Poor data quality is estimated to cost organizations an average of $12.8 million per year. All methods of data governance are vital to combating this rising expense. While metadata has always been recognized as a critical aspect of an organization’s data governance strategy, it’s never attracted as much attention as flashy buzzwords such as artificial intelligence or augmented analytics. Metadata has previously been viewed as boring but inarguably essential. With the increasing complexity of data volumes, though, metadata management is now on the rise.
According to Gartner’s recent predictions for 2024, organizations that use active metadata to enrich their data will reduce time to integrated data by 50% and increase the productivity of their data teams by 20%. Let’s take a deeper look into the importance of metadata management and its critical factors for an organization.
What is Metadata?
Metadata is data that summarizes information about other data. In even shorter terms, metadata is data about other data. While this might sound like some form of data inception, metadata is vital to an organization’s understanding of the data itself and the ease of search when looking for specific information.
Think of metadata as the answer to the who, what, when, where, and why behind an organization’s data. When was this data created? Where did this data come from? Who is using this data? Why are we continuing to store this information?
There are many types of metadata, these are helpful when it comes to searching for information through various key identifiers. The two primary forms of metadata include:
- Structural – This form of metadata refers to how the information is structured and organized. Structural metadata is key to determining the relationship between components and how they are stored.
- Descriptive – This is the type of data that presents detailed information on the contents of data. If you were looking for a particular book or research paper, for example, this would be information details such as the title, author name, and published date. Descriptive metadata is the data that’s used to search and locate desired resources.
- Administrative – Administrative metadata’s purpose is to help determine how the data should be managed. This metadata details the technical aspects that assist in managing the data. This form of data will indicate things such as file type, how it was created, and who has access to it.
What is Metadata Management?
Metadata management is how metadata and its various forms are managed through processes, administrative rules, and systems to improve the efficiency and accessibility of information. This form of management is what allows data to easily be tracked and defined across organizations.
Why is Metadata Management Important?
Data is becoming increasingly complex with the continually rising volumes of information today. This complexity highlights the need for robust data governance practices in order to maximize the value of data assets and minimize risks associated with organizational efficiency.
- Lowered costs associated with managing data
- Increases ease of access and discovery of specific data
- Better understanding of data lineage and data heritage
- Faster data integration and IT productivity
Where is this data coming from?
Show me the data! Not only does metadata management assist with data discovery, but it also helps companies determine the source of their data and where it ultimately came from. Metadata also makes tracking of alterations and changes to data easier to see. Altering sourcing strategies or individual tables can have significant impacts on reports created downstream. When using data to drive a major company decision or a new strategy, executives are inevitably going to ask where the numbers are coming from. Metadata management is what directs the breadcrumb trail back to the source.
With hundreds of reports and data volumes constantly increasing, it can be extremely difficult to locate this type of information amongst what seems to be an organizational sea of data. Without the proper tools and management practices in place, answering these types of questions can seem like searching for the data needle in a haystack. This illuminates the importance of metadata management in an organization’s data governance strategy.
Metadata Management vs. Master Data Management
This practice of managing data is not to be confused with Master Data Management. The two have similar end goals in mind when it comes to improving the capability and administration of digital assets. But managing data is not all one and the same, the practices are different through their approaches and structural goals. Master data management is more technically weighted to streamline the integration of data systems while metadata management focuses on simplifying the use and access of data across systems.
Metadata management is by no means new to the data landscape. Each organization’s use case of metadata will vary and evolve over time but the point of proper management remains the same. With greater data volumes being collected by companies than ever before, metadata is becoming more and more critical to managing data in an organized and structured way, hence its rising importance to one’s data management strategy.