Trust is a rare commodity in the digital age in any industry. Between artificial intelligence (AI)-created content and questionable standards of ethics, it has never been harder to trust data. Data is nevertheless essential for making informed decisions and avoiding costly mistakes. This interesting topic came to us from Information Week in their article, “Trusting Data: Finding Truth, Building Transparency.“
When there is no clear data governance framework in place, users may question the reliability and consistency of data. Insuring that data analytics processes are well-documented and transparent makes it easier to validate the results they produce.
When the sources and methodologies used to collect or analyze the data are not well understood, users may doubt the credibility of the results and begin searching for the presenter’s motive for deceit. To build trust in data, organizations must ensure data quality, establish robust data governance practices, promote transparency, address bias, and prioritize data privacy and security concerns.
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Melody K. Smith
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