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Why Spatial Data Governance is Critical to Your Business Strategy

Precisely

When speaking to organizations about data integrity , and the key role that both data governance and location intelligence play in making more confident business decisions, I keep hearing the following statements: “For any organization, data governance is not just a nice-to-have! “ “Everyone knows that 80% of data contains location information.

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Solving 5 Big Data Governance Challenges in the Enterprise

Precisely

According to a recent report from Drexel University’s LeBow Center for Business Analytics , 77% of data and analytics professionals say that data-driven decision-making is an important goal of data programs. However, fewer than half of survey respondents rate their trust in data as “high” or “very high.”

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Linking Data Governance to Business Goals

Precisely

Despite that understanding, many organizations lack a clear framework for organizing, managing, and governing their valuable data assets. In many cases, that realization prompts executive leaders to create a data governance program within their company. In many organizations, that simply isn’t the case.

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Five Reasons Automation Is Key to Data Governance

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According to a recent report on data integrity trends from Drexel University’s LeBow College of Business , 41% reported that data governance was a top priority for their data programs. Automating functions in support of data governance provides a range of important benefits.

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Data Program Investments are Yielding Business Value

Precisely

The 2023 Data Integrity Trends and Insights Report , published in partnership between Precisely and Drexel University’s LeBow College of Business, delivers groundbreaking insights into the importance of trusted data. Data-driven decision-making is the top goal for 77% of data programs. One major finding?

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Poor Data Quality is Pervasive, Impacting Trust in Data and Success Across Data Programs

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For the report, more than 450 data and analytics professionals worldwide were surveyed about the state of their data programs. Low data quality is a pervasive theme across the survey results, reducing trust in data used for decision-making and challenging organizations’ ability to achieve success in their data programs.

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Expert Insights for Your 2025 Data, Analytics, and AI Initiatives

Precisely

Key Takeaways: Data integrity is required for AI initiatives, better decision-making, and more – but data trust is on the decline. Data quality and data governance are the top data integrity challenges, and priorities. This gap underscores the urgent need for better data foundations.