Quantifying the value of data integration

As organizations attempt to collect and utilize a growing abundance of data to drive analytics initiatives and AI projects, many have realized the limitations of their existing data integration platforms. Legacy tools present processing and maintenance challenges as workloads and data volumes scale, while rigid compute capacity and inefficient data movement create bottlenecks that delay initiatives. Modern platforms resolve these issues by delivering integration-as-a-service with managed infrastructure and automated operations. Despite this operational need, buyers struggle to quantify the business case, failing to translate the technical uplifts to financial returns that drive investment and financial teams. Organizations should consider how data integration investments translate into cost savings, time savings, and profit extension and build a business case that connects both technical and financial teams to align decision making and promote consistent returns.