Organizations pay more in data integration tax every year due to a lack of vision, planning, management acumen, and sound technology choices. The spending is driven by passive leadership, inadequate incentive structures, low investment in scalable data architecture, misconceived data management, confusion over data ownership and access, data model inconsistency, application sprawl, naming inconsistencies, data source inconsistency, and dependency entanglements. To counter the tax increase, organizations can use their AI budget to build a data foundation for AI and leverage FAIR data principles.
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