ANALYST UPDATE: Field Reports for ‘Top 10’ Data Governance Solutions
Chief Research Officer, The MDM Institute
Data Governance is critical to achieving sustainable and effective MDM. Failure to execute Data Governance concurrently with an MDM program greatly decreases the probability of success and economic sustainability of MDM programs. Clearly, Data Governance is both synergistic and co-dependent with MDM. When deploying MDM, a proper Data Governance (DG) discipline should consider the business drivers, project scope, roles and people filling each role, policies and procedures, data quality, inheritability, social norms, and the business operating model. Moreover, Data Governance is more than a single product or process, rather, it is an ecosystem of products, processes, people, and information. At present, Data Governance for MDM is moving beyond simple stewardship to convergence of task management, workflow, policy management and enforcement.
Understanding the scope, diversity and limitations of current Data Governance solution offerings is tremendously challenging – even more so, given the fast pace of M&A & complexities of integrating such diverse software portfolios. Nonetheless, business and IT leadership chartered with defining and executing MDM programs need help to understand and navigate through the number and variety of DG options.
Through 2017, most enterprises will struggle with enterprise DG while they initially focus on customer, vendor, or product; integrated enterprise-strength DG that includes E2E data lifecycle will remain elusive as most organizations turn to lightweight glossaries with modest Data Steward workflows to support devolved autonomy and multi-disciplinary, bi-modal teams. During 2017-18, the majority of MDM software and service providers will focus on productizing such lightweight DG frameworks while mega MDM software providers will struggle to link governance process with process and data hub technologies. By 2019, mega vendor DG solutions will finally move from “passive-aggressive" mode to “proactive" Data Governance mode.
This session will a review of the current solutions in market as well provide a “top10” list of evaluation criteria for such solutions.
• Understanding the “top 10” evaluation criteria for DG solutions — e.g., E2E lifecycle management, Big Data & ECM support, DQ/ETL integration capabilities, etc.
• Assessing the vendor landscape— e.g., passive, active, integrated, pro-active, & passive aggressive, etc.
• Determining an enterprise-specific road map to evolve from a siloed, motley collection of DQ tools, processes & point products to a non-obtrusive enterprise DG program (supporting multiple domains, cross-disciplinary teams & federated data management groups)