This course introduces students to self-service analytics (SSA), which aims to make business users more productive and less dependent on IT for their reporting and analytics needs. The course will appeal to business users as well as IT professionals. Topics covered in this course include an introduction to SSA, relationship with BI, capabilities of a data analytics platform, as well as the benefits for the organization, business users and IT. The course will teach how to assess if an organization is ready for an SSA platform and, also, how to plan and implement an SSA project. The course will enable students to identify the different types of users expected to use the SSA platform and how they can be mapped to the architecture. Since data is the lifeblood of an SSA platform, various data-related topics will also be covered, such as metadata, data pipelining, and governed data flow. Also covered will be the SSA architecture, as well as its components and tools. Other topics covered include data governance, security, training, data and user onboarding, and barriers to adoption, as well as challenges, common mistakes, best practices, lessons, and tips. The course will also examine the role and utility of artificial intelligence, particularly, generative artificial intelligence, for self-service analytics.