Data-driven processes are essential in the manufacturing sector to maintain competitiveness. However, manufacturers face challenges such as inconsistent data formats, difficulties in accessing data, and a lack of skills to analyze data effectively. Poor data quality can lead to operational inefficiencies, increased costs, and decreased product quality. Manufacturers must leverage IoT data for predictive maintenance, implement automated data cleaning, enhance data integrity through advanced lineage tracking, utilize machine learning for anomaly detection, and strengthen data governance with automated policy enforcement to improve data reliability and boost overall operational efficiency.