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Culture and Methodologies
Agile Career Development Methodologies Team Management
Data Engineering
AI/ML Big Data Data Databases IoT
Software Design and Architecture
Cloud Architecture Containers Integration Microservices Performance Security
Coding
Frameworks Java JavaScript Languages Tools
Testing, Deployment, and Maintenance
Deployment DevOps and CI/CD Maintenance Monitoring and Observability Testing, Tools, and Frameworks

Last call! Secure your stack and shape the future! Help dev teams across the globe navigate their software supply chain security challenges.

Modernize your data layer. Learn how to design cloud-native database architectures to meet the evolving demands of AI and GenAI workloads.

Releasing software shouldn't be stressful or risky. Learn how to leverage progressive delivery techniques to ensure safer deployments.

Avoid machine learning mistakes and boost model performance! Discover key ML patterns, anti-patterns, data strategies, and more.

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  4. Modern Data App Architectures and Best Practices for Building Data Apps

Modern Data App Architectures and Best Practices for Building Data Apps

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It’s safe to say data application builders will never worry about a lack of data. Approximately 40 zettabytes (ZB) of new data was generated in 2019, and IDC predicts that with a steady growth trajectory, 175 ZB will be generated in 2025. Although these ever-increasing amounts of data present immeasurable opportunities for delivering data-driven insights to customers, there are two crucial questions every startup and established ISV provider should ask:

Can your underlying architecture scale to meet the needs of your business?

How can we deliver and scale a performant product while remaining operationally efficient and cost-effective?

Presenters:

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Nagesh Cherukuri

Principal Architect, Data Apps, Field CTO Office, SNOWFLAKE

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