Before the invention of shortcuts in Microsoft Fabric, big data engineers had to create pipelines to read data from external sources such as Google Cloud Platform (GCP) buckets and write into Azure Data Lake Storage. This duplication of data is at risk of becoming stale over time. Additionally, computing power might be wasted on bringing over data that is used one time. With today’s companies being comprised of mergers and acquisitions over time, your company’s data landscape might exist in multiple cloud vendors. How can we virtualize the data stored in GCP buckets in our Microsoft Fabric Lakehouse design?
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