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Constructing a Shared Language for Data Governance

The concept of data governance has become more important as organizations increasingly depend on the quality of their data to make critical business decisions. Data governance can be defined in a number of ways that all relate to the strategies and technologies in which an enterprise manages and controls access to its data. It is a major ingredient in the organization’s ability to meet regulatory and legal requirements as well as maintain corporate best practices.

Implementing a data governance policy is not a trivial task nor can it be simply dictated by upper management. For that matter, no individual strata of the corporate hierarchy can develop a data governance framework in isolation. In order to have a robust data governance program, a number of components are required. The organization needs to have a governing body, a defined and agreed upon set of procedures and a strategy to ensure those procedures are executed and monitored. The foundation of a data governance initiative is the establishment of a shared language with which to operate.

Steps to a Shared Data Governance Language

The basis for any constructive conversation or communication is the ability of the associated parties to understand each other. This implies that the participants engaged in the exchange are using the same language. Failure to do so obscures their capacity to reach an agreement or decide on a course of action when faced with a challenging decision. Not speaking a common language is a major impediment when attempting to build the framework for any cooperative endeavor.

Data governance needs to be a cooperative effort if it is to provide an enterprise with the benefits it seeks in managing its information in a structured manner. Defining the shared language and terms to be used in the program is a critical early step in the process of constructing a viable policy. To properly devise the data definitions that will power the data governance initiative, the associated organizational stakeholders need to be involved.

Stakeholder’s Level of Involvement

There are four basic levels of involvement that a stakeholder may occupy.  Stakeholders can identify themselves as belonging to one of the following categories regarding the development of terms and the construction of the organization’s data dictionary.

  • Responsible – Ideally, only one individual or office fills this role which exhibits the final responsibility for a data element.

  • Accountable – The office or individuals who are accountable for moving the data definition through the approval process and maintaining it going forward.

  • Consulted – These individuals or departments desire to be active participants in the development of a data definition and would like to be included when any proposed changes are considered.

  • Informed – Individuals or offices that fall into this category are not participants in developing data definitions but are required to be kept informed of final decisions and future changes to ensure they maintain an accurate understanding of the item.

Developing the Data Definitions

There are some methods which can streamline the process of developing the data definitions needed to implement an effective data governance program.

  • Leadership support – Generating the data definitions to power the program is a time-consuming process that involves the coordination of various members of the organization. Strong support from upper management is key in enabling the proper individuals to invest the necessary time in the process.

  • Identify the stakeholders – This is a critical step that can alleviate issues down the road once the policy is implemented. Involving the correct groups or people at the start of the process makes it more likely that valid definitions will result from their efforts. Management may have to reach out to involve certain parties who may not initially wish to participate, but that can bring insightful or controversial ideas to the table. It is much better to deal with conflicting views during the definition process than after the policy is in place.

  • Demonstrate the value to the business – The way in which data governance and its associated data definitions add value to your business is vital in getting buy-in from all stakeholders, in particular, upper management. Spending personnel resources should lead to tangible benefits for the enterprise.

  • Start with a draft – Beginning the process of defining the data for a particular domain can prove much easier when a draft is provided to the concerned stakeholders. This minimizes the time to ramp-up the discussion by supplying a starting point for the conversation.

  • Eliminate internal jargon – A real stumbling block to creating robust data definitions is the inclusion of terms which are specific to particular departments or areas of expertise. A DBA may use words and acronyms that have a completely different meaning to a compliance manager. These types of conflicts need to be eradicated in order to construct data definitions that are useful for all stakeholders.

Tools for Constructing a Shared Language

There are many moving parts involved when developing a data governance strategy and in constructing its foundational set of data definitions. Using a software tool specifically designed for this kind of collaborative activity will make the process run more smoothly and result in a policy that correctly reflects the goals of the organization.

ER/Studio Enterprise Team Edition is just such a tool. It will help develop the foundation to your data governance initiative with features like the ability to collaborate on glossary terms, implement naming standards, and share models and metadata across the enterprise. See how it can help you navigate the pitfalls of developing your shared language and furthering your data governance plan.

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