Taken from a combination of public market sizing estimations* as shared in leading electronic discovery publications, posts and discussions over time, the following eDiscovery Market Size Mashup** shares general market sizing estimates for both the software and service areas of the electronic discovery market for the years between 2013 and 2018.
Provided as a manual mashup charts are three general views of the eDiscovery market to include a combined software and services market view, a software market view and a service market view. The mashup charts represent one interpretation of publicly available market sizing data and are designed to be “general in nature, focusing on trends in relation to market size, growth and segmentation.
Sources for eDiscovery market sizing estimations include but are not limited to publicly available content (including abstracts, excerpts, quotes) from the following:
Previous ComplexDiscovery eDiscovery market sizing mashups include:
A mashup is a combination or mixing of content from different sources to create a new way of looking at data. The main characteristic of a mashup includes combinations, visualizations, and aggregation. Mashups can be helpful in making existing data more useful, moreover for personal and professional use. (Wikipedia)
This entry was posted on Wednesday, June 25th, 2014 at 11:28 pm. It is filed under chronology, discover, industry, Insight, original and tagged with electronic discovery, research. You can follow any responses to this entry through the RSS 2.0 feed.
Taken from a combination of public market sizing estimations as shared in leading electronic discovery reports, publications and posts over time, the following eDiscovery Market Size Mashup shares general worldwide market sizing considerations for software and services in the electronic discovery market for the years between 2015 and 2020.
When Maura Grossman speaks, people listen. In 2011, she was already known as a leading e-discovery attorney and litigator. But her influence exploded when she released research with co-author Gordon Cormack, a computer science professor at the University of Waterloo in Ontario, that concluded software using predictive-coding technology can do as good a job of sifting through documents as human reviewers.
ComplexDiscovery | Creative Commons Attribution 4.0 International