Building a Data Lake or Data Warehouse in the Cloud: What you need to know

In an era where data is omnipresent, businesses face the decision of choosing between cloud data warehouses and cloud data lakes for storing and analyzing their data. Cloud data warehouses serve as centralized hubs for structured data, supporting analytics and insights with schemas that facilitate querying, offering scalability, cost-efficiency, and integration with familiar analytics tools. In contrast, cloud data lakes provide a flexible repository for both structured and unstructured data in its raw form, accommodating non-relational data from diverse sources and supporting AI/ML applications. Many companies find value in deploying both systems, leveraging the data warehouse for structured analytics and the data lake for managing unstructured data and real-time processing, thereby addressing a wide range of business needs and enhancing data-driven decision-making. Ultimately, the choice between a data warehouse, a data lake, or both depends on a company's specific data requirements and strategic goals.