7 Key Aspects of Metadata Management

January 26, 2022

Many organizations do not utilize the entirety of the data at their disposal for strategic and executive decision making. Identifying, classifying, and analyzing data historically has relied on manual processes and therefore, in the current age consumes a lot of resources, with respect to time and monitory value. Defining metadata for the data owned by the organization is the first step in unleashing the organizational data’s maximum potential.

What is Metadata?

Metadata is information that describes various facets of an information asset to improve its usability throughout its life cycle. It is Metadata that transforms information into an asset. The more valuable the asset, the more critical it is to manage the Metadata around it as it unlocks the value of data.

Getting Started with Metadata Management

A well-structured Metadata, whether from an old-fashioned card catalog or a computer application, simplifies resource descriptions and makes enterprise data discoverable through one centralized repository. Key benefits are:

  • Enhanced data discovery
  • Faster data analysis & delivery timelines
  • Enhanced insights through lineage
  • Improved productivity
  • Quicker path to regulatory compliance through catalog and classification

The first step to get started with the Metadata management journey is to understand the data assets within the organization, their value and criticality. Once the key assets are identified they become the candidates for the Metadata management program starting with pilot and onboarding them in an incremental fashion.

Key Aspects of Metadata Management

1. Creation of Metadata Strategy and Policies

You’re not going to know how to classify data if you aren’t able to understand how it fits into the larger picture. A Metadata policy will help a business by explaining the context of their data.

This is a strategy that can be tailored to your operations to best suit your needs and inform other strategies to keep your data safe. Use the following questions to put together a Metadata policy:

  • Which types of Metadata and data are essential to daily business processes?
  • Which issues can Metadata be used to address?
  • What methods will be used to update the Metadata?
  • Are there regulatory stipulations that need to be followed?
  • Which types of Metadata are needed for specific user groups?

2. Identify types of Metadata to be captured

  • Technical Metadata – from applications or systems, such as tables, attributes/columns, integrity constraints, data type for each attribute, relationships between objects, lineage etc.
  • Business Metadata – from systems and applications which is descriptions of the data element from the perspective of business use, including information such as a business glossary with terms and definitions, synonyms, acronyms, business rules, and responsibilities.
  • Operational Metadata – from systems and applications that “describes details of the processing and accessing of data, e.g., execution logs, data sharing rules, error logs, audit results, various version maintenance plans, archive and retention rules, among many others.

3. Identify tool for Metadata Management

Managing Metadata for an enterprise could be challenging and overwhelming. It is best to look for an automated way to manage and maintain Metadata. This often is facilitated by a tool. The basic requirements for a tool to be successful are as below:

  • Ability to establish and deploy a centralized Metadata repository either on-prem or cloud.
  • Ability to define business terms, valid definitions, valid values, data domains through a hierarchy of glossaries.
  • Ability to read and extract Metadata from the most popular database management systems (Oracle, SQLServer, NoSQL) from data modeling tools, business intelligence tools, and ETL.
  • Flexibility to automate Metadata collection
  • Ability to facilitate curation and management of data catalogue, including assignment of accountabilities and responsibilities for data domains/systems (ownership & stewardship)
  • User friendly and intuitive interface for business use

4. Metadata Capture and Storage, build a Metadata foundation

To create a common Metadata foundation to deliver insight and intelligence across all your data management processes utilize a tool-based approach. The tool reads and scan systems, applications, and databases to collect and store Metadata. This collection process ideally should be automatically capturing the ongoing changes to the Metadata and log history.

The storage of Metadata is very important, compromised Metadata has the potential to expose information regarding the operations of your business. Carefully analyze and ascertain the storage needs based on the risk assessment through your data loss and prevention program. Cloud storage comes wide range of capabilities and advantages. However, security and regulatory needs may dictate an on-prem storage.

5. Integrate & Share Metadata with organizational ecosystem

The journey of harnessing the full value of your data is kick started by Metadata driven intelligence. The next step for the Metadata journey, organize and segregate the collected Metadata. Create glossary, standards, and definitions. Integrate this information with the technology landscape, create lineage of the data flow and transformation.

Few things that bring all these together are.

  • Leveraging an AI-powered enterprise data catalog and glossary and enabling consumption of the information to all employees.
  • Identification of the relationships across distributed data silos in an automated fashion (AI/ML) and connecting them to reduce manual interventions
  • Automated analysis of the data pipelines across the systems to identify lineage and transformation enabling the IT organization to build more efficient process and minimize rework.
  • Automated lineage enables automated data mapping significantly reduces effort and helps users across the organization to discover, understand and trust relevant data.
  • Automated segregation and categorization of data enables the organization a complete view of the data elements allowing them to efficiently manage security, access control and compliance.

6. Metadata Management & Governance

Enterprises need Data Governance to enable making informed business decisions, including Metadata Governance. Metadata Governance involves managing Metadata to effectively apply the intelligence to standards, lifecycles, and statistics, security, and access control in addition to how operational activities and related Data Management projects.

Although organizations acknowledge Metadata’s value, most have no Metadata standards in place, a crucial piece of Metadata Governance. Formal roles, such as an Executive Sponsor or champion assist stakeholders in understanding the importance of standards and Metadata Management. Finding ways to track and view Metadata quality through completeness, accuracy, currency/timeline, consistency, accountability, integrity, privacy, and usability can show strengths and improvements needed in Metadata management. Effectively governed Metadata becomes central to enterprise Data Governance.

7. Best Practices

To summarize Metadata management and its importance, here are several best practices to follow:

  • Organize a Data Governance Team
  • Put Together a Metadata Policy
  • Build a unified Metadata foundation, categorize
  • Apply AI/ML to activate your Metadata
  • Enable AI/ML model for metadata governance
  • Develop a Metadata stewardship program
  • Democratize usage of Metadata across organization

Organizations are required to manage Metadata effectively for regulatory requirements. However, good Metadata Management becomes critical to trustworthy, secure, and useful business data. Auditors, governments, customers, and other stakeholders demand this.

However, a key question is often overlooked. How much Metadata governance does your organization needs? Consider “just enough” attention to Metadata Management. Spending “too little” resources on Metadata Management eventually build up issues with organizational efficacy. Throw “too much” at Metadata Management and product fundamentals and business stakeholders suffer. There are two aspects an organization must look at “Cost” and “Relevancy”.

Ask the question: Is my program relevant? Does it resonate with my business problem? Putting efforts to create a Business Glossary or some other type of Metadata publication and having it become obsolete is not the desirable outcome.

Ask the question: What is the cost of my program? We can spend a hours and dollars putting together a Metadata program investing in latest technologies trying to compile inventory of all data. This will only increase cost if we do this without focusing on achieving a relevant function and ensure usage.

Why Trust Adastra

As a leading Canadian Information Management server provider, Adastra Corporation brings to bear over 20+ years of experience in designing and deploying Information Governance strategies and frameworks. Gartner has recognized Adastra’s data governance capabilities, as we’ve proven our abilities to establish a vision for our client’s data that supports their business strategy and objectives. We offer an extensive history of utilized our tested and proven methodologies to deploy successful MDM solutions.

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