With cybercrime rates at all-time highs, today’s technology-driven business world is no stranger to being hit hard by data breaches, and as regulatory compliance laws mandate that businesses do all they can to keep sensitive data out of the wrong hands, preparing to face litigation has become a huge part of the clean-up process in the aftermath of an incident.
What business owners may not realize, though, is that proactive data governance is one of the best ways to help their business through such a costly process. For those unfamiliar with eDiscovery and how data mapping and inventory can help with the process, it’s a good idea to get educated before litigation becomes your reality.
What is eDiscovery, and why is data mapping so crucial to the process?
Data mapping is vital to the eDiscovery process because it helps an attorney find exactly what they’re looking for when they dive into your system.
In its simplest definition, eDiscovery is a digital version of the classic discovery process in civil and criminal cases, requiring both parties to exchange electronic data and information during the discovery phase of a legal proceeding. Data mapping is a form of data governance that creates an organized inventory of all the company’s available data.
Despite its digital nature, eDiscovery is a notoriously costly process. Data mapping is vital to the eDiscovery process because it helps an attorney find exactly what they’re looking for when they dive into your system. In turn, it makes the process less expensive and more likely that an attorney will have what they need during litigation.
Foundations for the Data Mapping Process
Those new to data governance or the data mapping process may wonder what it entails. To that end, below is a breakdown of the process any business should engage in as it takes inventory of its data:
Data Types
The eDiscovery process has legal policies that govern what is seen as data. Consequently, you should be taking inventory of anything that might be included in that definition. Consider user-created data like emails, reports, and word processor documents, as well as structured customer data or financial entries. Don’t forget to include information that isn’t on a computer, such as text messages on a smartphone.
Storage Locations
Has it been archived? Is it on a legacy system or a decommissioned server? Your answers will be crucial for an attorney who may need to access the information.
Your data may be stored locally on your laptop or phone or in an offsite cloud server. That said, not only do you need to know the physical location of every piece of data, but you also need to make note of how accessible it is. Has it been archived? Is it on a legacy system or a decommissioned server? Your answers will be crucial for an attorney who may need to access the information.
Responsible Parties
Those responsible for collecting and managing a particular dataset will most likely know how the included data gets used, where it gets sent, and how it can be accessed. Still, as you take inventory of responsible parties, note that they may not be people or entities working at the company — you may need to look to a cloud or managed service provider.
Archival and Deletion Dates
Understand when it’s time to get rid of data and ensure you follow through on the process.
Regulatory compliance laws require most companies to have responsible data disposition policies. In some cases, data must be destroyed within a certain time frame from its last use.
As holding on to old data costs a company in many ways, including larger data storage fees and higher eDiscovery costs, understand when it’s time to get rid of data and ensure you follow through on the process.
Let an Experienced eDiscovery Attorney Go to Work for You
When facing litigation, the eDiscovery process can seem daunting, but an experienced attorney at Lancaster Tech Law can help Pennsylvania businesses structure their data inventory in a way that increases their chances of a successful outcome. Call today to discuss your case and your next steps toward proactive data governance.