Data mart or data lake: Choosing the right solution

In today's data-driven world, businesses need to process, store, and analyze large volumes of data. Two common solutions for managing this data are data lakes and data marts. A data lake is a centralized repository that stores all types of data in its raw format, while a data mart is a subset of an enterprise's data warehouse that contains specific business data. The key differences between the two include architecture, data sources, data analytics, data processing, scalability, and cost-effectiveness. Data lakes are highly scalable and can store large volumes of raw data from multiple sources, while data marts are designed for specific business functions or units and typically contain summarized and processed data. Choosing the right solution depends on the specific needs of your business. Factors to consider include data sources, data types, data storage, data processing, and data access. By making an informed decision, businesses can effectively use data to drive growth and success.