{"id":172901,"date":"2019-10-16T09:30:09","date_gmt":"2019-10-16T09:30:09","guid":{"rendered":"http:\/\/www.georgianewsdesk.com\/news\/story\/172901\/ediscovery-market-and-its-key-opportunities-and-challenges.html"},"modified":"2019-10-16T09:30:09","modified_gmt":"2019-10-16T09:30:09","slug":"ediscovery-market-and-its-key-opportunities-and-challenges","status":"publish","type":"post","link":"http:\/\/www.honolulunewsnow.com\/news\/story\/172901\/ediscovery-market-and-its-key-opportunities-and-challenges.html","title":{"rendered":"eDiscovery Market and its Key Opportunities and Challenges"},"content":{"rendered":"
\"eDiscovery<\/a><\/p>\n
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AccessData (US), Catalyst (US), Epiq (US), FTI (US), IBM (US), Micro Focus (UK), Microsoft (US), Nuix (Australia), OpenText (Canada), and ZyLAB (Netherlands)<\/div>\n<\/div>\n<\/div>\n
eDiscovery Market by Component (Software (Processing, Review and Analysis, Identification, Preservation and Collection, and Production and Presentation) and Services), Deployment Type, Organization Size, Vertical, and Region – Global Forecast to 2023<\/div>\n

The global eDiscovery Market<\/a><\/strong> is expected to grow from USD 10.76 billion in 2018 tand expected to reach USD 17.32 billion by 2023, at a compound annual growth rate (CAGR) of 10.0% as per a report by MarketsandMarkets. <\/p>\n

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Why increased demand for predictive coding to simplify and shorten document review process<\/strong> is an opportunity?<\/strong><\/p>\n

Predictive coding is essentially a machine learning process that uses computer algorithms and software to determine which documents are relevant to litigations by self-learning. The self-learning of the logic required for eDiscovery is based upon a review of test documents by lawyers and attorneys. The eDiscovery software then applies the same algorithm to a larger document group, thus making the document review process less difficult and less complex. The predictive coding makes eDiscovery reviews more efficient, thereby resulting in cost savings and skillfully countering the explosive growth in digital data. Several courts across the world have already approved the use of predictive coding for the discovery of relevant electronic documents. The predictive coding is becoming one of the integral aspects of litigations. eDiscovery vendors are cashing in on the opportunity of increased demand for predictive coding, and are devising new eDiscovery solutions and services, which make the use of this technology.<\/p>\n

Download PDF Brochure @ https:\/\/www.marketsandmarkets.com\/pdfdownloadNew.asp?id=11881863<\/a><\/strong><\/p>\n

How limited technical expertise for managing the advanced eDiscovery mechanism<\/strong> poses a major challenge?<\/strong><\/p>\n

The enterprises are facing new security and data breach threats due to ever-changing technology landscape and product innovations. Moreover, organizations are in an incessant pursuit to better cater to their customers by continuously upgrading and changing their products, and introducing new eDiscovery solutions for improved business and operational activities. This implies that legal departments in organizations need to constantly tune its eDiscovery solutions to address their litigation needs and effectively protect enterprises without any hurdles. This tuning requires security professionals to have a deep understanding of protocols, security, and eDiscovery offerings being deployed. They need to understand the application along with the threats, such as frauds, spoofing, and DDoS attacks. Additionally, they should be able to write policies for deployed eDiscovery solutions to protect enterprises’ data. Such skills are hard to find in an already limited pool of professionals. Thus, the lack of skills and limited technical expertise are expected to pose a challenge for the successful implementation of eDiscovery solutions across enterprises.<\/p>\n

Speak to Our Expert Analyst @ https:\/\/www.marketsandmarkets.com\/speaktoanalystNew.asp?id=11881863<\/a> <\/strong><\/p>\n

AccessData (US), Catalyst (US), Epiq (US), FTI (US), IBM (US), Micro Focus (UK), Microsoft (US), Nuix (Australia), OpenText (Canada), and ZyLAB (Netherlands) are the major vendors in the eDiscovery market.<\/p>\n

Media Contact<\/span>
Company Name:<\/strong> MarketsandMarkets<\/a>
Contact Person:<\/strong> Mr. Shelly Singh
Email:<\/strong> Send Email<\/a>
Phone:<\/strong> 1-888-600-6441
Address:<\/strong>630 Dundee Road Suite 430
City:<\/strong> Northbrook
State:<\/strong> IL
Country:<\/strong> United States
Website:<\/strong> https:\/\/www.marketsandmarkets.com\/Market-Reports\/e-discovery-market-11881863.html<\/a><\/p>\n

\"\"<\/p>\n","protected":false},"excerpt":{"rendered":"

AccessData (US), Catalyst (US), Epiq (US), FTI (US), IBM (US), Micro Focus (UK), Microsoft (US), Nuix (Australia), OpenText (Canada), and ZyLAB (Netherlands) eDiscovery Market by Component (Software (Processing, Review and<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[],"_links":{"self":[{"href":"http:\/\/www.honolulunewsnow.com\/news\/wp-json\/wp\/v2\/posts\/172901"}],"collection":[{"href":"http:\/\/www.honolulunewsnow.com\/news\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.honolulunewsnow.com\/news\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.honolulunewsnow.com\/news\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/www.honolulunewsnow.com\/news\/wp-json\/wp\/v2\/comments?post=172901"}],"version-history":[{"count":0,"href":"http:\/\/www.honolulunewsnow.com\/news\/wp-json\/wp\/v2\/posts\/172901\/revisions"}],"wp:attachment":[{"href":"http:\/\/www.honolulunewsnow.com\/news\/wp-json\/wp\/v2\/media?parent=172901"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.honolulunewsnow.com\/news\/wp-json\/wp\/v2\/categories?post=172901"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.honolulunewsnow.com\/news\/wp-json\/wp\/v2\/tags?post=172901"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}