Establishing a Winning Data Governance Model

Evolve Your Data Governance Strategy by Embracing the Latest Tools, Technologies and Tactics

Chris ReedSeptember 12, 2018

Data Sheet

It’s more critical than ever to ensure organizations have a firm understanding of their data from a business standpoint and can quantify its quality value if they want to realize optimal returns on data assets. However, with data being amassed, disseminated and deployed at a record pace, all too often data is mismanaged and misunderstood, resulting in a proliferation of business problems.

It’s the goal of every business to make their data an actionable asset that can drive better business decisions, but to do so, they need a winning data governance model. Successful data governance requires more than a collection of disparate tools combined with spreadsheets and Wikis. Using legacy resources and programs for governance often leads to mistrust or confusion among business users when they try to use them, because they’re often not updated or adequately maintained by the owners, or they’re created by IT, overly technical, and difficult to navigate. Yet when data governance is done correctly, business users are empowered to quickly find, understand and apply the right data sources to be analyzed and acted upon, and they’re assured that the quality of those data assets are maintained. Organizations just need to embrace a data governance strategy optimized for the future, and not remain reliant on tools or tactics from before the dawn of the big data age.

Data Governance Has Evolved

Successful data governance requires a collaborative, enterprise approach that puts business front and center. It requires organizations to bridge the divide between IT and business, and build cooperation among data owners, stewards and consumers to remove the ambiguity faced by business users as they perform critical business operations and make strategic decisions.

In the past, data governance was often a project undertaken within specific departments. Often reactionary, it might have served to address a regulatory fine or define data resources for a given group. But as with so many things, as time went on and employees left, the projects were often de-prioritized or forgotten. Today, data governance must be an enterprise-wide effort, because data is everyone’s concern, and its importance will never diminish. Organizations must engage all parties and clearly define varying roles and responsibilities among data owners, stewards and users to ensure full understanding of all data sets across the entire enterprise. Data is only valuable when users have confidence in both their data understanding and the integrity of all their data assets. In addition, data governance with effective collaboration builds both understanding and utilization of data to yield maximum business value.

However, fostering collaboration among different lines of business is not possible if the organization is relying upon various tools and spreadsheets. There needs to be a centralized data governance solution that delivers a business-friendly perspective of an organization’s data assets to build understanding and encourage collaboration.

Keeping Pace with Evolving Technologies

 A comprehensive data solution suite should include evolving data governance capabilities to help deliver a complete 360-degree view of an organization’s data landscape, from the data available, its owner/steward, lineage and usage, to its associated definitions, synonyms, and business attributes. It should allow business users to easily define, track and manage all aspects of their data assets, enabling collaboration to bring people and data together.

The solution suite should also include data quality capabilities for conducting data integrity checks such as data profiling, consistency, conformity, completeness, timeliness, and reconciliations to validate the integrity of data and ensure continued trust among business users. In addition, the solution suite should incorporate analytical capabilities to apply machine learning algorithms for self-learning to regularly improve data quality.

By combining the right people with the right approach and a modern solution, organizations can establish a winning data governance model to ensure their data supply chain delivers competitive advantage.

To learn more about a comprehensive data governance solution, download the data sheet below.

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