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Energy partnership drills down on data quality issues

Breitburn Energy Partners employed data quality tools to address the business pain of bad data, using the software to give end users the means to fix data quality issues themselves.

It's one thing to clean up data quality issues, and another to keep data clean on an ongoing basis. That is a takeaway from Patrick Seals, who has helped direct data quality efforts at U.S. oil and gas producer Breitburn Energy Partners. Data quality should be part of business processes, he said.

"Data quality is a day-to-day effort. You need tools that clean up data, while also ensuring that business processes are followed," said Seals, vice president and CIO at Breitburn, which is based in Los Angeles.

As part of work to combine diverse systems acquired via mergers, Breitburn implemented an ERP system from Enertia Software for general ledger, electronic invoicing and other needs. The ERP system was connected to a data warehouse.

Seals took over management of this implementation project upon joining the company in 2014. It was his job, he said with some bemusement, "to finish up the project and not screw anything up."

After the big bang

After the major "big bang" -- Seals' term for the work of launching a comprehensive ERP system -- wrapped up in April 2015, Breitburn set about to ensure data standards were continuously kept.

We needed a tool that identified problems with data and ... ensured internal folks adhered to the standard.
Patrick Sealsvice president and CIO, Breitburn Energy

There was some give and take in the effort to ease the burden on users. As part of that easing, the Breitburn data team reduced the number of primary attributes required to successfully fill out some business documents.

The data effort was, in part, enabled through the use of Naveego Inc.'s software, which includes data quality and master data management tools.

"We needed a tool that identified problems with data and that, as we added new data, ensured internal folks adhered to the standard," Seals said. He said Naveego's cloud-based tools enabled Breitburn analysts to check data quality for problems.

Cross-system comparisons

Naveego last week updated its data quality software, with a release that includes cross-system data comparison capabilities that make bad data more visible across diverse systems. Such comparisons make the tools a useful addition to Seals' toolbox.

"It easily shows the interrelationships of data and how terms are used in our different systems," Seals said. Connections to Naveego's data governance software, he added, help data managers highlight the downstream effect data quality issues can have on processes.

Cross-system comparison is an important inclusion in Naveego's latest release, according to Michael Osterman, an independent researcher and consultant. "Now, if you have similar elements in a CRM [customer relationship management] system and in an ERP system, you can quickly compare the data across them," he said.

Osterman said Naveego's systems, which are cloud-based, were effectively focused on end users. "It is not just the person working on master data management that is the focus of their efforts. Instead, the software is meant to help the end users out in the field," he said. "Each user has to be empowered to manage the data quality."

Such hands-on end-user tools help streamline processes that uncover data quality issues. For a company like Breitburn Energy Partners, one that has been highly focused on acquisitions, tools that ensure members of the organization "fill in the blanks" on data are critical.

The master limited partnership Breitburn Energy has encountered challenges in its pursuit of that strategy of acquisitions, development, and production of oil and gas properties in the United States, an area that has seen its share of ups and downs in recent years. Breitburn, at this writing, is restructuring under Chapter 11 in U.S. bankruptcy court.

Next Steps

Explore how data governance helps ensure data integrity

Learn how users can apply data quality rules

Read our guide to data quality assurance

Dig Deeper on Data quality management software

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