In the world of digital asset management, nothing happens without data.
You can’t find content without it. You can’t effectively create content without it. And you certainly can’t track or measure performance without it.
Data powers everything you do in your DAM, and it enables your users to take the actions they need within the system to do their jobs effectively. And yet, despite its importance, data in DAM continues to be one of the things users struggle with the most.
Why is that?
To put it simply, DAMs are complex systems that manage thousands, sometimes millions, of digital assets on behalf of users – users who are human, and may engage with this content in unique and unpredictable ways. No wonder, then, that it’s difficult to truly understand how to structure your data in a way that is most effective.
That’s why we’ve asked for help. In this guide to data in digital asset management, we’ve partnered with some of the industry’s leading experts and consultants, and asked them to explain how data in DAM works, and how you can leverage it to its greatest potential – whether that’s to improve team productivity in the DAM, increase findability of assets, or maximize the value of modern technologies like AI in your platform.
In this guide we’ll cover:
- Metadata in digital asset management
- How to think about keywording and how it’s different from other forms of metadata
- How your digital asset management data should mature and evolve
- The future of data in DAM, with a focus on AI and machine learning