Whether you’re looking at the issue from the point of view of an academic or historian, or the viewpoint of a business looking to optimize its operations, data preservation and the issues surrounding it has quickly become one of the most crucial challenges facing modern thinkers.
When people speak about data preservation today, they’re mostly discussing the issue of digital data preservation—the art of ensuring continued access to digital materials for as long as is possible and necessary. In other words, making sure the files and data used by organizations today will still be easily accessible through the lifespan of the company—and beyond.
There are several unique challenges faced by anyone undertaking the issue of data preservation, whether for altruistic or professional reasons. These include, but are not limited to:
- Scope. Digital data preservation can encompass anything and everything, but rarely needs to be so exhaustive.
- Proprietary storage. Storage formats and file types unlikely to be readily accessible in the future are an impediment to long term data preservation.
- Organization. Data stored in a manner that renders it little more than a digital junkyard isn’t particularly accessible, even if it is technically preserved.
- Long term storage. The data used in academia, business, and other fields has grown faster than the price of storage has dropped—meaning long-term storage of data must be highly efficient lest the expenses outpace the value of preservation.
Of course, data preservation isn’t simple for some nebulous future benefit. Modern businesses can leverage the principals of effective data preservation to practical ends today, with the benefits only growing over time.
- Efficiency. Good data preservation practices are cost efficient practices. By adopting them today, companies can save money wasted on inefficient storage, inefficient management, and wasted man hours.
- Growth and development. Good data preservation practices play two roles in the growth of a business: First, as a step towards improved scalability of operations, and second, as a robust source of data for analytics and well-informed decision-making.
- Insight. As analytics suites grow increasingly robust, the value of company data increases. A person may not be able to see the patterns in terabytes upon terabytes of raw data, but the latest prescriptive analytics suites can turn that raw data into actionable insights.
- Liability. Thorough documentation will always play a key role in minimizing corporate liability. If your company finds itself facing a lawsuit decades down the road related to operations today, it’s critical that you have easy and ready access to the same files and information you’re looking at now.
Of course, data preservation isn’t purely a matter of pragmatism. There’s a strong argument in favor of future-conscious preservation practices, lest the abundance of information available today vanish in the face of unsustainable storage practices, obsolete proprietary formats, and other issues of today. Data holds value, even if the companies which one used it have long since moved on to other challenges and business models—if only as a window into the business practices and markets of a bygone era. As automated analysis programs grow to maturity, this data could become increasingly useful in developing effective tools for businesses, governments, and other organizations.