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Effective business decision- making depends on providing staff, business intelligence (BI) tools and AI or analytics models with data that’s accurate, consistent and framed with the right context. We call this ‘data integrity’, and our first Data Integrity Trends survey seeks to measure how effectively enterprises are doing this across the world. This report summarizes what we discovered to paint a unique picture of how successfully enterprises are establishing and maintaining bases of high-integrity data to fuel their data-driven business transformations. Our findings suggest that most enterprises believe they have now laid the foundations for data-driven decision-making and automation at least quite successfully, but they also reported significant struggles. There’s still a way to go before staff will trust data-driven insights over their own intuitions. Currently, 45% of the executives we surveyed are democratizing data to empower staff to self-serve their own data-driven insights. But most have yet to take these projects beyond the ‘early adopter’ phase. Achieving strategic objectives like this will mean overcoming a range of technical and human challenges. Most of our survey respondents still lack the staffing resources and tools they need to manage their data effectively, while 73% say a lack of technology or services to facilitate data integration is creating challenges for their teams. However, our research also shines a light on the work top executives are doing to overcome these challenges. Automating data management processes, breaking down data silos, augmenting company data with third-party datasets, leveraging location information for business insights and embracing low-code/ no-code environments have emerged as steps enterprises can take to help enhance the integrity of their data. |
