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1
Introduction
2
Agenda
3
Historical Context
4
Why MultiCloud is Important
5
Challenges of MultiCloud
6
MultiCloud Business
7
Value Chain
8
Requirements
9
Who What Where
10
Azure
11
Service Principles
12
Integration
13
Data Sets
14
Inventory
15
Data Location
16
Data Assets
17
Data Ingestion
18
Local vs Federated Models
19
Takeaway
20
Databricks Lake House Platform
21
What is Databricks
22
Project Example
Description:
Explore the complexities and benefits of managing a multi-cloud data and analytics platform in this 40-minute video presentation by Databricks. Delve into the growing trend of multicloud adoption and its predicted prevalence by 2022. Discover the various reasons enterprises opt for multicloud strategies, including vendor lock-in prevention, access to best-of-breed cloud services, and regional requirements. Examine the challenges associated with this model, particularly the disparate approaches of different cloud providers. Learn how to effectively manage the Databricks Lakehouse Platform, a unified solution for data, analytics, and AI across major cloud providers such as AWS, Microsoft Azure, and Google Cloud. Gain insights into historical context, business value chains, integration techniques, data ingestion methods, and local vs. federated models. Conclude with key takeaways and a practical project example showcasing the Databricks Lake House Platform in action.

Managing a Multi-Cloud Data and Analytics Platform - Challenges and Solutions

Databricks
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