In the world of increasing volumes and complexity around data, it is more critical than ever for organizations to be able to apply business context, to then understand and quantify the value of that data. Shared data can be a huge asset to an organization, but also introduces additional risk when organizations have differing opinions rather than congruent answers to fundamental questions being asked by business users, such as what does the data mean and what level of quality assurance has been applied to it. When there are disagreements on fundamental concepts about data, it’s easy to surmise there is a systemic problem rooted in the absence of data governance.
For businesses to operate there are a series of business processes that are supported by numerous technical underpinnings. While both business and technical perspectives are important, for an organization to operate efficiently they must find a way to bridge the divide between both worlds, and in the process liberate their data to make better decisions.
Let’s break down the business side and the technical side.
Breaking Down the Perspectives
On the IT side, you have employees who understand the technical architecture that underpins an organization’s data. They can access the data, model how it should be stored, profile the data and trace how the data moves from point A to point B.
Then there are the business experts. These resources may not understand the technical complexities of an organization’s data, but clearly understand how data is utilized to make business decisions, comply with regulatory requirements, and serve the specific needs of clients. Conversations that involve the technological aspects of data are fuzzy for them to comprehend, resulting in difficulties getting in synch when collaborating with their technical counterparts to efficiently resolve problems and deliver projects. Failing to resolve these challenges introduces risk; business users may accidentally choose incorrect data, low quality data, or they may haphazardly make choices based on assumptions rather than having a direct path to the data owner to ask questions and remove ambiguities.
To continue maintaining a competitive edge, organizations need to look at ways to bridge this business and technical divide, one of which is the introduction of a business-oriented data governance solution. A solution that builds collaboration among data owners, data consumers, and data suppliers by synthesizing the critical details about the data in a way that it provides a multi-dimensional perspective for all resources that clearly defines roles and responsibilities, captures knowledge and ensures full understanding and frequent updates to interested parties within the organization in a model of true data governance.
Bridging the Gap
Data governance can seem a bit overwhelming to get off the ground and although it is predominantly a people driven framework, it is important to bridge the business and technical gap early on, start the collaboration process and document the most critical data assets, upon which organizations need a proper data governance platform.
When looking for a data governance platform organizations should look for one that delivers transparency into all aspects of an organization’s data assets. This includes the data availability, ownership/stewardship, lineage and impacts both to its associated definitions, synonyms and other business attributes. Full visibility allows business users to gain valuable insights into not only the details of an organization’s data assets, but into its shared value and inherent risks with its use across business.
In addition, the right solution should provide an all-inclusive view of an organization’s data landscape to meet all regulatory and compliance needs, as well as the agility to meet the shifting tides of business policies and realignment. Keeping the business users in mind, the solution should be easily navigable and not overly technical, and should bring clarity to the process of how and when data is used throughout the organization.
To learn more about data governance, download the data sheet below.
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