Quantifying the value of data preparation platforms

As organizations expand analytics beyond finance, adopt machine learning throughout business functions, and expand AI initiatives requiring clean data at scale, many have realized their data teams cannot keep pace with demand. Analysts report spending up to 80 percent of their time on data preparation rather than analysis. Although many analysts value their SQL and coding skills, manual preparation approaches do not scale with growing workloads. Data preparation platforms address this constraint by automating routine cleaning, connecting, and transformation tasks, allowing analysts to keep up with growing demands. Across user interviews, these platforms have delivered 40 to 60 percent improved analyst productivity while accelerating analytics and AI project timelines by 40 to 50 percent. Despite this need, buyers struggle to quantify the business case. A framework for translating time savings into financial value enables organizations to calculate potential returns from platform investments.