In every organization, there is an undeniable need to realize the total value and quality of every piece of data. The problem is that as time has progressed, we face an extreme growth in volume from big data collection. This has placed a higher emphasis on metadata management to contextualize and organize all the information being brought into an organization.
Metadata is generated every time any new data moves through an organization. It has slowly become one of the critical resources of a business because it is the data about data. It is the necessary information vital in unleashing the full potential of understanding where data came from, how it is referenced, and the best ways to use it in your systems.
The Power of Metadata Management
If metadata is the specific data about data, then metadata management is used to establish policies that create context and value for all the data moving through your organization. It ensures that all of your assets can be quickly discovered, measured, and shared in the most appropriate places for your internal and external users.
Proper metadata management allows you to identify data sources, track data movement and utilization and maintain an audit trail to meet compliance requirements. This includes everything from where the asset should be stored to when it was created.
There are three primary metadata types that can be leveraged, including:
Structural Metadata
This is how you index data assets for easy navigation, relationships, and references. Think of this like a table of contents or the individual chapters in a novel.
Administrative Metadata
This is more on the technical side of data assets. It logs the critical source information of a data asset, like the type of file, when it was created, usage rights, rendering files, and other technical details.
Descriptive Metadata
This is the discoverable information that is best used to organize metadata. If you were doing a search at a bookstore, this would be the author, title, genre, keywords, etc.
How is a Data Catalog Different than Metadata Management?
The primary purpose of a data catalog is to create an organized inventory of all your data assets. Once that mapping process has unfolded, you use the data catalog to index everything into easily discoverable storage locations.
The metadata of these assets differentiates the information by tagging, storing, and collecting different datasets.
Data catalogs and metadata are interconnected in that one indexes your data, and the other helps you understand data flow by building relationships and context. If data is facts, metadata is the description of those facts, and the data catalog is how those facts are stored.
The point of a data catalog is to bring data dictionaries and business glossaries together and integrate them with curated metadata. It is the unifying organization needed to centralize data throughout an organization.
The key difference between the two is that a data catalog is the organized index of assets while metadata management answers the questions of value, context, and flow.
The Critical Importance of Metadata Management
We already know that the more data-driven a company is, the more likely it will experience growth opportunities and potential revenue boosts. This is because it relies on valuable insights for decision-making.
None of those insights are possible without first introducing quality metadata management. Users need to be able to access the critical information necessary for analyzing quickly and efficiently. If no metadata management is in place, there is no opportunity for this access.
With bespoke metadata management, different departments, and teams outside of IT can leverage their own understanding of different assets. This creates a context for the role of these users and adds value to what that data represents. Such benefits include:
Productivity
The faster users can access highly relevant data based on searches, the more able they will be to streamline insights, reporting, and data tools. That includes less time spent cleaning or shifting through vast amounts of unrelated data.
For example, a team of data scientists may spend up to 80% of their valuable time fixing problems between various data sources. By integrating modern metadata management, this same team will spend more time analyzing and uncovering innovative ideas and relationships.
Customer Relationships
Today’s consumers appreciate a personalized experience that strengthens a personal relationship with a brand. With so much oversight and regulation over what information about customers is collected, it has become harder for businesses to leverage these data points.
By introducing metadata management into a business, first-party insights can be achieved with internal structures that make it far easier to unearth how to create more personalized experiences for customers – thus improving engagement.
Data Governance
It seems every year brings new regulatory controls over everything from medical information to privacy concerns. This initiates new data governance programs to ensure a business is up to date with their data and avoid any costly fees from mistakes.
None of that is possible without proper metadata management because it is what identifies and defines data assets so that everything ends up in its right place and no violations occur.
Advances in Tools & Practices
A business must invest in advanced metadata management tools to make the most of metadata management. These are designed to store information along with the critical data about data that enable the assets to be quickly searchable and understood. These tools are needed to create context, making it easier for non-IT users to discover highly relevant data for the searches they undertake.
A key aspect of these tools is that they allow the business user and data architect to collaborate. This will improve the data quality and usability. If a user requests all customer data from a specific area of the world, the data architect can use metadata to answer questions that place that data into context, like what is an “area” and what type of customer (demographics).
This is achieved through AI-related digital tools that remove the mundane and repetitive tasks of contextualizing and analyzing all the metadata details of data assets and automates the entire process. Without this automation, businesses would be overwhelmed by the tsunami of collected data.
The goal is to uncover tools that help with how metadata management works. That includes:
- Building the framework by identifying the datasets using a data catalog.
- Operate metadata management by considering changes in context to operations using data catalogs and data governance tools.
- Control the quality and value of the metadata using data privacy management, data quality, and data governance tools.
- Consume critical metadata by making it easier to locate with data catalog, governance, and marketplace solutions.
- Measure the performance of the metadata stored to assess how they add value to a business.
To achieve any of these critical phases or steps in the metadata management process, you will need to include everyone through an enterprise-wide initiative with leadership support. The importance of managing your metadata cannot be understated because of its value, especially in today’s fast-paced business environment.
Other best practices should include:
- Leverage AI/ML solutions to make metadata management active and automated across your systems.
- Create a supportive metadata foundation that ensures a window into how your data flows throughout its lifecycle.
- Avoid gaps in your metadata collection by gathering it from all available sources.
- Always include the source of any data assets so it can be tracked and logged.
- Create a stewardship program that ensures policies are implemented from the beginning to the end of your data flow.
Conclusion
The relevant context of data is critical to business success. Knowing how to find and capture data from anywhere in your organization so it can be readily used by a number of varying users is equally important. With the right metadata management in place, these issues are quickly resolved so data assets can be referenced and utilized to their full potential.
Taking the time to develop a strong metadata management program, policy, or implementation in your business can save you a lot of hassle in the long run. That is where the expert team at NextPhase can help. We have spent years constructing programs and initiatives in data management, including how best to use metadata across a business structure. Give our expert team a call today, and let us transform your metadata management capabilities.