A New Governance Paradigm Emerges
Metadata mandates governance, hence Metadata Management. More importantly, Metadata Management is inextricably entwined with Data Governance. The Data Governance program must incorporate and oversee all Metadata Management aspects and capabilities as part of its purview to manage data and its inherent metadata.
There are growing classes of problems demanding rapid insight. Companies need to take raw data and extract insights directly from it. Many more demand to exploit on-the-fly analysis and adjustment to optimize investments and decisions. These demands open new avenues for integration, inference, and insights in support of Advanced Analytics. They challenge proofs of veracity, provenance, and value scoring. They demand that data be certifiably Fit for Purpose, and Fit for Use. Metadata provides keys (lineage, traceability, ontology) to reach the goal of obtaining actionable insights from Advanced Analytics. Metadata Management proffers exchange processes where data complexity is overcome and Advanced Analytics aligns with organizational elements to ensure information and analytics quality and agility through automation.
So, it behooves us to think of Metadata Management in terms of Data Governance. Certainly a holistic approach to Metadata Management is necessary – one that incorporates a triumvirate of people, processes, and enabling technologies towards a single goal: a goal that allows Metadata Management to become a pillar of Information Management and Data Governance.
Metadata Management as Part of a Holistic Perspective
Metadata provides the connective tissue in the information architecture and facilitates the integration and leverage of data assets across departments, functions, and applications. Metadata Management comprises the processes, tools, solutions, and capabilities necessary to create, control, govern, integrate, access, and analyze Metadata. The value of Metadata in data management activities is not an artifact of technology; it is an artifact of the proper business management of data.
Incremental Metadata capability development allows the development of a concise understanding of the value of data as it develops complexity and nuance. Investment in Metadata is an investment in sophisticated technologies, infrastructure, and process management. The complexities of Metadata Management and Data Governance require close coordination across many disciplines and technologies, so much so that the role of Metadata has been transformed from being an afterthought into a fundamental approach to manage complex data requirements and analytics.
An all-encompassing approach is mandated to turn data into usable assets from which to improve decision-making and augment competitive advantages. Metadata Management raises confidence in data amongst users, as a way to deliver a ‘single version of truth.’ Always start from a strong, holistic Enterprise Information Management base…
The core philosophy around Metadata Management focuses on the alignment of data, connecting the end points. Using bi-directional meta-repositories provides an active means to align business drivers, governance policies and procedures, orchestration, event management, organizational structures, and enterprise data management. The traditional meta-repositories, originally developed to trace data lineage begetting Metadata Management, are being augmented with emerging tactics for gaining control over data management using much matured technologies. The bi-directional Metadata repository architecture provides the requisite workspace within which to organize enterprise integrated and advanced analytics into an intuitive, useful, and inviting discipline framework that combines policies, standards, and data management, for the administration and delivery of superb business intelligence.
Metadata Management tools have been in use for nearly three decades, but only recently have they been incorporated into the technology suites of many vendors. These catalog scrappers and organizers are now finding their way into maturing governance organizations as a means of identifying and verifying the proper alignment of data with traditional constructs such as Master Data, Data Governance, Data Quality, Metrics, and Business Process Management for the concise and appropriate management of data as a corporate asset. Metadata is the glue of an Enterprise Information Management program that facilitates the integration and leveraging of data across the different business groups, functions, processes, and applications
Governance Promotes Metadata Management
Metadata Management provides some very valuable tools held in a sharable, common Meta-repository:
- A common lexicon of business terminologies including requisite taxonomies and classification schemes to support competing perspectives, semantics, and search
- A comprehensive catalog of business rules and metrics
- A unified version of Data Models, including those for Big Data
- The unification of disparate Data sources of the same subject
- The standardization of proprietary algorithms and discrete derivations, lineage and traceability across data domains and elements to ensure proper provenance
- The proper integration of data elements across the corporate ecosystem and landscapes including requisite privacy constructs
- Certifiable and sanctioned data quality
- Augmentation of regulatory compliance, audit, impact analysis, and investigation
The Meta-repository provides a central, enterprise-wide, scalable, extensible, and secure storehouse. Metadata Management ensures conformance of business processes and outcomes (reporting, analytics), while fostering collaboration and knowledge sharing toward the goal of a ‘Single Version of the Truth,’ all invaluable tools for Data Governors and Stewards.
It is hard to envision Information Technology changing from its current state to where it needs to be to handle increased information management complexities, while re-aligning with the business, as each day that passes Information Technology becomes more of an outsider to the business-driven, service-based delivery of information from which to gain actionable insights… The challenge is to develop real solutions that enable the re-alignment of data management to once again become compatible with and instrumental to business goals and initiatives.
The New Data Governance Paradigm requires a multi-dimensional, multi-directional Informational Repository, which is “IT Strategic” in enhancing the abilities to provide Information as a Service [IaaS]. Traditional data management approaches impede capacities to incorporate unstructured content [Big Data] into our data management frameworks, and these paradigms thereby thwart the logical transformation into a service-based architectural model better suited to handle the complexities of our data nervous system. Today’s approach to Data Management is mostly transactional-based, application-driven, and difficult to associate with business drivers, KPIs, and events. This conundrum impedes unstructured data with its real-time delivery (e.g., driven by continual action) from making it easy to extract and visualize the nuances, insights, and relationships among disparate and disconnected bits’ content and knowledge. In addition, it impedes proper adaptations of unstructured content and business activities that are in continual flux and changing rapidly.
Augmenting the Vision with Metadata
So, it is incumbent that Data Governors and Stewards incorporate Metadata Management utilizing the following precepts.
- Simplified, Optimized, Integrated
- Standardize processes for managing data across and within markets, business units, and geographies
- Compliance and Privacy
- Master Data to augment risk management, customer care, and compliance, as well as data protections
- Hold and manage data in single [logical] instance; singly defined and managed
- Global Customer and Product Views (Hierarchies, Classification Schemes)
- Provide a clear picture of profitability in local, regional, and global markets; as well as by business units and product
- Consistent Standards
- Common set of standards and definitions
- Address dependencies among data elements and requirements
- Reduce Data and processing errors
- Reduce cost of operational support
- Improve operational capabilities
- Improve data quality
- Improve decision making
- Enhance reporting and analytics accuracy
- Provide comparability and auditability
- Capture tribal knowledge
- Improve availability of data (right time, right place)
- Enhance regulatory compliance
As Metadata Management maturity grows, so too will one’s abilities to simplify, consolidate, optimize, and transform into an organization that easily and quickly garners meaningful, actionable insights from Advanced Analytics.