Latest public cloud publications

Data lakes can store masses of structured or unstructured data in raw format until your enterprise needs that data for analytics. That’s why data lakes are now seen as an attractive alternative to traditional data warehouses. However, enterprises like yours struggle to realize the expected return on data lake investments because of unexpected data quality, data governance, and data immediacy challenges. This paper describes how to address these issues and prevent your pristine data lake from devolving into a useless data swamp.

Data lakes can store masses of structured or unstructured data in raw format until your enterprise needs that data for analytics. That’s why data lakes are now seen as an attractive alternative to traditional data warehouses. However, enterprises like yours struggle to realize the expected return on data lake investments because of unexpected data quality, data governance, and data immediacy challenges. This paper describes how to address these issues and prevent your pristine data lake from devolving into a useless data swamp.

Data lakes can store masses of structured or unstructured data in raw format until your enterprise needs that data for analytics. That’s why data lakes are now seen as an attractive alternative to traditional data warehouses. However, enterprises like yours struggle to realize the expected return on data lake investments because of unexpected data quality, data governance, and data immediacy challenges. This paper describes how to address these issues and prevent your pristine data lake from devolving into a useless data swamp.

Data lakes can store masses of structured or unstructured data in raw format until your enterprise needs that data for analytics. That’s why data lakes are now seen as an attractive alternative to traditional data warehouses. However, enterprises like yours struggle to realize the expected return on data lake investments because of unexpected data quality, data governance, and data immediacy challenges. This paper describes how to address these issues and prevent your pristine data lake from devolving into a useless data swamp.

Data lakes can store masses of structured or unstructured data in raw format until your enterprise needs that data for analytics. That’s why data lakes are now seen as an attractive alternative to traditional data warehouses. However, enterprises like yours struggle to realize the expected return on data lake investments because of unexpected data quality, data governance, and data immediacy challenges. This paper describes how to address these issues and prevent your pristine data lake from devolving into a useless data swamp.