This is a guest post by Dana Simberkoff, Vice President, Risk Management & Compliance, AvePoint . For most organizations worldwide, it’s no longer a matter of “if” they will move to the cloud but rather “what” they will put in the cloud. Keeping...
For this reason, risk analysis programs should also include the assessment of the quantity and broad content of legacy data. With today’s computer technology it is very easy to analyze legacy data and search for keywords or linguistic patterns related to all kind of risk, regardless of file format, content type (text, audio, image, or video) , location, or language
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Therefore when considering a legacy data clean up, creating a filing plan is a good starting point...This will ensure that you identify non-existing categories during the processing of the legacy data
In the following graph, the impact on early legacy data clean-up is shown...So, in time, legacy data clean-up pays itself back with an exponential return of investment!
Although storing 250GB of data can cost less than $250, hiring an external firm to process and review this data for e-discovery can cost up to $1 million. The impact of these costs is particularly noticeable to in-house legal teams and support staff who are often at the front lines of any e...
Juhnke brings more than 25 years’ experience to her work in records inventory, retention schedule and policy development, project management, records management program implementation, and legacy data cleanup
Gaining control over the vast amounts of legacy data you already have should be approached in a similar fashion as setting up your go-forward structure for records and information management: 1
Obviously, the results do not only apply to the use of Machine Learning in eDiscovery, but also to Legacy Data Clean-up, Defensible Disposition, and Automatic data classification in records management, enterprise information archiving and intelligent data migration from legacy systems to for instance the cloud
” CCAs allow access to multiple data sources and foster the merging of real-time and legacy data into a single interface in order to simplify a complex business process