What is Metadata Management and How Can IT Teams Do It Better?
Businesses run on data. Metadata is the foundation for making that asset usable.
The simplest way to define metadata is that it’s data about data; it helps organizations find, maintain and compare data. AsGartner explains, metadata describes the various facets of an information asset that can improve its usability throughout its lifecycle.
“Data about your data lets you understand its importance, accuracy and relevance to the business,” says Jay Limburn, director of product offering management and distinguished engineer withIBM Data and AI.
More Big Data and a growing number of data consumers means there’s an increased urgency to adopt or improve metadata management for organizing information assets. The increasing need for data governance, risk and compliance, data analysis, and data value drives the growth of metadata management solutions, according to Gartner.
“Metadata management is getting more attention because it is now part of the business conversation,” says Reetika Fleming, research vice president at HFS Research. The global enterprise metadata management market is projected to reach$9 billion by 2023.
Metadata puts data and its associated processes, services, rules and policies that support an organization’s information systems into context. Types of metadata in the context of data management environments are:
By also defining who gets access to the data, administrative metadata “directly informs organizational policy and vice-versa, and helps with governance,” says Jeffrey Pomerantz, associate professor of practice at the School of Library and Information Science at Simmons University and the author of “Metadata.”
Companies have been accumulating data for years in multiple systems with inconsistent associated metadata. The integration of social media data and its associated metadata creates additional complications.
Business intelligence is one of the most important solutions for metadata management, Fleming says. It’s often the case that business users and analysts confront data in a report that doesn’t make sense or is incomplete, or that the same report generated in two different reporting systems shows two different results.
Metadata makes it possible to locate and verify data, and metadata management makes it possible to trace the lineage of that data so that its quality can be assessed before it is loaded into an analytics tool. “If we can understand the quality of our data and where it’s being used, we can expose rich data to the business community,” Limburn says.
Metadata management in the past has been a long, laborious and expensive process, requiring many data curators and stewards to stay on top of an ever-growing and changing amount of data. Automating the discovery and data movement processes makes metadata management easier. Time can be saved, and errors and costs reduced, when metadata is automatically discovered from sources including databases and reporting tools versus using a manual process to expose the data journey.
There has been a lot of progress on automated tagging and creation of metadata content using technologies like machine learning, according to Fleming.
