Latest On premise publications

Selecting the right endpoint management solution for your organization can be a daunting task. With continuous growth and accompany security risks, comes the need to realize complex endpoint management needs with smooth IT operations and tightened security posture. If you are not getting the best from your solution, it’s time to pull up your socks... Read More

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.