Veracity, accuracy are important characteristics to produce high-quality results consistently.
It is not about being static or silo, as a matter of fact, it’s about connecting, communicating, and collaborating to enforce trust and transparency. Running a reliable business with steadfast speed takes planning, structure or process tuning, and measurement setting.
Veracity: Veracity refers to the quality, integrity, and credibility of data. It encompasses the truthfulness of information and the degree to which it can be trusted.
In the realm of big data, veracity highlights concerns regarding data quality, including issues like bias, inconsistencies, and the overall trustworthiness of data sources.
Veracity is crucial because it determines whether data can provide valuable insights. High veracity means that the data is not only accurate but also reliable and relevant for decision-making.
Accuracy: Accuracy refers specifically to how close a measured or calculated value is to the true value or actual state of affairs. Accuracy is often assessed in quantitative terms—such as how precise measurements are in scientific experiments or how correctly data reflects reality.
While accuracy is essential for ensuring that data points are correct, it does not necessarily imply that the data is trustworthy or complete. Data can be accurate but still lack context or relevance.
Veracity, accuracy are important characteristics to produce high-quality results consistently. In order to overcome multifaceted complexity, today’s business leaders and professionals need to keep consistent in having intellectual curiosity, learning agility, resourcefulness, reliability, etc.
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