Data lake is a very large scale data processing paradigm that disrupts the conventional data warehousing model. Data warehouses require all data to be structured and stored in a relational database, which can be inflexible and may require significant upfront data processing using extract-transform-load (ETL) technologies.
Data lakes can offer greater flexibility whilst retaining the benefits and efficiency of centralised data governance. With Canonical OpenStack private cloud platform, Kubernetes and Charmed Spark solutions, your data lake architecture can also benefit from extended flexibility and scalability whilst remaining cost effective to operate.
Join this webinar to learn more about the benefits of the data lake architecture, and how you can efficiently adopt this technology at scale using modern private cloud technology.
Learn more or contact our team: https://canonical.com/data/spark