If we begin with this analogy, that ONE BYTE OF DATA = ONE GRAIN OF RICE. Here is what that volume looks like if we apply it to the larger units of measure for data sets.
“Conferences can be overwhelming: they’re loud, bright, full of new faces and punctuated by advertisers jostling for your attention. Without a clear plan of action, professionals risk wasting an invaluable opportunity to learn and develop”Charlotte Woffindin, Senior Product Manager, Amazon UK
Many conference goers suffer from FOMO (fear of missing out). They pack their day full of sessions only to find themselves overloaded with information and turning into a conference zombie. Pick your “A” sessions first and then talk to others about which ones they are attending and why?
Records Managers have the toughest job. They are supposed to tell everyone who can "save a file and where" which inevitably disrupts the way everyday users work. They build out proper taxonomies and then add a bunch of metadata on top of it, which is a recipe for unmanaged data and unhappy users. Their projects are measured in years and rarely cause a ripple in the pond of data. Imagine that you are tasked with understanding an ocean of data and every single file's life-cycle with a budget that gets you an ice cream cone and last years Super Bowl hat.
Overcoming a case of AI FOMO - published Janurary 2018
Just over a year ago, we discussed the urgency of Artifical Intelligence projects on our blog. In early 2018, organizations were trying to grasp how best to implement AI solutions before they fell dangerously behind. Now in 2019, the challenge is still the same, but companies are finally starting to realize what's causing the pain. (Hint: it's data).
Organizations need to improve data quality and information architecture to power their transformational efforts. Artificial Intelligence and Machine Learning have proven effective tools to gain insight into enterprise documents and kick off the journey to automation.
The promise of Artificial Intelligence has been dominating the headlines for the last few years, promising massive disruption across all industries. “Fifty-three percent of global data and analytics technology decision makers are implementing or expanding their use of AI, while another twenty percent plan to implement AI in the next 12 months.”1 Even though AI has been dominating the headlines in 2018, there has still been very few massive deployments of enterprise AI. Instead, CXOs have been focusing on quick win AI projects to drive real ROI. In 2019, this shift will continue as organizations realize that a massive enterprise AI deployment is not possible with the current state of their data.