Jump Start your Data Governance Journey with a Data Catalog

January 10, 2022

Data Governance (DG) is a continuous, ongoing way of working with data to ensure it is trusted, understood, and fit for business users’ purposes. By formalizing data management practices, it ensures data and digital assets are treated like valuable assets for the insights that they can provide with careful analysis.

DG Is a Journey with Many Curves and Potential Pitfalls along the way

Achieving the target state where a company’s data estate is under standardized management by a community of Data Stewards and Owners is easier said than done. There are several reasons for this, with perhaps the main one being a hands-off approach to DG. This situation is often encountered in industries such as financial services and pharmaceuticals, where companies may have defined DG frameworks, at the behest of regulators who have requested a regulatory data that produces in a systematic, controlled manner.

In other cases, companies may have mandated the stand up of DG capabilities to protect sensitive data and control personally identifiable information. Such companies may typically have defined DG-related roles, responsibilities, processes, and policies in place, and are often surprised when few DG activities get done. If we look deeper at these DG deployments, we often find that DG frameworks focuses on compliance in place, however the DG function does not enable business units in working with their data.

This is a typical pitfall of taking a holistic, systematic approach to DG. Simply put, a company can get stalled along the way or stuck in the build out of DG foundations. We often encounter this when a company’s initial DG deployment has lacked a robust underlying use case or priority business problem. This scenario reflects the change management challenge that is often inherent in deploying a new function such as DG, where new ways of working are mandated for compliance reasons, and practitioners do not see the business enablement value of DG in dealing with their day-to-day business challenges. To illustrate, the DG journey involves:

  • Designing a DG Target Operating Model
  • Designing an Organization Structure
  • Creating an Accountability system for data
  • Appointing Data Owners & Data Stewards for all key company data entities
  • Building a suite of DG processes that formalize the full data management lifecycle and articulate who does what
  • Deploying enterprise-grade tools and technology platforms to enable data management functions
  • Building a suite of policy artifacts including standards, templates, and how-to guidelines to standardize how work should be done
  • Executing a change management strategy, delivering targeted communications, and training key stakeholder roles in the new way of working.

Ultimately, putting all these elements in place is required for DG to cover the full range of a company’s strategic objectives, operational/analytical needs, and compliance requirements. However, it may be a multi-year effort, and tactical needs may go unanswered.

Hence, companies may seek to reinvigorate or advance their DG journey efforts through tactical projects to accelerate progress.

A New Approach: Jump Starting the DG Roadmap

Companies are taking note of recent trends in the data management space. Many companies have invested into new architectural approaches, including migration to the cloud. In doing so, they have gained direct access to sophisticated new tools and technologies, including those that involve AI/ML for advanced analytics. In trying to extract value from these high-potential, high-value toolsets, many companies are realizing that they do not understand their data as well as they thought they did, or sufficiently to extract value from their investments.

Whether a company is on their DG journey or needs to understand its data better for tactical reasons can benefit from this trend. The trend focuses on metadata management to jump start their DG journey. The promise of working with metadata to build out a data catalog is compelling because companies can quickly reap the rewards of increased data transparency and literacy, such as:

  • Helping business users learn what data is available via a searchable, centralized view of their data estate
  • Enabling faster access to data for business users
  • Helping technical, compliance, and business users understand what systems, applications, and databases contribute what data elements to their projects
  • Enabling faster systems development
  • Identification of sensitive and private (PII) information that needs safeguarding

Regardless of where a company may find itself on its DG journey, it can do no wrong by an immediate and tactical focus on metadata. These efforts will not be wasted or require re-work; beyond delivering immediate benefits, metadata-related work also accelerates the DG journey because it lays a foundation for a wider range of DG-related topics, including:

  • Data quality: is my data complete, consistent, accurate, updated, and reliable?
  • Which version of data is the right one to use? What is the authoritative source of “truth”?
  • Who manages the data?

The immediate benefits of creating a company data catalog with metadata-related activities are numerous and include:

  • Data Centralization – an enterprise data catalog enables centralization and searchability of a company’s entire data estate. This is not possible with siloed data dictionaries.
  • Data Literacy Enablement – a populated data catalog offers
  • A Business Glossary, enabling business users to speak the same language by using unique, formalized business definitions for data elements
  • Taxonomies/ontologies formalize the relationships between data elements to enable their usage in reporting and systems development
  • Data Classification is the key means of imposing controls on data, including identifying private and sensitive data, recording how the data may be used and by whom
  • Data Lineage maps to show all the transformations the data element may have undergone prior to consumption for confidence in the data’s integrity
  • Application of Governance Controls
  • As the centralizing point for all data elements and requirements for their handling, the data catalog becomes the book of record and enabler for controls around
  • Access, provisioning, security, and privacy
  • Retention, archiving, destruction
  • Data Ownership and Stewardship
  • Business rules and policies applied to data
  • Where the data is used: business processes and workflows
  • History
  • Integrations

Beyond immediate benefits: How Metadata Management and a Data Catalog Accelerate DG and Democratize Data

The list of immediate benefits and reasons to embark on building a data catalog in a tactical manner is extensive and will provide ROI in a shorter time to market in reporting and systems development/integration.

However, these efforts also accelerate the DG journey because metadata on data assets is required to begin measuring, remediating/cleansing, and monitoring their data quality. Moreover, both metadata and data quality management are required to build a single, authoritative view of the company’s main data entities, its master data domains (such as customer, product, transaction, and so on).

Finally, a Data Catalog is a foundational enabler of the promise of data democratization and self-service access to data, as the metadata it contains can be used to instantiate a data marketplace. In this holy grail state where IT gets out of the way to let data consumers self-serve, they can create, manage, publish, browse, request, have their access requests approved, and receive data for their usage according to their permissions. None of this is possible without metadata.

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