Explore the data lakehouse architecture in this 25-minute keynote presentation by Arsalan Tavakoli-Shiraji, SVP of Field Engineering at Databricks. Dive into the challenges organizations face in managing massive amounts of data and learn how the data lakehouse offers a flexible, multi-cloud solution supporting all data types, teams, and use cases. Discover key concepts of the Databricks Lakehouse Platform and its applications in data engineering, analytics, data science, and machine learning. Gain insights into the Data and AI Maturity Curve, open-source trends, and multi-cloud strategies. Understand how the data lakehouse simplifies data infrastructure, addresses challenges of traditional data lakes, and incorporates features like Delta Lake, Unity Catalog, and Delta Sharing. Explore role-based experiences and industry-wide adoption of the lakehouse architecture, equipping you with knowledge to leverage data for innovation and business outcomes.
Discover the Data Lakehouse: Simplifying Data Architecture for Analytics and ML
Databricks via YouTube
Overview
Syllabus
DATA+AI Virtual WORLD TOUR Training
Data explosion has created clear winners
But effectively leveraging data is not easy
We know data is critical to business outcomes
The Data and Al Maturity Curve From descriptive to prescriptive
Open source tailwinds
All organizations will be multi-cloud
Eliminate complexity
Data infrastructure is too complicated
Warehouses and lakes create complexity
The data lakehouse offers a better path
Data lakes alone present challenges
Delta Lake provides solutions
Unity Catalog for Governance of the Lakehouse
Delta Sharing Secure data sharing between organizations
ML & data science workloads on Databricks
Full ML Lifecycle on Databricks From data ingest to model deployment
Data engineering workloads on Databricks
SQL workloads on Databricks
Role based experiences A unified platform with purpose-built experiences for every member of a data team
Lakehouse adoption across industries
Taught by
Databricks
