determine if the current training is sufficient or if you should adjust the training settings.
Perform the relevance training after assessment is complete, and then once again tag files as relevant or not relevant to the issues you've defined for the case
Track the Relevance analysis process to determine if Relevance training has achieved your assessment target (known as a *stable training status) or whether more training is needed; you can also view the Relevance results for each case issue
Make decisions based on Relevance analysis to determine the size of the resulting set of case files that can be exported for review
Test the quality of the Relevance analysis to validate the culling decisions made during the Relevance process
The final step in analyzing case data in Advanced eDiscovery is to export results of the analysis for external review.
Other Advanced eDiscovery tools
Advanced eDiscovery provides additional tools and capabilities beyond analyzing case data, relevance analysis, and exporting data.