We’ve wrote about metadata before (here it is, in case you missed it). Simply put, metadata summarizes basic information about data, making it easier to find and to use specific instances of data. Every single piece of data contain metadata, and managing it can be a daunting task, that’s why there are tools available to manage it, in turn making your life easier.
How is metadata generated?
Metadata doesn’t just come into existence on its own, it is created when the data itself is created, added to an organization tool, or moved. There are many different types of metadata, such as:
- Time of creation.
- Method of creation.
- How it was obtained.
- Size, colours, compression type (for images).
- Who is allowed to see or use the asset.
- How can it be used.
- What other users have done with it.
What is a metadata management tool?
If an organization doesn’t have a way to organize and process metadata, it will just waste precious space, and not be as useful as it could be.
To have all metadata organized and optimized the best option is a metadata management tool. It’s a software that help organize, store, categorize and analyse information on an organization’s datasets, helping better optimize the use of data, in turn helping an organization make better use of its benefits.
By providing a standardized way to store and manage metadata, these tools can help organizations ensure that data is used in compliance with regulatory requirements and internal policies.
These tools can also improve data quality, by enabling organizations to track data from its origin and identify any issues or errors, improving data accuracy.
Examples of metadata management tools
While there are many different tools to manage metadata, each has its specific characteristics, so an organization must first understand what it needs and choose the best tool to accomplish its goals.
Some of the tools available are:
- Metadata harvesting – These tools enable the collection and management of metadata from diverse sources in a standardized form. The process involves gathering metadata from various sources and aggregating it in a central location, where it can be searched and analysed.
- Metadata ingestion and translation – These tools translate metadata from diverse sources into a standardized format that can be integrated in a management system. The process involves identifying metadata sources, extracting metadata, and translating it into a usual format.
- Data catalogs – These tools focus on data discovery, helping users find and understand the data they need. They typically provide a searchable catalog of data assets, along with metadata such as data source, structure, and lineage.
These are just a few examples of tools and there are many more available, each with its specific use.
AI and Machine Learning metadata management tools
These solutions enable metadata to work for you on its own. Machine learning algorithms analyse datasets, finding all metadata, categorizing it, and making it active and intelligent. With these solutions, metadata errors can correct themselves, enriching the quality of the whole dataset.
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Your content and data are the foundation upon which your business operates, and critical decisions are made. Recent advancements in AI in areas such as image and natural language processing have enabled a whole new level of automatic extraction of information and data analysis that power the automation of key business processes not possible until now.
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