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Emerging Data Quality Trends Address Data Governance and More

Authors Photo Rachel Levy Sarfin | January 6, 2020

There’s more data in the world than ever before, and there’s no sign of data generation slowing down. The volume, velocity, and variety of information is staggering. 

The information being created can be immensely valuable, but only if you apply data management and data governance best practices. Since data has changed, so too have data standards. This blog post explores which new data governance and data management trends you should know about to make the most of your information. 

Data: the fuel for the new economy

In the May 6, 2017 edition of The Economist, a briefing appeared discussing the importance of data in today’s economy. The briefing’s author compared information in this century to oil in the last century: an economic driver. 

“Flows of data have created new infrastructures, new businesses, new politics and crucially, new economies,” the briefing states. The Economist isn’t the only publication to pick up on data’s importance; if you perform an Internet search on just how significant information is today, you’ll receive millions of results. 

Although data’s value has reached unprecedented heights, certain rules haven’t changed: if the quality of the information is low, you can’t make good decisions based on it. Because data has fundamentally changed, the guidelines surrounding data governance and data management have been updated, too.

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New data quality trends for changing information 

Business initiatives across industries are applying more data than ever to drive analytics and AI in the quest for new competitive insights. As the volume and variety of data gathered by organizations continues to escalate, both on-premises and in the cloud, traditional methods of data quality are transforming to meet this big data challenge.

While traditional data governance and data management practices are falling short in the face of the new types of information coming into the enterprise, organizations are putting additional data quality measures in place, such as looking at information’s provenance, its continuity, and how much it’s changed from its origin. Looking at these aspects of your data will give you better insight into how complete, accurate, correct, and relevant it is. 

Another reason to update your data governance and data management practices is crucial technological updates: AI and machine learning. Both of those technologies rely upon high-quality data; without it, AI and machine learning can’t properly correlate information, leading to poor decision making for business leaders. 

Because there’s so much more information than ever before, it’s vital that companies can carry out data governance and data management best practices at scale. Automating these processes is the only way to cleanse that much information at once. 

Read our whitepaper to explore three ways that data quality can supercharge your data governance program, both now and in the future.