Way back in 1982, author John Naisbitt claimed that we’re drowning in information but starved for knowledge. Nearly four decades later, most of that information exists in digital form, but the same rule applies. Digital data is increasingly behind everything we do, but many companies are still only using 10% of their data to drive smarter decision making. The biggest problem is that data sets have expanded beyond the ability of businesses to manage it. They don’t know where all their data lies in today’s complex multi-cloud environments; data overabundance is making it harder to identify what’s important and what’s not, while the wealth of unstructured data renders conventional data insight solutions obsolete.
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 their side, businesses can also take advantage of practically unlimited storage space and compute power. Today’s data insight 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.