Women in big data and analytics often face the challenge of bias embedded within data sets and algorithms. Data collected and used for training algorithms can reflect societal biases, disproportionately affecting outcomes related to gender. This can perpetuate stereotypes and inequalities, making it crucial for women in the field to actively work towards identifying and mitigating such biases.

Women in big data and analytics often face the challenge of bias embedded within data sets and algorithms. Data collected and used for training algorithms can reflect societal biases, disproportionately affecting outcomes related to gender. This can perpetuate stereotypes and inequalities, making it crucial for women in the field to actively work towards identifying and mitigating such biases.

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