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The data-driven economy has been in full swing for two decades, and it is only accelerating. But just because the data-driven economy is here to stay doesn’t mean that organizations have been able to fully participate. There are many challenges that prevent organizations from effectively using the data that they gather or from efficiently driving data projects forward. Barriers to making the most of data come in many forms:
Garbage in, garbage out. If the quality of test data for software development and data projects is poor, so are the results. Significant effort during data projects goes to identifying and filling gaps and adjusting for bias. These are not easy fixes, and require time and often manual resources. Traditional test data management solutions are not always able to adequately address these quality issues, leading to subpar results.