Cloud, open-source, and SaaS business models have revolutionized how companies build and manage their technology stacks, leading to the development of the Modern Data Stack, which is a flexible array of technologies designed to help businesses store, manage, and analyze data. Typically cloud-based, these stacks incorporate low- and no-code tools that enable wider access to data without requiring advanced technical skills. The evolution of the data stack from on-premises systems to cloud solutions has facilitated significant improvements in security, cost-efficiency, and scalability, while the shift from ETL (Extract-Transform-Load) to ELT (Extract-Load-Transform) models allows for more efficient data processing. Self-service analytics tools, like Metabase, democratize data exploration, enabling non-technical users to access and analyze data independently. The modular nature of these stacks allows companies to easily adapt to changing needs without being locked into specific vendors. Key components of a Modern Data Stack include data sources, data ingestion, data storage, data transformation and modeling, data analytics, and data operationalization, each serving a unique role in creating a comprehensive data strategy.