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Increase Data Lake ROI with Streaming Data Pipelines

Data lakes have emerged as an attractive complement to traditional data warehouses because they store masses of structured and unstructured data in native formats until analytical needs arise. However, many enterprises struggle to realize the expected return on data lake investments due to the unexpected challenges associated with data quality, data governance and data immediacy. This paper discusses how to automate your data lake pipeline to address these challenges and stop pristine data lakes devolving into useless data swamps.

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