Datum
09.12.2021 - 17:00 - 18:00 Uhr
Veranstaltungsort
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Termin: Outlook: iCal
Building advanced data products comes with several challenges:
• end-users consume analytics in many different ways: dashboards, ad-hoc data discovery, exporting to excels or desktop BI, importing data to AI, ML, and statistical tools, 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 down-time and continuous deployment of the analytical stack, deployable to microservices-based projects
• product management need flexibility, customizability, and solution that will support their roadmap plans
In this meetup, we will explain the fundamental concepts of a headless BI with live examples. You’ll learn:
• why 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
• why define metrics and all analytics objects declaratively to achieve agile, continuous delivery of your data product
• how Open APIs delivers analytics to all channels and places where your users need it
You can download your version of the headless BI from dockerhub: https://hub.docker.com/r/gooddata/gooddata-cn-ce or learn more about the product at https://www.gooddata.com/developers/.
Speakers:
Martin Svadlenka, Product Manager
Martin has spent most of his professional career as a Product Manager, including years of experience working with customers and users from many different business domains. He considers life as one big product management experience — from the vision and roadmap to efficiently collaborating with others. At GoodData, Martin leads GoodData.CN, the cloud-native, headless analytics service. He ensures that all users — from developers to data analysts — will have a successful tool for valuable analytical projects and applications.