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Data Warehousing im Lakehouse

On Demand

Type

  • Session

Format

  • Hybrid

Track

  • Data Lakes, Data Warehouses and Data Lakehouses

Room

  •  Moscone South | Level 2 | 215

Duration

  • 35 min

Überblick

Most organizations routinely operate their business with complex cloud data architectures that silo applications, users and data. As a result, there is no single source of truth of data for analytics, and most analysis is performed with stale data. To solve these challenges, the lakehouse has emerged as the new standard for data architecture, with the promise to unify data, AI and analytic workloads in one place. In this session, we will cover why the data lakehouse is the next best data warehouse. You will hear from the experts success stories, use cases, and best practices learned from the field and discover how the data lakehouse ingests, stores and governs business-critical data at scale to build a curated data lake for data warehousing, SQL and BI workloads. You will also learn how Databricks SQL can help you lower costs and get started in seconds with instant, elastic SQL serverless compute, and how to empower every analytics engineers and analysts to quickly find and share new insights using their favorite BI and SQL tools, like Fivetran, dbt, Tableau or PowerBI.

Session Speakers

Franco Patano

Product Specialist DBSQL

Databricks

Jonathan Keller

Sr. Director, Product Management

Databricks

Haley Creech

Product Director, Enterprise Data and Analytics Platform

GSK

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