Tag Archives: Data Stewardship
No organization begins to implement a data governance program from an entirely blank slate; every organization likely has some capabilities to leverage. Determining an organization’s current level of data governance maturity is a useful and necessary first step in developing a customized plan that is both relevant and executable. So how do you assess your maturity? Well throw a rock in any direction and you’re likely to hit a software vendor, consulting company or industry analyst that offers a maturity model and assessment tool to support your data management and data governance efforts. Actually don’t throw rocks, you could hurt somebody. (Yes, we offer one too – more on that below). (more…)
For the final facet of our data governance framework, I’ve intentionally saved Program Management for last. I felt to fully demonstrate why your organization must invest in skilled program managers I should first introduce all the simultaneous moving parts that make up a comprehensive data governance strategy. (For links to my posts deep diving into each facet, see my blog page). (more…)
The next facet of our Data Governance Framework recognizes the key dependency any data governance-related effort has on change management. No matter how compelling the vision and business case, making data a trusted corporate asset on par with your financial and people assets is a major culture shift for most organizations.
As mentioned in my post describing the major business processes that comprise a data governance function, the Measure and Monitor processes i) capture and measure the effectiveness and value generated from data governance and stewardship efforts, ii) monitors compliance and exceptions to defined policies and rules, and iii) enables transparency and auditability into data assets and their life cycle. (more…)
As mentioned in my post describing the major business processes that comprise a data governance function, the Apply processes aim to operationalize and ensure compliance with all the data governance policies, business rules, stewardship processes, workflows, and cross-functional roles and responsibilities captured through the Discover and Define process stages. (more…)
As mentioned in my post describing the major business processes that comprise a data governance function, the Define processes documents data definitions and business context associated with business terminology, taxonomies, relationships, as well as the policies, rules, standards, processes, and measurement strategy that must be defined to operationalize data governance efforts. This process runs parallel and is iterative to the Discover process stage as Discovery drives Definition, and Definition drives more targeted focus for Discovery. (more…)
As mentioned in my post describing the major business processes that comprise a data governance function, the Discover processes capture the current state of the organization’s data lifecycle, dependent business processes, supporting organizational and technical capabilities, as well as the state of the data itself. Insights derived from these steps are leveraged to define the data governance strategy, priorities, business case, policies, standards, and the ultimate future state vision. This process runs parallel and is iterative to the Define process stage as Discovery drives Definition, and Definition drives more targeted focus for Discovery. (more…)
To truly manage data as a valued enterprise asset, data governance must be managed as a business function like finance or human resources. A finance function is comprised of multiple core business processes such as accounts payable, accounts receivable, payroll and financial planning. So to manage data governance as a function, what are the core business processes that comprise data governance? (more…)
While the People facet of our Data Governance Framework focuses on skills and responsibilities, the Organizational Alignment facet focuses on the working relationships between dependent roles. Many organizations begin their data governance journey putting decision-making responsibility, resourcing and stewardship within existing organizational structures – and early business value and momentum can certainly be delivered this way. But to truly scale data governance as a holistic, cross-enterprise effort benefiting multiple parts of the business, the current state of your organizational structure will have to adapt.
The next facet of our data governance framework focuses on the three intentionally simplified dependent processes that constitute the data lifecycle. When educating your business sponsors and evangelists on the data lifecycle, I like to categorize it into these three broad areas: upstream processes, stewardship processes, and downstream processes. If you’re an enterprise or data architect, you’ll likely have a much more granular set of steps in a data lifecycle, which is perfectly fine. But when engaging with your business partners, keep it simple and they may actually listen! (more…)