Join AWS in this introductory session to learn about the power of data lakes and modern, cloud-based analytics architectures.

Data volumes are increasing at an unprecedented rate, exploding from terabytes to petabytes and sometimes exabytes of data. Traditional on-premises data analytics approaches can’t handle these data volumes because they don’t scale well enough and are too expensive. Many organizations are taking data from various silos and aggregating all that data in one location, called a “data lake” by many, to do analytics and machine learning. A data lake on AWS provides a centralized, scalable, and cost-effective location for data storage, while integrating with purpose-built analytics services so you can get fast insights from both structured and unstructured data. It also provides fine-grained access control and simple data governance, enabling you to secure and monitor access while at the same time democratizing access to your data through a centralized data catalog and self-service analytics.