The transformation of data analytics from a field requiring specialized skills to one accessible to all employees has been driven by technological advancements in AI, cloud computing, and intuitive analytics tools. This evolution has enabled a shift towards data democratization, empowering organizations to make informed decisions without relying solely on data professionals. Self-service analytics tools, with user-friendly interfaces, allow users across departments to independently analyze data and generate insights, from marketing to finance. However, the expanding modern data stack also presents challenges such as cross-stack incompatibility and data access control gaps, which can be mitigated by implementing a universal semantic layer. This layer centralizes data modeling, metrics definitions, and security, ensuring consistent insights and efficient application performance. Embracing these advancements and solutions is crucial for companies to thrive in a data-driven world, leveraging the full potential of self-service analytics to foster a culture of informed decision-making.