Cultivating Data Quality to Strategies, Challenges, and Impact on Decision-Making

Ronak Pansara

Abstract


Data quality plays a critical role in today's data-driven world. This research paper delves into the multifaceted aspects of data quality, exploring strategies for improving it, the challenges involved, and its profound impact on decision-making processes. We analyze the key factors affecting data quality, such as accuracy, completeness, consistency, and timeliness, and discuss methods for assessing and enhancing data quality. The study also investigates the repercussions of poor data quality, including errors, bias, and their implications for decision-making in various domains. With a focus on real-world applications, this research provides valuable insights into the pivotal role of data quality in the era of Big Data and analytics.

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