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One of the most common excuses used to avoid data democratization and self-serve augmented data discovery is that the organization cannot guarantee data integrity and that, if business users have access to dated, incorrect or incomplete data, the resulting decisions will not be better but rather worse than the decisions made today. Further, this theory says that the distribution of this inaccurate data will have a systemic effect on truth and promote disastrous business decisions.
One of the most common excuses used to avoid data democratization and self-serve augmented data discovery is that the organization cannot guarantee data integrity and that, if business users have access to dated, incorrect or incomplete data, the resulting decisions will not be better but rather worse than the decisions made today. Further, this theory says that the distribution of this inaccurate data will have a systemic effect on truth and promote disastrous business decisions.
Business Intelligence for Shipping: The Smart Choice! If you work in the shipping and distribution industry, you know how complicated life can be! The industry has come under increasing scrutiny as international trade, national trade, security concerns and other factors impact the shipping enterprise in ports, distribution hubs, and entry points around the world.
One of the most common excuses used to avoid data democratization and self-serve augmented data discovery is that the organization cannot guarantee data integrity and that, if business users have access to dated, incorrect or incomplete data, the resulting decisions will not be better but rather worse than the decisions made today. Further, this theory says that the distribution of this inaccurate data will have a systemic effect on truth and promote disastrous business decisions.
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