Cloud data lake
More and more companies are using big data technologies to complement their existing data warehouse, and more often than not, they are looking at the cloud. The goal is to have multiple analytics projects, run on a scalable infrastructure, using advanced analytics and machine learning. The challenge in enterprise data lakes is to find the right balance between handling the many structured and unstructured data sources in a quick and agile fashion on one hand, and in delivering results that are useful and valuable, on the other hand. We've implemented several enterprise data lakes at large clients, usually in the cloud.
Through experience we found that no on-premise infrastructure or architecture can rival the scalability, reliability and agility of the cloud. We actively promote cloud migrations, and we are agnostic to which vendor the client decides to move. Using cloud technologies, we've seen processes which take 6 months on-premise, such as ordering new hardware, be done in 5 minutes, using automated scripting.