Data Quality: How to Build Trust in the Data That Drives the Oil and Gas Enterprise

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Shale Play Optimization Analytics at Continental Resources

Everyone knows the importance of having accurate data in business. Decisions are made on it, it is required to comply with federal regulations, and people lose their jobs and sometimes even go to prison over it.

In today’s oil and gas market, it is even more critical to trust your data, share it with the right systems and people, and make informed decisions. Companies must have a strategy and commitment to cleanup up the data at the source and then accurately integrate it across the enterprise.

Persistent data quality problems do more than create explicit and hidden costs. An oft-cited Gartner study found that poor-quality data costs the average company a staggering $14.2 million annually.

What’s more, those surveyed by Gartner believe data quality problems will only get worse—which points to perhaps the most prevalent symptom of operation dysfunction in oil and gas: the lack of confidence and trust in corporate data.

This “bad data” psychosis affects executive-level data consumers and IT departments alike. The C-suite wants to harness data to understand the business and make decisions that increase operational efficiency and optimize profits. But if the underlying data is suspect, so are decisions based on analysis of that data.

When it comes to data management, “garbage in, garbage out” doesn’t have to be the oil and gas industry’s version of “c’est la vie.” There are powerful data quality (DQ) tools on the market today—such as Stonebridge’s EnerHub Data Quality Module—that enable high-quality data integration and interact with MDM solutions.

Using best practice-based rules and process automation, these DQ tools can run quality checks against source systems—e.g., WellView, Enertia, P2—and flag DQ violations before the data interacts with the MDM solution. The tools also track data quality over time in a measurable way that continually builds organizational confidence and trust so that the data can be integrated across the enterprise.

Data quality goes hand in hand with data orchestration as an essential component of a master data management (MDM) strategy. Both tactics not only help build the business’s trust and confidence in your enterprise data throughout the well life cycle, but also help lay the necessary foundation for digital transformation.

NOTE: This blog is based on the article “The Golden Record Is Not Enough: The Case for Data Orchestration,” published in PPDM’s Foundations magazine.

EnerHub is an enterprise data management solution developed for oil and gas companies by Stonebridge. Contact Stonebridge to schedule an EnerHub demo.

EnerHub’s Data Quality and Master Data Modules are powered by Naveego, a leading provider of cloud-first, distributed data accuracy solutions for seamless, end-to-end data quality and self-service master data management (MDM). Click here for more information about how the Stonebridge-Naveego partnership is advancing data management in oil and gas.