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1
Introduction
2
Agenda
3
Data Lake House
4
Unified Data Platform
5
Performance
6
When to use it
7
How to use it
8
GRPC
9
Governance
10
Programmability
11
File optimization
12
Hierarchical namespace buckets
13
Challenges
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Discover how to leverage Google Cloud Storage for unifying data in analytics workloads in this 33-minute conference talk from Google Cloud Next 2024. Learn about the benefits of Cloud Storage, including exabyte scalability, strong consistency, and cost-effectiveness. Explore new product announcements and hear from enterprise customers about real-world solutions integrating Cloud Storage with BigQuery, Hadoop, Spark, and Kafka. Gain insights into topics such as Data Lake House architecture, unified data platforms, performance optimization, GRPC implementation, governance strategies, programmability options, file optimization techniques, and hierarchical namespace buckets. Address common challenges and understand when and how to effectively use Google Cloud Storage in various analytics scenarios.

How to Use Google Cloud Storage to Unify Data for Analytics Workloads

Google Cloud Tech
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