Effective data processing within civil litigation and eDiscovery/ eDisclosure matters is crucial, as it streamlines workflow and can significantly reduce costs.
De-duplication is the most effective part of processing as it will remove any duplicate documents, reducing the amount of overall documents for review, as well as preventing reviewers having to look at the same document more than once.
There are two types of de-duplication techniques; Global De-duplication and Custodial De-Duplication.
Global de-duplication will look at the entire dataset and keep only one instance of a duplicate document.
In some cases where there is more than one custodian (person/laptop) being investigated, it can sometimes be crucial to know whether a certain document is present within both custodians datasets. We have an option called ‘Custodial De-duplication’, which will still remove duplicate documents, however it will keep one instance of a document within each person’s dataset.
There are further cases where sometime de-duplication is not relevant and it is crucial that the review shows every instance of a document within a dataset, even if duplicate documents are present. For instances like this, we set ‘No Duplication’ on when processing your dataset.
These options are discussed with you prior to us carrying out any processing on your case. The eDiscovery Specialists at CYFOR will work alongside yourselves to work out what the best duplication option is on a case by case basis.
Nuix Data Processing
CYFOR have worked alongside Nuix since 2013, utilising a number of tools such as Nuix Investigator and Nuix eDiscovery Workstation.
The processing tool offered by Nuix, allows us to collect and process large volumes of data, including Lotus Notes, Forensic Images, Exchange Sever, SharePoint and a range of email and cloud based repositories.
Nuix allows us to remotely download various mail stores such as Yahoo, Gmail, Outlook, AOL etc. We also have the ability to remotely download the accounts from Dropbox, Google Drive and Microsoft OneDrive. We can also process backups of iOS devices stored in iCloud without needing access to the devices themselves. Having the ability to remotely download these accounts saves our clients both time and money, as we can do the download from our offices with no disruptions to yourself.
Nuix works through the entire Electronic Discovery Reference Model (EDRM) project lifecycle, covering collection, processing, search and analysis, culling, review, and production.
- Advanced Search and Filtering Options – Search your data any way you like with exact, fuzzy, proximity and regular expression searches to identify the key terms of interest.
- Apply advanced filters such as file type, skin tone, media attributes, custodians, word lists, languages or named entities.
- Visualize data to quickly identify trends, locate information of interest and drill down to specifics.
- Built in Visual Analytics to assist in ‘drilling down’ into large volumes of data, allowing you to visualise and identify trends, time gaps and anomalies.
Relativity Data Processing
Relativity Processing is tightly integrated into Relativity, allowing CYFOR to process, analyse, and review your data within a single platform.
Relativity Processing allows us to process native files and quickly prepare them for review. Full metadata and container extraction, domain parsing, and native application imaging combine to provide a complete processing solution. Easy access to the facts you need for each processed data set, such as metrics on the original data source and the documents which were published to review.
Relativity Processing allows for the triaging of data and uses filters like date range, sender domain, and file type to eliminate unnecessary raw data from the discovery process. Relativity Processing allows CYFOR to ingest raw data directly into your workspace for eventual search, review, and production.
Some of the primary goals of processing are to:
- Determine, at an item-level, exactly what data is contained in each data set.
- Maintain and record all document-level and system-level metadata as it existed prior to processing.
- Enable defensible reduction of data by selecting only appropriate items to move forward to review.