Question: Can you recommend a platform that allows me to build custom analytics into my product with minimal coding required?

If you want a platform where you can integrate custom analytics into your product with as little programming as possible, Sisense is a strong contender. It's got a lot of tools and features to accommodate different analytics needs, including integration, data connections to many sources, and AI and machine learning. Sisense offers pro-code, low-code and no-code options for advanced analytics, so it's flexible enough for businesses and developers. It also offers data visualization with drag-and-drop interfaces and interactive visualizations, and developer tools for building custom dashboards and sharing insights.

Another strong contender is Vizzly. It's geared specifically for modern SaaS companies, and it's got a no-code builder that lets you create interactive analytics experiences fast and easily. Vizzly offers interactive and customizable analytics dashboards with self-serve reporting, data modeling and queries, and native SDK-based embedding for popular frameworks. It also has a powerful Theme API for customization, so you can embed analytics capabilities without a lot of technical work.

If you prefer a more graphical interface, Tableau is a powerful business intelligence and analytics tool. Tableau connects to a variety of databases and lets you drag and drop to create visualizations. It's available in cloud, on-premises and Salesforce CRM deployment options, and it's got AI/ML abilities, governance and data management tools. Tableau is well known for its easy-to-use products and community-driven approach, so it's easier for people to create and share actionable insights.

Last, GoodData is another good option for creating customized data products with interactive analytics. It's got a no-code user interface, an AI Chat Assistant and the ability to embed analytics in cloud or on-premises environments. GoodData supports interactive dashboards and charts and streamlines workflows for data analysts and engineers, so it's good for both analytics engineers and consumers.