Building datawarehouse by using Amazon redshift.

1. CASSANDRA Exploring NoSQL
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Building Data Warehouse by using REDSHIFT

2. What is Redshift?

3. 1. An Amazon Redshift data warehouse is an enterprise-class relational
database query and management system.
2. Amazon Redshift supports client connections with many types of
applications, including business intelligence (BI), reporting, data, and analytics
tools.
3. When you execute analytic queries, you are retrieving, comparing, and
evaluating large amounts of data in multiple-stage operations to produce a final
result.
4. Amazon Redshift achieves efficient storage and optimum query performance
through a combination of massively parallel processing, columnar data storage,
and very efficient, targeted data compression encoding schemes. This section
presents an introduction to the Amazon Redshift system architecture.
What is Redshift?

4. Data warehouse

5. ETL?

6. 1. Time consuming
2. Expensive
3. Complexity with parallel processing
4. Hard to scale
5. Does not support data lake
6. Fault tolerance
Challenges?

7. ELT instead of ETL
Redshift

8. Redshift
Redshift works on principle called ELT

9. Build Schema on Target Database(Redshift)
Create a CSV from your datasource and put into S3
Use COPY command to upload data into Redshift
How ELT looks with Redshift

10. Sample DW house Redshift
https://github.com/nanofaroque/data-engineering-udacity/tree/master/Lesson_3/
Data_Warehouse

11. Redshift internal architecture?

12. Columnar Storage?

13. 1. 1/3 IO of row based storage
2. Better compression
3. Better Storage options for unstructured rows
4. Bigger block size reduces IO
Benefits of columnar storage?

14. Redshift run on Single AZ but not in multi AZ.
Fault Tolerance

15. Fault Tolerance

16. Fault Tolerance

17. Fault Tolerance

18. Fault Tolerance

19. What happened leader fails??
Benefits of columnar storage?

20. 1. All blocks on disk and s3 are encrypted
2. SSL is used in data transit
3. VPC is used for network isolation
4. Audit logging with cloud trail
Security

21. 1. We can use different type of instance
2. Resizing is super easy by using CLI or few clicks on console
3. During resizing, cluster becomes read only. Data will be
copied to new cluster with MPP
Scalability

22. https://github.com/nanofaroque/nerd-read/tree/master/redshift
Good Read

23. Thanks
The Omar