Building advanced data products comes with several challenges:
- End users consume analytics in many different ways, including dashboards; ad-hoc data discovery; exporting to Excel or desktop BI; importing data to AI, ML, and statistical tools; and receiving emails with PDF or XLS attachments.
- You have to maintain consistency of the analytics across multiple consumers and the channels mentioned above.
- Self-service that is required as a one-size-fits-all approach never works in analytics.
- Developers want to build dashboards rapidly and, as a code, integrate analytics to the stack with open APIs.
- Infrastructure teams need zero downtime and continuous deployment of the analytical stack, deployable to microservices-based projects.
- Product management needs flexibility, customizability, and a solution that will support its roadmap plans.
In this meetup, we will explain the fundamental concepts of a headless BI with live examples. You’ll learn:
- Why you should use the semantic model to ensure data consistency across all users of your data product
- How composable measures enable self-service analytics for your end users
- The importance of defining metrics and all analytics objects declaratively to achieve agile, continuous delivery of your data product
- How open APIs deliver analytics to all channels and places where your users need it
Meet the speakers
Does GoodData look like the better fit?
Get a demo now and see for yourself. It’s commitment-free.