Data stewardship needs highly motivated self-starters, that will have a strong passion for data management, and in-depth experience in data governance, data management frameworks, metadata/ master data management, data quality, policy creation and data standards and controls, It is a natural evolution from Data Analyst and Database Designer, and reflects the emergence of Internet Web Sites which need to integrate data from different unrelated Data Sources, unfortunately many believe that only public companies or large, established companies with many shareholders need to be concerned about, or can benefit from, implementing corporate governance practices.
Data will be of little value if the available data cannot answer questions about actual delivery, so to begin with a conceptual framework will have to be proposed for the adoption and implementation of product stewardship.
If you are an already established enterprise you can still do an incremental approach and most likely will have a more accelerated timeline to get compliant, data stewardship poses security issues and challenges to organizations and the organizations governance framework, in particular to internal controls as well as to data management and data protection. Laying the foundation of the understanding of what data quality is, the framework for which it is defined, and how to capture data quality is critical to understanding one of the important process components of information governance, especially in terms of ensuring the right data quality processes are built and then monitored in ongoing operations.
Having a sound security plan in place to collect only what you need, keep it safe, and dispose of it securely can help you meet your legal obligations to protect sensitive data, by conducting some statistical analysis, you can see, in real time, exactly where and how your data is adding to (or in other cases, hurting) your bottom line and thus determine the business value of data, subsequently all who have a leadership role in the public service need to have a relentless focus on results and have such results underpin how you design policy, implementation and incentives.
Information technology governance (IT governance) is the collective tools, processes and methodologies that enable an organization to align business strategy and goals with IT services, infrastructure or the environment, your policy will set set out a framework of governance and accountability for the management of organization records in all formats within the wider organization information governance and security framework to enable establishment of financial management governance structures that foster prudent stewardship of resources.
Roll out the enterprise wide Data Governance framework as identified in the Data Governance strategy, with a focus on the improvement of Data Quality in systems of record and the protection of data through modifications to organization behaviour, policies and standards, culture, principles, governance, processes and related procedures.
For instance, the GDPR requires data controllers and processors to be able to demonstrate their compliance with its requirements through certain documentation, including relevant logs, policies and procedures.
Data governance is the formulation of policy to optimize, secure, and leverage information as an enterprise asset by aligning the objectives of multiple functions, As mentioned earlier, there are many, many more documents, processes, and tools within data governance, and this is a good starting point, historically, a minority of organizations have taken a proactive approach to managing data quality, however the majority have endured the pains of poor-quality data and dealt with it in a reactive manner.