LIVE ONLINE TRAINING: STARTING YOUR DATA GOVERNANCE PROGRAM
Learn how to plan, design, and build a successful Data Governance program from the ground up.
Metadata powers effective action on information by providing context. To trust the data context, businesses need effective Metadata Management. As Michael Chui says, “you have to understand the data [in order to win in the age of analytics].” Grasping the who, what, when and how of data means knowing Metadata and Metadata Management.
With the Internet of Things (IOT), a growing mass of Big Data, and changing regulations, CIOs must look at managing their data more effectively through Metadata. Gartner estimates the market for Metadata Management solutions around $170 million. Expect this value to double in 2017. In 2020, 50% of “information governance initiatives will base their policies on the proper management of Metadata alone.” Add to this the reality that Metadata Management needs to address a range of complex problems.
In the past, a form of Metadata Management meant knowing how to use the card catalog to find a book or magazine in a library. Currently, Metadata Management means also knowing how to use computer applications to identify money laundering, securing business information, complying with auditors and targeting marketing efforts. Comprehending good Metadata and Metadata Management becomes essential.
What is Metadata?
Metadata is “information describing various facets of an information asset, improving its usability through its life cycle. It provides understanding that unlocks the value of data.” This understanding comes from setting the data in context, allowing it to be reused and retrieved for multiple business uses and times.
Metadata exists in a variety of structures table headers, legacy applications, configuration files, in IOT, in the Cloud, media, and Data Models. According to Donna Burbank, the Managing Director of Global Data Strategy, in a recent DATAVERSITY® webinar, point to the Data Model from a relational database structure and find Technical Metadata (structure, format, and rules for storing data), and the Business Metadata (business definitions, rules, contexts).
Examples of technical Metadata include column structure of a database table, keys and validation rules. Examples of Business Metadata include security levels, privacy levels, and acronym levels. Metadata differs from data in that it describes data not specific instances or records. Both IT and business need quality metadata to understand the data on hand. Without useful Metadata, the organization is at risk for making the wrong decisions based on the wrong data.
Good Metadata Management
Creating or pointing more Metadata does not make the information more useful. Good Metadata Management does that. Properly managed Metadata, whether from an old- fashioned card catalog or a computer application, simplifies resource descriptions and provides vocabularies to link contexts.
Good Metadata Management makes for quality Metadata for enterprise content:
“Not evidently immediately, but cumulatively. Over time, consistently applied Metadata will yield greater and greater returns, while lack of such Metadata will progressively compound retrieval issues and further stress organizational efficacy.”
Key components of Metadata Management include Metadata Strategy, Metadata Capture and Storage, Metadata Integration & Publication and Metadata Management & Governance:
- Metadata Strategy
According to the research report Emerging Trends in Metadata Management only 13.59% of those surveyed have a clearly defined Metadata Strategy and for most it is a piece of another strategy. A Metadata Strategy “ensures actionable, consistent and relevant control of an enterprise’s data ecosystem.” A good Metadata Strategy needs to include why should the business track Metadata, in addition to gaining feedback from business stakeholders and prioritizing key data components. Key considerations in implementing a Metadata strategy also include business drivers and motivation, Metadata Management maturity, and Metadata sources and technologies.
- Metadata Capture and Storage
Good Metadata Management requires identification of all external and external Metadata sources and what the business is trying to capture. Using a combination of Metadata solutions, including Data Modeling, Metadata Repositories, and Data Governance tools can help business people evaluate and specify Metadata Captured. Metadata from IoT promises to be helpful. Two research groups, the Thing to Thing Research Group (T2TRG) and the Web of Things (WoT-IG) are exploring Hypermedia. According to Michael Koster, “Hypermedia is the descriptive Metadata about how to exchange state information between applications and resources.” This standard will make diverse Metadata from IoT more interoperable.
- Metadata Integration and Publication
Metadata Integration and Publication describes how to communicate Metadata Strategies and Management to stakeholders and to whom. Prioritizing field standards, using an established external Metadata standard, and emphasizing cohesion among diverse types of Metadata, makes Metadata Integration and Publication easier. The Jet Propulsion Laboratory (JPL) accomplished this using the Dublin Core Specifications. Two templates, also used, include the Business Glossary and Data Lineage.
- Business Glossary: Firms use a Business Glossary as a common way to publish business terms and their definitions The Metadata managed in a Business Glossary becomes a backbone for a common business vocabulary and accountability for its terms and definitions. This resulting Metadata layer, enhances shared communication, exchange, and understanding of the Business Glossary. Consequently, said Ian Rowlands, ASG’s Vice President of Product Marketing, the Business Glossary enables collaboration around business data, resulting in a focused entry point.
- Data Lineage: Publishing Data Lineage describes information on the what, when, where, why, and how of business data, enhancing regulatory compliance and problem solving. Data Lineage especially helps in showing the interrelationship of diverse types of Metadata, clarifying customer’s relationships to businesses and information security. “This Data Lineage can be tracked in most Data Modeling tools,” or businesses may consider using a Metadata Management tool to stich Metadata together providing “understanding and validation” of data usage and risks that need to be mitigated. Using web-based reporting makes it easy for users to explore Metadata, by drilling-down to each data source and investigate further lineage.
Metadata Management and Governance
Enterprises need holistic Data Governance to make informed business decisions, including Metadata Governance: Metadata Governance involves looking at Metadata roles responsibilities, standards, lifecycles, and statistics, in addition to how operational activities and related Data Management projects integrate Metadata.
Although firms acknowledge Metadata’s value, about 50% of organizations 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 provides a view into the flow of data, the ability to perform an impact analysis, and finally an audit trail for compliance, ensuring trust in a firm’s data. Good Metadata Management becomes central to holistic Data Governance.
“Just Enough” Metadata Management
Give “just enough” consideration to Metadata Management. Spending too little resources on Metadata Management “will progressively compound retrieval issues and further stress organizational efficacy” said Burbank. Throw too much at Metadata Management and product fundamentals and business stakeholders suffer. Consider cost and relevancy.
- Cost: Too much or too little Metadata management results in increasing costs. Beware of using the greatest new shiniest data processing paradigm, said Rowlands. Businesses can spend hours and dollars inventorying their data across various computer files or in the latest Cloud environments, to the expense of product development and meeting customer needs. Don’t focus on compiling data about data to achieve a particular function at the expense of directing Metadata creation and usage. The latter will give the best bang for the buck.
- Irrelevant: Nothing can be more disheartening than to create a Business Glossary or another type of Metadata publication and having it become obsolete. Internal and external users then ignore the firm’s Metadata relegating it to the dusty corners of a book shelf or the dark recesses of a distant computer’s memory. Without commitment to knowing data’s inventory, lifecycle, characteristics, relationships and roles within a business, and the resulting Metadata Management becomes an academic exercise with little use, commented Rowlands.
Executives and managers must manage Metadata effectively. Financial and Health market places already require this. With the expansion of the data, especially from IoT, other markets will likely join in. Good Metadata Management becomes critical to trusty, secure, and useful business data. Auditors, governments, customers and other stakeholders demand this.
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