In the ultra-competitive market of the 21st Century, any means of gaining an advantage over rivals can spell the difference between a successful venture and one that fails miserably. Making the best use of their data assets is one method that businesses can use to set themselves apart from the competition.
Data governance is a widely-used technique with which organizations can manage key data resources. It incorporates various aspects of the way enterprise data is used, stored, and maintained. This includes maintaining data security and consistency as data travels throughout an IT environment. Data governance has been adopted by many large organizations as a means to exert more control over their data assets.
As with any methodology that a corporation attempts to implement, the human resources involved in the initiative are critically important. In cases where data governance is being introduced to the organization, properly staffing the team that will oversee the program is an essential step that can impact its viability and usefulness. Choosing the wrong personnel for specific roles can make it difficult to achieve the benefits promised by data governance.
Filling Data Governance Roles
The process of staffing the data governance team requires us to have detailed knowledge concerning the strengths and weaknesses of potential team members. We can evaluate each candidate to make an informed decision regarding their qualifications to fill specific vacancies on the team. It’s kind of like putting together a professional sports team through the free-agent process, but of course, without the multi-million dollar contracts. Perhaps unfairly, mediocre relief pitchers and running backs are paid better than superior data stewards.
Just as a football or baseball team needs to obtain individuals with different skill sets to play the positions necessary to be competitive, multiple roles need to be filled in the pursuit of success in a data governance program. The individuals chosen to fill these positions should be carefully selected from among the available resources with an eye toward developing the strongest data governance team possible.
The terminology used to categorize data governance roles may differ slightly depending on which definition is consulted. We will look at the most common roles and the responsibilities of those positions.
Steering Committee
The data governance steering committee is comprised of upper management and company executives. This may include corporate Vice Presidents of areas of the business that make up a data domain such as finance, customer relations, or production. Proper leadership from the steering committee is an essential component of a successful effort. Responsibilities include:
- Setting the overall strategy and defining the outcomes of the data governance program;
- Keeping the program on point and accountable for meeting the defined outcomes and timelines;
- Promoting the work of data stewards by providing support for the time spent on the initiative and fostering cooperation between business units.
Data Owners
Data owners are associated with a specific data domain and may also be part of the steering committee. They are charged with verifying that the information pertaining to their data domain is governed across the organization. Some of their responsibilities are:
- Approving data definitions and glossaries;
- Ensuring the accuracy of their domain’s data as it is used throughout the enterprise;
- Reviewing and approving the approaches, outcomes, and initiatives associated with data management;
- Working collaboratively with other data owners to resolve discrepancies in the way data is defined or used across different domains;
- Reviewing issues identified by data stewards;
- Furnishing input to the steering committee regarding policies, regulatory requirements, and software solutions related to their data domain.
Data Stewards
Data stewards are subject matter experts who are responsible for the daily management of data. They know what the data in their domain means and how it should be used. They have a range of responsibilities including:
- Serving as subject matter experts for the data domain;
- Working with other stewards to cooperatively resolve data issues;
- Participating in the data steward council which is responsible for creating data policies;
- Reporting data decisions to stakeholders in their domain and ensuring that their interests are represented;
- Crossing business lines to ensure that the domain’s data is used appropriately.
The selection of individuals to fill these roles should not be done without considering factors like their availability and enthusiasm for the data governance program. A similarly skilled and more motivated technical resource will make a better data steward than one who is overworked and skeptical of the value of data governance. Choose team members who have demonstrated the ability to work collaboratively and convey information to stakeholders across the business.
A Tool for the Team
The foundation of any viable data governance program is made up of shared data definitions, glossaries, and dictionaries. Policies and standards need to be agreed upon that satisfy all parts of the organization. Creating these artifacts requires a collaborative effort by the members of the governance team.
IDERA’s ER/Studio Enterprise Team Edition is a valuable tool that can assist with the collaboration required by an effective data governance team. You can discover and document the existing data assets in your environment to provide a realistic starting point for your efforts. The tool lets you catalog metadata and build a solid foundation for the program. Impact analysis can be performed on proposed policies before they are implemented.
Team collaboration is enhanced with a centralized data glossary that can be built out into a hierarchy to model your organization’s data resources. You can automatically apply data naming standards for logical and physical data models across the enterprise. With a good team and ER/Studio Enterprise Team Edition, your business will be ready to use data governance productively.