Building a Multi-Cloud Data Fabric for Analytics

1

Introduction

00:00 • 2min

2

Why You Need a Data Lake

02:04 • 2min

3

Data Lake - The Data Lake Is a Great Way to Quickly and Easily Query Data

04:17 • 4min

4

Are You Seeing More Use Cases With Data Warehouse and Data Lake?

07:54 • 4min

5

Is There a Single Cloud or Multi Cloud?

12:15 • 4min

6

Is There a Reduced Cost in Multi Cloud?

15:53 • 4min

7

Cloud Computing

19:55 • 2min

8

Using a Third Party Product to Extract the Latest Changes in a Table

21:27 • 4min

9

Azure Data Factory - The Best Way to Save Time and Money

24:58 • 2min

10

A Data Fabric Is a Data Warehouse

27:23 • 5min

11

Is There a Difference Between a Data Lake and a Relational Database?

32:27 • 3min

12

Decentralization of the Data Mesh

35:01 • 4min

13

Data Mesh Is the Theory of It All, but We Need to Technology Behind It to Make It Effective

38:55 • 2min

14

Data Mesh - The Number One Problem I've Seen With Customers

40:34 • 2min

15

Data Mesh

42:37 • 3min

16

Streaming ETL Versus Batchloading?

45:42 • 3min

17

The Data Lake Versus the Data Warehouse

48:27 • 4min

18

The Difference Between Snowflake and Synapse

52:12 • 4min

19

Data Fabric and Data Match - What's the Key Difference?

56:05 • 3min