Our organization cut it’s teeth in the data management arena, recognizing early on the need for data governance as a key component in managing data effectively. As our depth of expertise grew we realized that there are significant advantages to looking at data within the broader context of information management. When the term information governance began to gain traction, we were drawn to it to help explain our overall information management perspective. We believed the disciplines would begin to coalesce around an overarching information management framework. See the whitepaper, Defining Information Governance, to understand how we saw the industry evolving around these two terms. The reality is that that these two movements have remained relatively separate with only occasional lip service being paid across disciplines.
In our white paper, we described the situation in terms the tale of “The Blind Men and the Elephant” where each blind person uses the term “elephant” but only sees it through his own frame of reference. The person holding the leg interprets the elephant as a pillar, the person holding the ear senses a fan, the person with the trunk senses a snake, etc. Unfortunately, when it comes to information governance and data governance, comprehensive information management (the elephant in the room) is still not seen as a whole.
Let’s examine the two terms, try to understand the context, and look at opportunities for cohesion. Definitions won’t help. The definitions for data governance and information governance read more or less the same. Data governance professionals talk about availability, usability, integrity, and access. Information governance professionals talk about creation, storage, use, archival, and deletion of information. Both sets of professionals talk about decision rights, policies, and procedures to support their initiatives.
To really understand the differences, we must look at the key business drivers and the points of emphasis. Data governance arose in conjunction with efforts to improve the quality and accessibility of data within organizations. Data warehouse and business intelligence initiatives gave us access to usable data only to discover the organization had multiple sources of the same piece of data and that the data was not consistent and often was just not correct. Data governance arose to solve these types of problems.
Information governance arose as organizations realized the overlap between the legal and regulatory requirements for data retention and security requirements for protected data. Information governance also did not limit its scope to data in IT systems, but included data in content management systems, unstructured data, email systems, and user developed applications such as Excel spreadsheets.
It is clear that all these perspectives are critical in order to effectively manage information within the organization.
At MetaGovernance, we start by defining what is meant by information and what is meant by data.
• Information – the communication or reception of knowledge or intelligence
• Data – facts and statistics collected together for reference or analysis.
These definitions lead us to view information independent of the method and medium in which it is stored or collected, whereas data contains that dependency. These terms provide the vernacular to state that the same piece of information can be stored as data in numerous locations and different formats within the organization.
We apply the term business attribute to the piece of information we are working with and data object to the piece of data as it is stored within the organization. From this, we can look at the organization’s information from a broader context that incorporates both the information and data governance perspectives:
Mapping out these relationships in detail will then form the basis for defining the information governance architecture framework of the organization. Knowing the information governance architecture will provide significant benefits to the organization.