AWS Cloud Data Engineering Tech Stack

Focused View

Jim Macaulay

3:40:33

101 View

1. AWS Glue

1. Glue.mp4

00:51

2. Introduction.mp4

01:13

3. About the course.mp4

00:50

4. AWS Glue Console.mp4

03:09

5. Creating Database and Connections.mp4

03:39

6. Crawlers.mp4

04:44

7. Classifiers.mp4

06:13

8. AWS Glue Studio.mp4

04:04

9. Migrate data from S3 to RDS.mp4

07:09

10. Glue Transformations - Apply Mapping.mp4

05:19

11. Glue Transformations - Select Fields.mp4

02:34

12. Glue Transformations - Drop Fields.mp4

02:03

13. Glue Transformations - Drop Null Fields.mp4

01:42

14. Glue Transformations - Drop Duplicates.mp4

01:48

15. Glue Transformations - Rename Field.mp4

01:39

16. Glue Transformations - Split Fields.mp4

02:27

17. Glue Transformations - Join.mp4

05:22

18. Glue Transformations - Filter.mp4

01:44

19. Glue Transformations - Aggregate.mp4

02:04

20. Glue Transformations - SQL.mp4

03:10

2. AWS Glue DataBrew

1. DataBrew.mp4

00:34

2. Introduction.mp4

00:59

3. Overview of AWS Glue DataBrew.mp4

02:30

4. Create RDS Data Set.mp4

04:35

5. Create S3 Data Set.mp4

03:09

6. Filter.mp4

02:02

7. Column.mp4

01:55

8. Format.mp4

02:48

9. Clean.mp4

02:29

10. Extract.mp4

02:21

11. Missing.mp4

01:51

12. Invalid.mp4

01:37

13. Duplicates.mp4

01:44

14. Outliers.mp4

02:15

15. Split.mp4

01:44

16. Merge.mp4

01:46

17. Create.mp4

03:10

18. Group.mp4

02:04

19. Join.mp4

02:50

20. Union.mp4

03:01

3. AWS Athena

1. Athena.mp4

00:50

2. About the Course.mp4

00:53

3. Introduction and Navigation of Athena Interface.mp4

06:04

4. Creating Database.mp4

01:44

5. Creating Table.mp4

09:49

6. CTAS (Create Table As Select).mp4

03:14

7. Creating View.mp4

04:14

8. CTAS - Text.mp4

01:41

9. CTAS - Parquet.mp4

04:21

10. CTAS - Json.mp4

02:07

11. CTAS - ORC.mp4

01:36

12. CTAS - Avro.mp4

01:40

13. Partition.mp4

08:40

14. Bucketing.mp4

02:45

15. Partition and Bucketing.mp4

04:14

16. Insert.mp4

06:24

17. Delete.mp4

02:15

4. AWS Kinesis

1. Kinesis.mp4

01:03

2. Streaming.mp4

02:08

3. What will you learn .mp4

01:04

4. Kinesis Overview.mp4

01:26

5. Installation.mp4

05:00

6. Configuration.mp4

05:00

7. Useful Commands.mp4

00:52

8. DataStream.mp4

11:08

9. Data Firehose - Delivery Stream.mp4

10:08

10. Streaming from EC2 to S3.mp4

06:26

11. Streaming from EC2 to Redshift.mp4

06:39

Description

What You'll Learn?

AWS Cloud Data Engineering
Data Engineering Tools
ETL, Analytical, Querying and Streaming
Complete code Data Engineering tools in AWS Cloud Infrastructure

Who is this for?

ETL Architects

Cloud Data Engineers

Cloud Engineers

ETL Developers

Cloud Data Integration Specialists

Data Architects

Cloud Data Warehouse Developers

What You Need to Know?

No programming experience needed

More details

Description
This course is useful for,
ETL Developers
Data Engineers
ETL Architects
Data Migration Specialists
Database Administrators
Database Developers

Â Â Â Â Â Â Â Â Data integration is the process of preparing and combining data for analytics, machine learning, and application development. It involves multiple tasks, such as discovering and extracting data from various sources; enriching, cleaning, normalizing, and combining data; and loading and organizing data in databases, data warehouses, and data lakes. These tasks are often handled by different types of users that each use different products.

We will be working with the data platforms such as,
Data stores
Amazon S3
Amazon Relational Database Service (Amazon RDS)
Third-party JDBC-accessible databases
Data streams
Amazon Kinesis Data Streams
Firehose
Glue data catalog
Classifiers
Crawlers

AWS Data Engineering ensures fast querying to run Data Analytics on a massive volume of data and feed data to different Business Intelligence Tools, Dashboards, and other applications.

Data engineers work in a variety of settings to build systems that collect, manage, and convert raw data into usable information for data scientists and business analysts to interpret. Their ultimate goal is to make data accessible so that organizations can use it to evaluate and optimize their performance.

ETL, which stands for extract, transform and load, is a data integration process that combines data from multiple data sources into a single, consistent data store that is loaded into a data warehouse or other target system.
Who this course is for:
ETL Architects
Cloud Data Engineers
Cloud Engineers
ETL Developers
Cloud Data Integration Specialists
Data Architects
Cloud Data Warehouse Developers

User Reviews

Rating

average 0

Total votes0

Focused display

Amazon AWS

AWS Certified Cloud Practitioner

Jim Macaulay

Instructor's Courses

My self Jim, am an experienced Software and Robotics Engineer with a demonstrated history of working in the financial services industry. Passionate about teaching and blogging. Am also a YouTuber and an instructor. Skilled in Data Engineering with various ETL, Database and Cloud Technologies, and a Robotics Engineer. Strong consulting professional with a Master’s degree focused in Software Systems (Data Analytics) from Birla Institute of Technology and Science, Pilani.

Udemy

View courses Udemy

Students take courses primarily to improve job-related skills.Some courses generate credit toward technical certification. Udemy has made a special effort to attract corporate trainers seeking to create coursework for employees of their company.