Why Develop Data Products on Top of Headless BI
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Contact usDescription
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
You can download your version of the headless BI from dockerhub, or learn more about the product at www.gooddata.com/developers.
If you are interested in GoodData.CN, please contact us. Alternatively, sign up for a trial version of GoodData Cloud: https://www.gooddata.com/trial/
Meet the speakers
Martin Svadlenka
Product Manager
GoodData
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