Fivetran

Innovator

Overview

Fivetran, the global leader in data movement, helps customers use their data to power everything from AI applications and ML models, to predictive analytics and operational workloads. The Fivetran platform reliably and securely centralizes data from hundreds of SaaS applications and databases into any cloud destination — whether deployed on-premises, in the cloud or in a hybrid environment. Thousands of global brands, including Autodesk, Condé Nast, JetBlue and Morgan Stanley, trust Fivetran to move their most valuable data assets to fuel analytics, drive operational efficiencies and power innovation. 

Fivetran Inc. ("Fivetran") respects your right to privacy.  This Privacy Notice explains who we are, how we collect, store, share and use personal data about you, and how you can exercise your privacy rights.  This Privacy Notice applies to personal data that we collect, including through our website at www.fivetran.com, within our product(s) and on other websites that Fivetran operates and that link to this Privacy Notice (collectively “Websites”).  

Sponsored Sessions

  • Breakout
    Beginner
    Data Engineering and Streaming
    Databricks Workflows
    Energy and Utilities
    Retail and CPG, Food
    Financial Services
    yes
    All Sessions
    Data Ingestion
    Migrations
    Wednesday, Dec 10
    1:00 p.m. Wednesday, Dec 10
    Adevinta is a leading online classifieds group, operating digital marketplaces across Europe with over 120 million monthly users. As part of a strategic shift they set out to decentralize its data infrastructure and enable local autonomy. Within a year, the team transitioned from a central data lake to localized Databricks warehouses. To power this transformation, they turned to Fivetran as a reliable and scalable solution to integrate data from 40+ sources, including Google Ads, Salesforce, and Postgres. In this session, you will discover: - Key technical and organisational drivers behind Marktplaats’ decentralization strategy - How Fivetran streamlined data ingestion across 85% of sources in just weeks - Lessons learned while building scalable, autonomous data operations for local markets