Главная
Study mode:
on
1
Intro
2
Agenda
3
Household announcements
4
Who is Alice
5
What does Alice need
6
What does the data look like
7
What do we know
8
What do you think
9
What is Azure Data Factory
10
Azure Data Factory Canvas
11
Why you should not use Azure Data Factory
12
What is Databricks
13
Who can use Databricks
14
Why use Databricks
15
Notebooks
16
Technical Knowledge
17
Synapse Analytics
18
Multiple disciplines
19
Comprehensive platform
20
Languages
21
Notebook
22
Error in Databricks
23
Error in Synapse Analytics
24
Lets Compare
25
What did Alice learn
26
What should Alice choose
27
Comparing tools
28
Comparing Spark clusters
29
Optimized Spark
30
Implementation Costs
31
Performance
32
Performance comparison
33
Cost comparison
34
Conclusion
35
Benchmarks
36
Summary
37
Maturity vs integration
38
Which should you choose
39
Its not that easy
40
When to use Azure Data Factory
41
When to use Databricks
42
When to use Synapse
43
Chart to make a decision
Description:
Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Explore a comprehensive conference talk that delves into the decision-making process for selecting the right Azure data engineering tool. Compare Azure Data Factory, Azure Databricks, and Azure Synapse Analytics, understanding their strengths, limitations, and ideal use cases. Learn about each tool's capabilities, including Azure Data Factory's canvas, Databricks' notebook environment, and Synapse Analytics' comprehensive platform. Discover implementation costs, performance comparisons, and benchmarks to guide your choice. Follow Alice's journey as she navigates through these options, and gain insights into when to use each tool. Utilize a decision-making chart to help determine the best fit for your specific data engineering project needs.

Azure Data Engineering Tools: Choosing Between Data Factory, Databricks, and Synapse Analytics

SQLBits
Add to list
0:00 / 0:00