Employing a distributed architecture on public cloud platforms enhances efficiency and cost-effectiveness. Large, centralized databases can lead to high expenses and are not well-suited for cloud environments. Instead, utilizing smaller, flexible data structures allows teams to meet non-functional requirements effectively. The cloud is optimized for handling numerous small data instances, akin to 'pebbles' rather than 'boulders.' Teaching this approach fosters a better understanding of the cloud's capabilities, encouraging the division of tasks into smaller components for improved performance and resource management.
Data is at the center of many business decisions and advances today, including AI-driven capabilities. This requires companies to have well-governed data that is easy for users to find, use and understand. In moving to the cloud, Capital One modernized its data ecosystem and adopted a “You Build, Your Data” model to equip its data stakeholders with self-service capabilities to use and build data applications.
Jim Lebonitte is a Senior Distinguished Engineer at Capital One leading technical architecture and strategy for enterprise data platforms. He has over 15 years of experience building platforms focused on data and software delivery experiences. Jim joins the podcast to talk about how to empower data users at scale while keeping data well-governed, building data pipelines and applications, and much more.
Full Disclosure: This episode is sponsored by Capital One.
This episode is hosted by Lee Atchison. Lee Atchison is a software architect, author, and thought leader on cloud computing and application modernization. His best-selling book, Architecting for Scale (O’Reilly Media), is an essential resource for technical teams looking to maintain high availability and manage risk in their cloud environments.
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