What are Unstructured Data?
These are data stored in a native format and processed only when needed. Unstructured data comes in various formats, such as emails, social media posts, presentations, chats, IoT sensor data, and file server data. These datasets are organized individually, varying from person to person based on personal thinking and organizational methods.
What are Structured Data?
Structured data is processed in databases according to universally accepted rules. The processing of information follows a clearly defined process with explicitly assigned “locations.” Common examples of structured data include weblog statistics, point-of-sale data like barcodes and quantities. Additionally, spreadsheet applications are familiar to anyone dealing with data.
In the event of a legal dispute or an impending legal process, when documents and data need to be preserved for evidence without alteration, deletion, or manipulation (= Legal Hold), this poses a significant challenge for a company in its data management, especially with unstructured data. Tems Security gladly offers its eDiscovery solution for identifying, searching, and filtering this data set. EDiscovery is a digital investigative method that aims to find and secure evidence in emails, business communication, and other data for use in legal disputes or criminal proceedings.
It is essential to not only identify and secure the data and data sources but also, with the employees’ consent, ensure that the data remains usable, accessible to multiple users simultaneously, and can be systematized and processed without altering the original documents. Without an eDiscovery system, this is not only unimaginable today but also hardly feasible due to the high density of data. Tems Security has the right solution for every unique case!
An additional objective of eDiscovery is to reduce costs for this process by decreasing turnaround times for archiving, deduplication, collection, work, filtering, and searching. Ultimately, the eDiscovery-optimized process ensures that not only all data has been processed during the final reviews but also that all relevant data has been filtered from a system. The entire data volume is thus reduced to relevant data, facilitating the discovery of the digital needle in the haystack when needed.