That’s the focus of my latest post on the Ediscovery Insight Blog. Obviously, it focuses on AccessData’s eDiscovery platform, but the idea of cutting costs by cutting down the amount if data to review, and having an efficient workflow, applies no matter what technology you are using!
Follow these topics: LitigationSupport
Beware of Too General Production Agreements in E-discovery | Florida Injury Lawyer Blog tags: MM LitSupport Hackers hide child abuse images on the servers of legitimate websites Might want to be aware of what is being stored on your web server if you host your own site. tags: Security MM CA 9 Tips on Preparing…
If you were intrigued by the 3 minutes Josh Gilliland and I spent talking about Social Networking and eDiscovery at ILTA a couple of weeks ago, you might want to check out the Social Media and eDiscovery webinar that is being put on as part of Virtual LegalTech on Sept 23. The panel looks to…
Imagine a day when technologists, lawyers, and vendors could have easy conversations about eDiscovery because they all have a deep understanding of the technology and tools involved. We don’t see it often, and that causes some real problems as we see from some of the cases we all read about. Maybe someday.
15 Things Companies Should Stop Doing If They Want To Improve Their Cybersecurity
Looking Back at 2022 in LegalTech Reveals Trends Going into the New Year: An Ediscovery Day Recap
The Economic Cost of Poor Employee Mental Health– Yes the costs can be large, but pay attention to the issue because you care about the people who work for you regardless.
“There’s been a lot of data breaches lately, and the numbers seem to be constantly increasing. From the high profile attacks against the likes of Ashley Madison and Sony Pictures, to the lesser known breaches like Kmart Australia and Systema Software, it’s practically becoming routine to read a headline that says, “Company X breached; data…
In the age of AI, though, this might be the high-priority risk. That old, untrustworthy, and outdated information that no one ever bothered to clean up is actively messing up your AI implementation. Your attempt to be a data-driven business depends on having accurate data. That becomes difficult to do when you’re not actively cleaning up after yourself.Â