Is your data supply chain a liability?

Organizations have more data available today than ever before, and data architects, analysts, and data scientists are becoming prevalent in all business functions. Yet as companies fight for skilled analyst roles to utilize data to make better decisions, they often fall short in improving the data supply chain and resulting data quality. Without a solid data supply-chain management practices in place, data quality often suffers. Poor data quality is cited as the major reason initiatives fail to achieve their expected value – up to 60% of business initiatives fail because of data quality issues. Data quality becomes an even more pressing issue as organizations move toward AI/ML-enabled decision-making. If the data used to fuel AI/ML models is inaccurate, incomplete, or outdated, the models won’t deliver the desired outcomes. 

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