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Organizations can experience great benefits from adopting an end-to-end data lakehouse, including reduced efforts in data integration, a smoother pathway to ML/AI, accelerated time to value for advanced analytics, and improved governance and productivity through enhanced collaborations. However, a critical question arises for IT and business decision-makers: How can they justify investing in yet another data product when their technology stack already contains numerous tools, sometimes eight or more tools per step in the data lifecycle? That’s where an end-to-end data lakehouse comes in.

This checklist helps you follow steps that you can take to benefit from an end-to-end data lakehouse.

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