Главная
Study mode:
on
1
Agenda
2
Data Variety and Velocity
3
BigQuery
4
Governance
5
Object Tables
6
BigQuery Omni
7
Data is a product
8
Data bottlenecks
9
Crossfunctional data teams
10
Three fundamental tenants
11
Key building blocks
12
Serverless and scalable capabilities
13
Introducing TROL
14
Tribe Squat Hierarchy
15
Reminders
16
What is next
17
BigLake Architecture
18
Analytical Pipeline Architecture
19
ML Pipelines
20
Evaluation Framework
21
Whats next
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Discover how BigQuery and BigLake enable innovative data analytics solutions and implement AI/ML-powered data products for real-world applications in this 37-minute conference talk from Google Cloud Tech. Delve into the latest advancements in both technologies, focusing on BigLake's integration with Apache Iceberg for efficient AI/ML and BigQuery's role as a foundational element in successful data mesh architectures. Gain insights from industry leaders Trendyol and Snap as they share their transformative experiences using these technologies for large-scale analytics and AI initiatives. Explore topics such as data variety and velocity, governance, object tables, BigQuery Omni, data as a product, crossfunctional data teams, serverless and scalable capabilities, and analytical pipeline architecture. Learn about key building blocks, the TROL framework, and future developments in BigQuery and BigLake.

BigQuery and BigLake: Real-World Data Products for AI/ML at Scale

Google Cloud Tech
Add to list
0:00 / 0:00