PluralSight - Building Batch Data Pipelines on Google Cloud (2023)

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PluralSight - Building Batch Data Pipelines on Google Cloud (2023) (Size: 257.4 MB)
  01. Creating and re-using pipeline templates.mp4 6.9 MB
  01. Creating and re-using pipeline templates.vtt 5.5 KB
  01. Module introduction.mp4 1.1 MB
  01. Module introduction.vtt 512 B
  01. Optimizing Dataproc.mp4 4.7 MB
  01. Optimizing Dataproc.vtt 4.1 KB
  02. Module introduction.mp4 1.9 MB
  02. Module introduction.vtt 1.1 KB
  02. Orchestrate work between Google Cloud services with Cloud Co.mp4 1.8 MB
  02. Orchestrate work between Google Cloud services with Cloud Co.vtt 1.8 KB
  02. The Hadoop ecosystem.mp4 7.8 MB
  02. The Hadoop ecosystem.vtt 7 KB
  03. Aggregate with GroupByKey and Combine.mp4 9.6 MB
  03. Aggregate with GroupByKey and Combine.vtt 8.7 KB
  03. Apache Airflow environment.mp4 2.3 MB
  03. Apache Airflow environment.vtt 2 KB
  03. Optimizing Dataproc monitoring.mp4 5.4 MB
  03. Optimizing Dataproc monitoring.vtt 4.8 KB
  04. Lab Intro - Building and executing a pipeline graph in Cloud.mp4 546.1 KB
  04. Lab Intro - Building and executing a pipeline graph in Cloud.vtt 409.6 B
  04. Running Hadoop on Dataproc.mp4 15.9 MB
  04. Running Hadoop on Dataproc.vtt 14.6 KB
  05. Monitoring and Logging.mp4 6.8 MB
  05. Monitoring and Logging.vtt 5.8 KB
  05. Pluralsight - Getting Started with GCP and Qwiklabs.mp4 9.6 MB
  05. Pluralsight - Getting Started with GCP and Qwiklabs.vtt 5.7 KB
  06. DAGs and Operators.mp4 14.4 MB
  06. DAGs and Operators.vtt 10.5 KB
  07. Cloud Data Fusion UI.mp4 3.6 MB
  07. Cloud Data Fusion UI.vtt 2.4 KB
  07. Cloud Storage instead of HDFS.mp4 11.5 MB
  07. Cloud Storage instead of HDFS.vtt 8.4 KB
  07. Lab Intro - MapReduce in Beam.mp4 542.7 KB
  07. Lab Intro - MapReduce in Beam.vtt 512 B
  08. Explore data using wrangler.mp4 4 MB
  08. Explore data using wrangler.vtt 2.5 KB
  08. Lab Intro - Running Apache Spark jobs on Dataproc.mp4 861.7 KB
  08. Lab Intro - Running Apache Spark jobs on Dataproc.vtt 614.4 B
  08. Summary.mp4 2.4 MB
  08. Summary.vtt 3.4 KB
  09. Lab Intro - An Introduction to Cloud Composer.mp4 647.3 KB
  09. Lab Intro - An Introduction to Cloud Composer.vtt 614.4 B
  09. Lab Intro - Building a Simple Dataflow Pipeline.mp4 304.3 KB
  09. Lab Intro - Building a Simple Dataflow Pipeline.vtt 307.2 B
  09. Optimizing Dataproc storage.mp4 15.6 MB
  09. Optimizing Dataproc storage.vtt 12.2 KB
  1. Course Introduction.mp4 4.8 MB
  1. Course Introduction.vtt 1.3 KB
  1. Course Summary.mp4 5.3 MB
  1. Course Summary.vtt 5.2 KB
  1. Quality considerations.mp4 4.5 MB
  1. Quality considerations.vtt 4.4 KB
  10. Components of Cloud Data Fusion.mp4 3 MB
  10. Components of Cloud Data Fusion.vtt 2 KB
  10. Optimizing Dataproc templates and autoscaling.mp4 8.8 MB
  10. Optimizing Dataproc templates and autoscaling.vtt 7.9 KB
  10. Why customers value Dataflow.mp4 6.6 MB
  10. Why customers value Dataflow.vtt 4.4 KB
  11. Introduction to Cloud Data Fusion.mp4 6.4 MB
  11. Introduction to Cloud Data Fusion.vtt 4.3 KB
  11. Introduction to Dataflow.mp4 8.3 MB
  11. Introduction to Dataflow.vtt 8.7 KB
  11. Module introduction.mp4 1.2 MB
  11. Module introduction.vtt 614.4 B
  12. Side inputs and windows of data.mp4 9.4 MB
  12. Side inputs and windows of data.vtt 6.5 KB
  12. Summary.mp4 685.4 KB
  12. Summary.vtt 819.2 B
  13. Lab Intro - Practicing Pipeline Side Inputs.mp4 493.1 KB
  13. Lab Intro - Practicing Pipeline Side Inputs.vtt 512 B
  14. Build a pipeline.mp4 8.5 MB
  14. Build a pipeline.vtt 6.8 KB
  14. Key considerations with designing pipelines.mp4 3.9 MB
  14. Key considerations with designing pipelines.vtt 3.3 KB
  15. Building Dataflow pipelines in code.mp4 5.8 MB
  15. Building Dataflow pipelines in code.vtt 5.2 KB
  15. Workflow scheduling.mp4 9.6 MB
  15. Workflow scheduling.vtt 7.5 KB
  16. Transforming data with PTransforms.mp4 5.8 MB
  16. Transforming data with PTransforms.vtt 4.4 KB
  2. Module introduction.mp4 2.2 MB
  2. Module introduction.vtt 1.3 KB
  3. How to carry out operations in BigQuery.mp4 7.9 MB
  3. How to carry out operations in BigQuery.vtt 4.6 KB
  4. EL, ELT, ETL.mp4 6.9 MB
  4. EL, ELT, ETL.vtt 4.4 KB
  5. Shortcomings.mp4 7.4 MB
  5. Shortcomings.vtt 4.5 KB
  6. ETL to solve data quality issues.mp4 11.6 MB
  6. ETL to solve data quality issues.vtt 9.3 KB
  Bonus Resources.txt 409.6 B
  Get Bonus Downloads Here.url 204.8 B
  playlist.m3u 4.5 KB
  ▲ 93 total files

Description


Building Batch Data Pipelines on Google Cloud (2023)
https://DevCourseWeb.com

Released 6/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English + vtt | Duration: 2h 22m | Size: 257 MB

Data pipelines typically fall under one of the Extra-Load, Extract-Load-Transform or Extract-Transform-Load paradigms

Data pipelines typically fall under one of the Extra-Load, Extract-Load-Transform or Extract-Transform-Load paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud for data transformation including BigQuery, executing Spark on Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Dataflow. Learners will get hands-on experience building data pipeline components on Google Cloud using Qwiklabs.

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