Data stewardship: Essential to data governance strategies
Organizations are establishing data governance programs to address evolving privacy requirements and increase the utility of business data. The lack of a data steward can undermine any data governance effort.
Approaches to data governance vary depending on the organization. Some rely on tools to keep data in line. Others centralize data governance under roles like CIO. Others ask data product managers to drive the value-creation aspects of data governance.
Data governance incorporates controls to help understand metadata, data quality and proper use, said Matt McGivern, a managing director at Protiviti, a management consulting firm.
“It has become popular to call data an asset, but without proper data governance, this is impossible,” he said.
Data governance is a strategic analysis technique, while data stewardship is a more tactical role. Data steward could be a specific job title or a responsibility within the job of a business manager. Every organization should lay out its data governance goals and specific measures to translate them into daily practices.
To be an asset, data needs to be understood by an organization. The organization must know where it’s stored, how it’s utilized, who is utilizing it and when it is destroyed or disposed of. Data governance supports each of these areas, and data stewards drive understanding of appropriate data use. They also establish the standard controls to data and ensure that it is used in the appropriate context by confirming contractual restrictions with legal guidance.
Depending on the situation, the differences between data governance and data stewards determine if one is needed. Organizations also should consider what may happen if they don’t have a steward in place.
Every company has its own distinctions between data stewardship and data governance. Most experts agree data governance is a broader concept and data stewardship is a specific role to put it into practice. There are different ways of framing the distinctions between them. Broader versus supporting controls. Data governance is a comprehensive set of controls — strategies supported by policies, procedures and technologies — to help control data, McGivern said. Data stewardship, by design, is a specific supporting set of controls to help data governance act. “Data stewards are often where ‘the rubber meets the road’ for data governance controls,” McGivern said. “[They are] helping to provide the necessary context to the data and other knowledge about required controls, proper usage and the current state of quality.” Framework versus role. Data governance establishes a framework for how an enterprise provisions and stores data, while data stewardship is a role within the organization that advocates for effective uses of that data to create value, said Ed Murphy, senior vice president of data science at 1010data. In this regard, governance focuses on the essential infrastructure for data-driven enterprises: In contrast, stewardship focuses on wringing value from data: Policies versus tasks. Data governance is the ownership and management of the policies, processes and procedures for data, said Claire Thompson, chief data and analytics officer at Legal & General Group, a financial services company. In contrast, data stewardship is undertaking tasks needed to ensure adherence to and compliance with the data policies and frameworks. The data steward interprets and implements required processes on a day-to-day basis. Outcomes versus inputs. Data governance is the outcome while data stewardship is the input required to achieve it, said Graeme Thompson, CIO at Informatica. Data governance includes what someone is trying to achieve and the mindset necessary to achieve it. Data stewardship involves defining ownership and responsibility for different pieces of data and for the processes that generate the data. While they’re different, they are not separate.
