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Udemy - Learn Azure data factory and AWS GLUE (ETL)

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Udemy - Learn Azure data factory and AWS GLUE (ETL) (Size: 3.7 GB)
  1. AWS GLUE PROJECT.mp4 167.3 MB
  1. Athena Introduction.mp4 14.3 MB
  1. INTRODUCTION.mp4 4.6 MB
  1. Introduction -SCD TYPE-1.mp4 19.8 MB
  1. Introduction ETL.mp4 7.5 MB
  1. Introduction and business use case.mp4 4.2 MB
  1. Introduction- 2 azure blob storage to output.mp4 7.7 MB
  1. Introduction- s3 to azure blob data pipeline.mp4 6.1 MB
  1. Introduction.mp4 8.2 MB
  1. introduction and business use case.mp4 7.1 MB
  10. PROJECT -1 END TO END REAL TIME PROJECT (GLUE+S3+LAMBDA).mp4 129 MB
  10. sorting.mp4 17.3 MB
  11. PROJECT -2 END TO END REAL TIME PROJECT PARTITIONING.mp4 93.8 MB
  11. between & in.mp4 15.4 MB
  12. like.mp4 11.3 MB
  13. distinct.mp4 7.7 MB
  14. union vs union all.mp4 16.3 MB
  15. join in sql.mp4 86.2 MB
  16. case satement.mp4 21.6 MB
  17. view.mp4 14 MB
  18. store procedure -1.mp4 15.3 MB
  19. store procedure -2.mp4 27.8 MB
  2. ADF PROJECT.mp4 277.7 MB
  2. Course Curriculum.mp4 17.2 MB
  2. PIPELINE.mp4 52.5 MB
  2. SETUP -SCD TYPE-1.mp4 65.7 MB
  2. SETUP- 2 azure blob storage to output.mp4 29.8 MB
  2. SETUP.mp4 2.2 MB
  2. Setup- s3 to azure blob data pipeline.mp4 3.7 MB
  2. WHAT IS GLUE.mp4 10.1 MB
  2. how athena works.mp4 4.1 MB
  2. project setup lab.mp4 65.7 MB
  2. setup lab.mp4 62.4 MB
  2. setup theory.mp4 2.3 MB
  2. sql commands.mp4 23 MB
  20. constrain in sql.mp4 33.9 MB
  21. constrain lab.mp4 74.8 MB
  22. row number, rank ,dense rank.mp4 43.5 MB
  3. Data pipeline.mp4 110 MB
  3. GLUE BENEFITS.mp4 7.1 MB
  3. PIPELINE -SCD TYPE-1.mp4 98.1 MB
  3. SETUP LAB.mp4 66.8 MB
  3. create data pipeline.mp4 59.7 MB
  3. create table.mp4 53.9 MB
  3. project create data pipeline.mp4 34.9 MB
  3. setup lab - s3 to azure blob data pipeline.mp4 53.2 MB
  3. setup lab.mp4 65.7 MB
  3. who is athena for and prereqisite.mp4 11.3 MB
  4. DATA PIPELINE.mp4 37.8 MB
  4. GLUE USE CASE.mp4 8.4 MB
  4. Introduction - Union.mp4 4.9 MB
  4. Introduction -SCD TYPE-2.mp4 37.3 MB
  4. alter.mp4 23.7 MB
  4. create data pipeline.mp4 82.2 MB
  4. difference between sql server and athena.mp4 13.7 MB
  4. pipeline- s3 to azure blob data pipeline.mp4 81.8 MB
  5. GLUE TERMINOLOGY.mp4 16.3 MB
  5. Introduction - blob to blob (copy & delete).mp4 7.1 MB
  5. LAB-1 athena create table by crawler.mp4 80 MB
  5. SETUP -SCD TYPE-2.mp4 65.7 MB
  5. SQL table specific columns transfer to azure blob.mp4 8.9 MB
  5. create data pipeline.mp4 91.3 MB
  5. filter.mp4 30.8 MB
  6. Alter & filter.mp4 6.5 MB
  6. Data Pipeline.mp4 80.1 MB
  6. GLUE ARCHITECTURE.mp4 10.9 MB
  6. Lab -2 create table without crawler and directly from s3.mp4 25.7 MB
  6. PIPELINE -SCD TYPE-2.mp4 135.2 MB
  6. Setup - blob to blob (copy & delete).mp4 2.8 MB
  6. delete drop.mp4 20.3 MB
  7. GLUE DEMO LAB.mp4 131.5 MB
  7. Project -1 superstore data analysis by using athena.mp4 76.7 MB
  7. Setup Lab - blob to blob (copy & delete).mp4 32.8 MB
  7. create data pipeline.mp4 93 MB
  7. group by & having.mp4 31.9 MB
  8. GLUE TRANSFORMATION LAB.mp4 170.2 MB
  8. Project -2 Partitioning using athena.mp4 52.5 MB
  8. aggregate funcion.mp4 14.3 MB
  8. pipeline blob to blob (copy & delete).mp4 63.6 MB
  9. GLUE TANSFORMATION LAB - MULTIPLE SOURCE.mp4 114.7 MB
  9. update delete.mp4 14.3 MB
  Bonus Resources.txt 409.6 B
  Get Bonus Downloads Here.url 204.8 B
  StatewiseTestingDetails.csv 608.3 KB
  covid_19_india.csv 981.9 KB
  covid_vaccine_statewise.csv 881.5 KB
  emp_1.csv 102.4 B
  emp_11.csv 102.4 B
  emp_2.csv 0 B
  employee1.csv 204.8 B
  employee2.csv 204.8 B
  employee3.csv 204.8 B
  sales_data_sample.csv 520.1 KB
  superstore.csv 2.2 MB
  ▲ 97 total files

Description


Learn Azure data factory and AWS GLUE (ETL)
https://DevCourseWeb.com

Published 10/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 84 lectures (9h 48m) | Size: 3.8 GB

Master ETL in cloud with AWS glue & Azure data factory lab

What you'll learn
Confidently work with AWS Serverless services to develop Data Catalogue, ETL, Analytics on a Data Lake
Build a serverless data lake on AWS using structured and unstructured data
By end of this course you will be able to develop pipeline in azure data factory
how to perform transformation in azure data factory
you will learn how to develop incremental load pipeline
you will be able to understand about databricks architecture and how to use
Industry level SCD type-1,type-2 projects
Failure handling and debug pipeline and learn about email alerts and all

Requirements
Good to have Azure and AWS Account for the practical lab
Good internet and laptop/desktop
Willing to learn

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