Data and AI World Tour 2024 Bangkok - Deep Dive on Data Management, AI, and Industry Applications
Dive into a comprehensive 2.5-hour conference session from the Data + AI World Tour 2024 in Bangkok, exploring cutting-edge technologies in data management, warehousing, governance, and generative AI for enterprises. Gain insights from industry leaders o…
How to Treat Your Data Platform Like a Product - 5 Key Best Practices
Discover 5 key best practices for treating your data platform as a product, ensuring reliability and scalability for maximum business value.
Data and AI World Tour 2024 Bangkok - Deep Dive on Data Management, AI, and Industry Applications
Explore cutting-edge data and AI technologies, real-world applications, and industry insights from global experts. Gain knowledge on generative AI, data governance, and optimizing data intelligence for enterprise success.
Data Engineering and Storage Concepts - With ETL, ELT, Warehouse, Lake, and Lake House
Comprehensive overview of data engineering concepts, including storage solutions, ETL/ELT processes, and modern data architectures like data mesh, with practical examples and best practices for effective data management.
Solving Business Problems with Data - Delivering Value Through Use Case Deconstruction
Explore strategies for aligning data teams with business goals, focusing on use case deconstruction and value delivery. Learn to bridge the gap between technical expertise and practical business impact.
The Evolution of the Open Data Ecosystem
Explore the evolution of open data ecosystems, addressing challenges in big data processing and introducing new approaches like data mesh and open APIs to streamline data management and accelerate value creation.
OS-Climate: A Breakthrough Open Data and Analytics Collaboration for Climate-Aligned Finance
Explore OS-Climate's open data and analytics initiative for climate-aligned finance, featuring Data Commons, Data Mesh, and tools for risk assessment and portfolio alignment.
Four Technical Value Drivers of a Data Lakehouse with Iceberg
Explore four key technical value drivers of data lakehouses and how Apache Iceberg enhances these capabilities for data practitioners across various roles.
Mastering Unity Catalog - Lessons from Zalando's Adoption Journey
Explore Zalando's journey in adopting Databricks Unity Catalog, overcoming challenges in a large-scale environment with diverse use cases, distributed schemas, and strict regulations to enhance data governance and productivity.
Accelerating Application Development with GraphQL Data Mesh
Explore how GraphQL Data Mesh can streamline and speed up application development processes, enhancing efficiency and productivity in modern software engineering.
NextGen Data Platforms - The Data Mesh Architecture and Domain-Driven Design
Explore domain-driven data mesh architecture and its implementation for efficient data platforms, focusing on decentralized ownership, federated governance, and self-serve functionality.
Data Mesh: From Experimentation to Industrialization - A Financial Services Case Study
Discover how a financial organization transformed their data architecture using Data Mesh on GCP, reducing lead times from months to days while enabling self-service analytics and cross-domain collaboration.
From Data Lakes to Data Mesh - The Evolution of Redmesh
Explore Bosch Digital's journey from data lakes to data mesh through redmesh, a self-service platform revolutionizing enterprise data management and analytics for faster, more efficient data-driven decision making.
Shell's Journey Towards Effective Data Governance with AI and Lakehouse
Shell's data strategy journey: Overcoming governance challenges with Unity Catalog, Data Mesh, and AI. Insights on aligning goals, identifying use cases, and scaling operations for data, analytics, and AI success.
What is a Data Mesh? - Understanding Decentralized Data Architecture
Explore data mesh architecture, its principles, and implementation strategies for scalable, domain-oriented data management in cloud-native environments.
DevOps Best Practices for DataOps Mesh
Discover DevOps best practices for implementing DataOps Mesh, enhancing data management and collaboration in complex environments.
Deep Dive into Data Mesh Principles
Explore Data Mesh principles: domain ownership, data as product, self-serve platform, and federated governance for modern business success.
Demystifying Data Mesh - Tackling Common Misconceptions About Data Mesh - Wannes Rosiers
Clarifies Data Mesh principles, debunks misconceptions, and explores its potential to revolutionize data management in distributed landscapes. Provides insights for better understanding of this approach.
Building a Data Mesh - Strategies and Best Practices
Explore data mesh architecture: benefits, challenges, and best practices for implementation. Learn strategies for designing data products, governance models, and ensuring data quality in this decentralized approach.
Scaling Machine Learning with Data Mesh - Shawn Kyzer
Explore scaling machine learning with Data Mesh, covering key concepts like data as a product, self-serve infrastructure, and federated governance. Learn innovative strategies for enhancing ML capabilities and driving business value.
Data Management for Your Next Generation Applications
Explore how a converged database streamlines infrastructure, eliminates complexity, and empowers developers to create innovative applications for next-generation business needs.