In 1860, French inventor Édouard-Léon Scott created the first ever audio recording using his phonautograph, which he’d patented three years prior. But it wasn’t until almost a century and half later that audio historians found a way to play it back. Today, we take our streaming media for granted in a world where technology is moving faster than ever before. Even though we’ve been digitising information since the 50s, data migration has shifted from magnetic media to solid-state and, much more recently, to the cloud. Physical media is fast disappearing, as are the computers beneath our desks, but despite data itself being potentially eternal, the rapid change in the way we generate and store information presents some unique challenges.
The first big challenge was the constant pace of evolution in physical and digital media. The quest to find more efficient and reliable digital storage mediums saw rapid obsolescence to the point you’ll have a hard time trying to migrate data from, say, a digital compact cassette or a quick disk. The challenge is even greater when migrating from analogue formats and those which were a commercial failure, such as Betamax. But today there’s a new challenge – access to cloud-based systems has brought data to the masses in scales never seen before. File sizes are growing, and content creators are worried about losing control in an age when everything is stored in remote data centers operated by third parties.
In every industry, especially in content-heavy ones like the entertainment sector, implementing a data migration strategy that future-proofs and secures informational assets has become a core priority. What’s more is that organisations need a better way to manage their data assets across increasingly diverse ecosystems, and artificial intelligence is one such solution for making sense out of unstructured data.
Figuring out how to drive greater value out of data is one of the biggest challenges in strategic decision making. Businesses are turning towards artificial intelligence and machine learning to make sense out of big data, particularly that which exists in unstructured form. Automatically extracting metadata from both physical and digital media, whether it’s information archived on tape drives or office documents hosted in the cloud, gives decision makers a strong start. With the cloud on side, businesses can also take advantage of practically unlimited storage space and compute power. Today’s data insights solutions can extract metadata out of unstructured data, categorise information, and help automate the application of data retention policies.
This gives business leaders the means to easily access, search through, and visualise data from any source. They can easily apply policies in a time when data privacy and security are some of the biggest concerns of all. They can manage the full lifecycle of data more efficiently. They can automate a multitude of routine tasks. And, above all, they can enable more strategic decision making and drive newer, smarter processes.