Metadata management can offer many benefits for businesses, for a number of reasons. It is used to establish and enforce rules on defining and discovering an organization’s data assets. Among other things, this allows researchers to locate data quickly and efficiently and helps promote accurate data use. Metadata management is the organization of metadata for research purposes, emphasizing the data’s lineage and associations. 

Metadata is essentially a labeling system, an abbreviated description of a data asset’s contents and history, which is designed to provide context and useful information about a specific file or data asset an organization is using.

Generally speaking, metadata exists behind the scenes, with researchers relying on search engines to find the file or data asset they want. Metadata plays an essential role in successfully locating data and extracting value from it. Metadata management can be used to help businesses manage their product and customer strategies. It also supports businesses as they strive to continuously meet changing customer demands. 

Metadata management is the oversight and control of this labeling system. The process involves creating policies and procedures that will ensure data can be located, integrated, accessed, linked, shared, and/or analyzed. Metadata provides the basic information about a data asset: the file type, the size of file, the time of creation, the author, and more. Metadata management determines what information is shown in the label. This process provides context to the metadata and allows an organization to maximize its use of data to develop actionable insights about customers and the efficiency of the business. 

Metadata is generated whenever data is: 

• Accessed by users 
• Profiled
• Taken from a source 
• Cleansed 
• Analyzed
• Moved through an organization
• Integrated with data from another source

Metadata can be created manually or automatically. Manually creating metadata supports more detailed, more creative metadata, while metadata created through automation normally contains only the most basic information. Some metadata managers use automation to label the majority of their data assets but will manually label important or vital data assets. 

A robust metadata management strategy supports high-quality data, as well as other benefits, such as compliance with privacy regulations. Metadata management is an important feature in Data Governance, and a well-designed metadata management system promotes both better decision-making and improved regulatory compliance. Poor metadata management can result in lost opportunities and higher expenses.

Finding the Metadata

To find a file’s (or photo’s) metadata, click on the file or image. Then move to the File menu, and click File Info (for Microsoft) or Get Info (for Macs). When the information pops up, the metadata can be copied or edited. Some basic visual examples for manually working with metadata can be found here.

Adopting Metadata Standards and Schema

In order to be functional, metadata must be standardized. Metadata standards include a common language, date formats, spelling, etc. They support good communications between computer systems. With no metadata standard in place, comparing data sets can be very difficult. You should choose metadata standards based on your organization’s specific industry needs and your organization’s goals.

Metadata standards provide uniformity within the metadata. 

An important component of metadata is its schema. Metadata schemas are outlines of the metadata’s overall structure. It is a logical plan that shows the relationships between metadata elements. They contain the overall layout of the metadata’s information and normally address the standards applied to the metadata. Some metadata schemas address specific industry needs. 

Without clearly defined metadata standards, a computer system’s functionality drops dramatically because new, incoming data may be unusable. 

The Benefits of Good Metadata Management

Good metadata management requires automation, or very quick, very precise manual work. While manually describing a data asset can be useful for unique identification purposes, attempting to manually describe the bulk of your data in a metadata format is quite time-consuming and supports human errors. 

An automated metadata management system will provide the following benefits:

• Improved digital transformation: Historically, when an organization shifted from paper format to digital format, it has been (and still is) called digital transformation. Generally speaking, however, modern digital transformation is done on a much smaller scale. For example, the paperwork filled out by a salesperson when their smartphone is out of range would need to be digitally transformed later. A good metadata management program will “label” a new file, or alter the old metadata, with a minimum of effort and human error.

• Improved Data Governance programs: Modern Data Governance relies on metadata because it can be helpful in dealing with many of the core issues Data Governance is designed to control. These issues include a lack of data standardization, ambiguous data ownership, data security concerns, compliance concerns, etc. Metadata as a labeling and communications system helps resolve these concerns and provides a way to track the data’s lineage. Additionally, metadata is necessary for developing a business glossary.

• Improved productivity: The most obvious way metadata improves productivity and efficiency is by making it easy for users to locate the right document. Through its label, the data can be found even when it’s saved in an illogical or unexpected location. Finding data/information quickly and efficiently has the effect of boosting productivity. Using metadata to classify and organize documents makes research much easier and reduces the time needed to find the desired document.

• Improved regulatory compliance: Regulations, such as the CCPA (California Consumer Privacy Act), GDPR (General Data Protection Regulation), and BCBS (Basel Committee on Banking Supervision) are impacting the financial, retail, healthcare, and pharmaceutical industries. With automated metadata systems, sensitive and private data is tagged automatically, and data lineage is automatically documented for tracking purposes.

• Improved Data Quality and searchability: Automated metadata management solutions can be used to standardize, classify, and corroborate incoming data, in real time, and reduce the potential for human error. Effective metadata management assures the storage and use of high-quality data.

• Improved speed and efficiency: Without the appropriate metadata management tools and practices, over 80% of a researcher’s time is spent searching for data, and then preparing it. A metadata management system can accomplish these tasks in seconds, rather than hours. Projects requiring research are accomplished much more quickly.

• Improved data consistency: As an aspect of improving Data Quality, metadata can be used to standardize data, eliminating the potential for errors caused by conflicting terms. Data formats, languages, and other consistency issues are transformed into compatible data. Improved data consistency makes it easier to retrieve data, reducing the time it takes to apply data to projects.

• Reduced storage costs: Automated metadata management solutions promote lower storage costs by reducing redundancy and unnecessary storage expenditures.

• Improved marketing strategies: Marketers can use metadata to monitor the use of content. A website selling merchandise can track their customers’ interests as they browse potential purchases. Marketers can gather metadata to provide context to these viewings and promote on-page marketing strategies to increase sales. For example, a website including a section titled “people who bought this item also bought these” may increase sales. Metadata management may also be used to improve customer retention strategies. 

Effective Metadata Management

Effective metadata management is needed to ensure compliance with data protection regulations such as the General Data Protection Regulation and the California Consumer Privacy Act. These regulations require businesses to keep detailed records of their data processing, including records of the data they have collected, its purpose, and whom it was shared with. Metadata can be used to provide the documentation needed to show compliance and help businesses avoid expensive fines and damage to their reputations.

Developing a robust metadata management strategy involves using a combination of software and people. It also requires investing in tools that can collect, store, and organize metadata efficiently. These tools can offer a comprehensive view of the organization’s data, and may include data catalogs, data lineage tools, and metadata repositories. With these tools, metadata can be used to support a common language, promoting a form of harmony.

Donna Burbank, Global Data Strategy’s managing director and author of Data Modeling Made Simple and Data Modeling for the Business, addressed the benefits of metadata management in an interview: ”What’s obvious to one person is never obvious to another person, so get it out of people’s heads and put it in a glossary, a metadata repository, or a data catalog.”

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