Mastering Data Governance
Follows These Steps for Mastering Data Governance
To realize optimal returns on data assets, organizations must have a firm understanding of that data from a business context and they must be able to quantify its quality value. But with data being amassed at such a rapid pace, there has been a proliferation of business problems caused by mismanaged and misunderstood data.
The confluence of increasing government regulations, the escalating need to leverage advanced analytics, and a growing number of organizational teams accessing and applying data to make better business decisions have created an urgent demand for data clarity. Mastering data governance to ensure a firm understanding of data to battle the shifting tides of business policies and business alignment in an increasingly complex regulatory landscape is the new challenge.
Taking the Right Approach to Mastering Data Governance
Mastering data governance requires more than just the right tools; it also requires the right people and the right processes. More often than not, data governance is presumed to be an IT task, but who actually leverages the data to make business decisions? Not the IT department; operational areas are appropriately tasked with interpreting data to drive business decisions. Therefore, when IT is tasked with implementing data governance, there is often a communication disconnect, leaving business users to try and translate the IT department’s technical jargon, and precious IT resources wasted playing interpreter.
To be successful, data governance should never fall on just one department or a single group of people. It requires organizations to build collaboration among data owners and data consumers to remove the ambiguity faced by business users as they perform critical business operations and make strategic decisions.
Organizations must engage all parties and clearly define varying roles and responsibilities among data owners, stewards, and users to ensure full understanding and frequent updates across the entire enterprise. It is only when users have confidence in both their data knowledge and the quality of data assets that they will deem it trustworthy and dependable for use in making important determinations. Data governance with effective collaboration, then, not only builds understanding, but utilization of data to extract maximum business value.
However, fostering collaboration among different lines of business is not always easy. Everyone in the organization has responsibilities outside of managing data, and asking every individual to invest additional time to help with data governance can be a major inconvenience. To help, organizations need an all-inclusive data governance platform that delivers a business-friendly perspective of an organization’s data landscape across the enterprise.
An all-inclusive data governance platform should 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 any user to easily define, track, and manage all aspects of their data assets, enabling collaboration, knowledge-sharing, and user empowerment through transparency across the enterprise.
The platform should champion a community approach to bridge the business to technical divide and bring people and data together. The platform should also clearly define ownership and accountability for every data asset, so everyone knows the resource when they have pressing questions about data, such as, how is it used? Is it trustworthy? What is the definition?
With the right platform and the right approach, mastering data governance allows organizations to get a step ahead of their competition.
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