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Decision-Making Is Driving Data Governance Programs, Not Regulatory Compliance, According to erwin’s New Study on Data Governance and Automation

erwin’s latest research reveals organizations are still grappling with data governance challenges and still depend largely on manual approaches for data lineage, data cataloging and data mapping

MELVILLE, N.Y., Jan. 28, 2020 – Data governance drivers have shifted, according to the 2020 State of Data Governance and Automation (DGA) report released today by erwin, with 62% of survey respondents citing better decision-making as the primary reason for implementing data governance. Regulatory compliance was the main driver two years ago, just ahead of the General Data Protection Regulation (GDPR) going into effect, so the new emphasis on decision-making may indicate organizations are using data to improve their overall performance, rather than merely ticking off a compliance checkbox.

As a follow-up to its 2018 State of Data Governance Report, erwin worked with Dataversity to look at how data governance attitudes and practices are evolving. This latest survey reveals that the most serious data governance bottlenecks are documenting complete data lineage (62%);  understanding the quality of source data (58%); finding, identifying and harvesting data (55%); and curating data assets with business context (52%).

“The results of our new research show that organizations are still trying to master data governance, including adjusting their strategies to address changing priorities and overcoming challenges related to data discovery, preparation, quality and traceability,” explains Mariann McDonagh, CMO for erwin. “That’s not surprising considering the amount and complexity of data to manage, plus most data operations are still manual and dependent on IT resources.”

In fact, this latest research reveals that data lineage would be the most valuable process to automate (65%), followed by data cataloging (48%) and data mapping (53%). But only 25%, 53% and 39% of these processes have been automated, respectively. “Without an accurate, high-quality, real-time data pipeline, it will be difficult to uncover the information necessary for making the best decisions. Automating data operations creates sustainable and repeatable practices that reduce errors, improve analytics and increase speed to insights,” McDonagh notes.

Other key findings of the 2020 State of DGA report:

  • 38% say their data governance programs are a work in progress and 31% are just getting started, as compared to 42% and 21% in the prior survey.
  • Analytics (51%), regulatory compliance (48%), digital transformation (37%) and data standards/uniformity (36%) are the primary drivers of data governance, behind better decision-making.
  • 67% have deployed data preparation, data governance or data intelligence solutions.
  • When asked to specify which types of the above solutions have been deployed, data analytics (65%), metadata management (59%), data quality (59%), data catalog (49%) and business glossary (49%) top the list.
  • 25% of respondents say length of project/delivery time is the most significant challenge, followed by data quality/accuracy at 24%, time to value at 16%, and reliance on developer and other technical resources at 13%.
  • 70% of respondents spend 10 or more hours per week on time-sinking data-related activities. Searching for data is the biggest culprit.

“Businesses still depend too much on manual approaches to data management,” McDonagh says. “Data availability, quality, consistency, usability and reduced latency are at the heart of successful data governance and sound decision-making. In today’s competitive landscape, stakeholders must have confidence in the data underlying the analytics they rely on for both strategic and tactical decisions.”

More than 260 North American business technology professionals at organization of various sizes,  responded to the erwin-Dataversity survey on which the 2020 DGA report is based. Most are in data and/or information architecture roles (29%), followed closely by information/data governance professionals (25%). Business intelligence/analysts are the third most represented job function, with data scientists and executive management also participating.

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