What are the best tools and platforms for data governance and metadata management?

1 Data Governance Platforms

A data governance platform is a software solution that provides a centralized and holistic view of your data landscape, allowing you to define, implement, monitor, and improve your data governance policies and processes. Such platforms typically feature a data catalog – a searchable and browsable repository of your data assets with rich metadata, lineage, quality, and usage information – as well as a data glossary with business and technical terms. Data quality rules, metrics, and workflows are also included to measure, monitor, and improve accuracy, completeness, validity, and timeliness. Additionally, a framework for managing access, privacy, and compliance of your data is provided with roles, permissions, encryption, masking, and auditing capabilities. The platform also facilitates assigning and managing the roles and responsibilities of your data owners, custodians, and consumers while promoting collaboration and communication. Examples of data governance platforms include Collibra, Alation, Informatica Axon, and IBM Watson Knowledge Catalog.

3 Data Governance Frameworks

A data governance framework is a compilation of guidelines, best practices, and methodologies that can help you design and execute your data governance strategy and program. It helps define your vision, goals, scope, roles, processes, metrics, and outcomes. In addition, the framework includes components such as a data governance maturity model to assess the current state of capabilities and identify gaps and priorities for improvement; a roadmap to outline the steps, milestones, deliverables, and resources needed to reach objectives; a charter document to establish the purpose, scope, principles, roles, responsibilities, and authority of the program and organization; policies and standards to govern data asset creation, acquisition, storage, distribution, usage and disposal; and metrics and KPIs to monitor and evaluate performance. Examples of data governance frameworks are DAMA-DMBOK, DCAM, CMMI DMM, and ISO 8000.

5 Data Governance Best Practices

Data governance best practices are the recommended ways of doing data governance that can help you reach your goals and avoid common mistakes. These best practices may vary depending on your industry, domain, size, culture, and maturity level, but some of the general ones include aligning your data governance strategy with your business strategy, establishing a clear vision and mission for your program, engaging and empowering stakeholders across the organization, taking a pragmatic and iterative approach to implementation, leveraging frameworks, tools, and platforms to support processes and capabilities, defining metrics and KPIs to track performance, impact, and value, and promoting a data-driven culture.

6 Data Governance Resources

Data governance resources are the sources of information, knowledge, and guidance to help you understand data governance concepts, trends, challenges, solutions, and opportunities. Examples of these resources include books such as Data Governance: How to Design, Deploy and Sustain an Effective Data Governance Program by John Ladley and The Data Governance Cookbook by Nicola Askham; articles such as The Ultimate Guide to Data Governance by Panoply and What is Data Governance? by CIO; blogs like TDAN and Data Governance Pro; podcasts like Data Governance Stories by Nicola Askham and The Data Chief by Cindi Howson; webinars like Data Governance Demystified by Talend and Data Governance 101 by Alation; courses like Data Governance Foundations by LinkedIn Learning and Data Governance Master Class by eLearningCurve; events such as the Data Governance and Information Quality Conference; and communities like the Data Governance Society and the Women in Data Governance.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?