The article explores the ideological underpinnings of datafication, dataism, and dataveillance in the context of Big Data. It argues that datafication, the process of transforming social actions into quantifiable data, is rooted in problematic ontological and epistemological claims. Dataism, a belief in the objective quantification and tracking of human behavior through online media technologies, has gained traction due to widespread trust in corporate platforms and public institutions. This trust is extended to entities like academia and law enforcement, which handle personal data. The interplay between government, business, and academia in adopting dataism raises concerns about the credibility of the connective media ecosystem. Datafication has become a new scientific paradigm, with social media platforms collecting and analyzing vast amounts of metadata to predict human behavior. This has led to the concept of "life mining," where data is used to extract useful knowledge about individuals. However, the datafication paradigm is critiqued for its assumptions about data as neutral and objective, and for its implications on privacy and surveillance. The article also examines the trust in institutions, highlighting how data companies, governments, and researchers rely on users' trust in the datafication paradigm. This trust is often based on the belief that data is neutral and that institutions handle it responsibly. However, the Snowden revelations exposed the extent to which data is collected and used by governments and corporations, raising questions about the integrity of datafication. The article further discusses the struggle for credibility in the datafication ecosystem, emphasizing the role of users, governments, and institutions in maintaining trust. It highlights the challenges of balancing privacy and security, and the need for critical scrutiny of datafication's assumptions and practices. The article concludes that the credibility of the datafication ecosystem is under threat, and that a more critical and interdisciplinary approach is needed to address the ethical and social implications of Big Data.The article explores the ideological underpinnings of datafication, dataism, and dataveillance in the context of Big Data. It argues that datafication, the process of transforming social actions into quantifiable data, is rooted in problematic ontological and epistemological claims. Dataism, a belief in the objective quantification and tracking of human behavior through online media technologies, has gained traction due to widespread trust in corporate platforms and public institutions. This trust is extended to entities like academia and law enforcement, which handle personal data. The interplay between government, business, and academia in adopting dataism raises concerns about the credibility of the connective media ecosystem. Datafication has become a new scientific paradigm, with social media platforms collecting and analyzing vast amounts of metadata to predict human behavior. This has led to the concept of "life mining," where data is used to extract useful knowledge about individuals. However, the datafication paradigm is critiqued for its assumptions about data as neutral and objective, and for its implications on privacy and surveillance. The article also examines the trust in institutions, highlighting how data companies, governments, and researchers rely on users' trust in the datafication paradigm. This trust is often based on the belief that data is neutral and that institutions handle it responsibly. However, the Snowden revelations exposed the extent to which data is collected and used by governments and corporations, raising questions about the integrity of datafication. The article further discusses the struggle for credibility in the datafication ecosystem, emphasizing the role of users, governments, and institutions in maintaining trust. It highlights the challenges of balancing privacy and security, and the need for critical scrutiny of datafication's assumptions and practices. The article concludes that the credibility of the datafication ecosystem is under threat, and that a more critical and interdisciplinary approach is needed to address the ethical and social implications of Big Data.