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Dataquality is the top data integrity priority in 2024, cited by 60% of respondents. The 2025 Outlook: Data Integrity Trends and Insights report is here! What are the latest data integrity trends you need to know about? How does your dataprogram compare to your peers?
And yet, only 12% of organizations report that their data is of sufficient quality and accessibility for effective AI implementation. What are the primary data challenges blocking the path to AI success? Dataquality was the top data integrity challenge for 64% of organizations in 2024, up from 50% in 2023.
For the report, more than 450 data and analytics professionals worldwide were surveyed about the state of their dataprograms. Low dataquality 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 dataprograms.
And yet, only 12% of organizations report that their data is of sufficient quality and accessibility for effective AI implementation. What are the primary data challenges blocking the path to AI success? Dataquality is the top data integrity challenge for 64% of organizations this year, up from 50% last year.
Consistent: Data is consistently represented in a standard way throughout the dataset. Qualitydata must meet all these criteria. If it is lacking in just one way, it could compromise any data-driven initiative. However, simply having high-qualitydata does not, of itself, ensure that an organization will find it useful.
77% of data and analytics professionals say data-driven decision-making is the top goal for their dataprograms. Data-driven decision-making and initiatives are certainly in demand, but their success hinges on … well, the data that supports them. More specifically, the quality and integrity of that data.
This was made resoundingly clear in the 2023 Data Integrity Trends and Insights Report , published in partnership between Precisely and Drexel University’s LeBow College of Business, which surveyed over 450 data and analytics professionals globally. 70% who struggle to trust their data say dataquality is the biggest issue.
To remain competitive, you must proactively and systematically pursue new ways to leverage data to your advantage. As the value of data reaches new highs, the fundamental rules that govern data-driven decision-making haven’t changed. To make good decisions, you need high-qualitydata.
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