Sr. VP IT Operations and Security at Stream Realty Partners

As the cliché goes, those who fail to learn from history are doomed to repeat it. Can this cliche be true if we were to apply it to old legacy data that we have been forced to carry forward for long beyond all our compliance and regulatory required time frame? Looking back a decade or two, I can easily remember one of the greatest challenges was what to do with old data. Do you really have to keep data that is 10+ years old? Who still looked at that data? Who would even remember it existed? Little own know where it was and provide IT enough information to request it be returned from off storage. What about the never-ending costs that were associated with what would be deemed low-value data 99 percent of the time?

 With the emergence of cloud storage and storage as a service, even the financial hurdles might soon be something we can overcome. 

Clive Humbly is credited with saying, "Data is the new oil," and while it was true then, it is even truer in the age of LLM, AI, and the entire emerging tech. Each of these systems has an incredible appetite for data if they are going to be useful to us. Ten years ago, as data analytics were emerging, it was still a very labor-intensive process to harness raw data and turn it into useful information. That challenge, while it is not cured, is quickly fading. Unstructured data, old files, financial data, etc., can all be harnessed by this emerging tech.

All of that old data, if brought online, could be ingested into one of these AI tech models. What insights could business leaders gain from product deployments, projects, marketing launches, etc., that were unavailable in the past? We could potentially look back and find out why they worked. We could analyze consumer trends, recognize the human behavior of a particular generation at a point in time and see if it correlates to a new generation that is reaching that same age range.

While storage still has a significant cost associated with it. It may prove to be a very worthwhile investment if you can harness all of it to gain historical insights that allow your business to maximize its growth by staying true to the most historically efficient launches. With the emergence of cloud storage and storage as a service, even the financial hurdles might soon be something we can overcome. Scale up, scale down, ingest data in 5–10-year increments, build your models, capture insights and perhaps only track useful summaries that can be ingested and analyzed by the AI model. Keep repeating until you can survey the entire landscape of your business history. You could then compare against the annual reports of your competitors and then see what succeeded and what failed for them.

The question is ‘no longer who can use this data?’ Instead, the question has changed to 'What can we do with this data?' How can we maximize the return on all our data? How can you harness your company's new modern 'Oil' in a profitable and productive way?