Isbn: 9798265072450 - learn aws glue: create serverless etl pipelines and data catalogs: 15 (10 risultati)

Lingua: Inglese
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Lingua: Inglese
Editore: Independently published, 2025
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Lingua: Inglese
Editore: Independently published, 2025
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Lingua: Inglese
Editore: Independently published, 2025
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Lingua: Inglese
Editore: Createspace Independent Publishing Platform Sep 2025, 2025
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Taschenbuch. Condizione: Neu. Neuware - LEARN AWS GLUE Create Serverless ETL Pipelines and Data CatalogsRecommended for students and professionals seeking practical mastery in data orchestration, serverless ETL, and corporate pipeline automation with AWS Glue. The content covers everything from job creation, execution, and monitoring to advanced integration with AWS S3, Redshift, Athena, RDS, DynamoDB, Lake Formation, Glue Data Catalog, as well as connection with tools like Databricks, Apache Spark, Airflow, Python, PySpark, Pandas, Grafana, Kibana, and multi-cloud integrations with Azure and Google Cloud. Learn how to transform, catalog, and automate data flows, create scalable workflows, apply validation, tuning, partitioning, and optimize big data analytics in professional environments.Gain autonomy to build robust pipelines, implement data lakes, governance, and secure large-scale integrations.You will learn: - Configure and run serverless ETL jobs with Glue and PySpark- Integrate AWS Glue with S3, Redshift, Athena, RDS, and DynamoDB- Orchestrate multi-cloud pipelines, data lakes, and data automation- Manage Glue Data Catalog, workflows, triggers, and crawlers- Apply validation, tuning, partitioning, and performance in big data- Connect Glue to Databricks, Airflow, Python, Pandas, and Spark- Monitor and audit pipelines with Grafana, Kibana, and CloudWatch- Ensure security, governance, and automation of data routines- Optimize analytics, reporting, and corporate BI processesBy the end, you will master AWS Glue to build serverless, scalable, and secure ETL solutions ready for data projects, analytics, multi-cloud integration, and corporate automation.aws glue, etl, serverless, pipelines, s3, redshift, athena, data catalog, pyspark, airflow, databricks, big data, automation, cloud integration, governance, analytics, monitoring, partitioning, tuning.…

Lingua: Inglese
Editore: Independently Published, 2025
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Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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Paperback. Condizione: new. Paperback. LEARN AWS GLUE Create Serverless ETL Pipelines and Data CatalogsRecommended for students and professionals seeking practical mastery in data orchestration, serverless ETL, and corporate pipeline automation with AWS Glue. The content covers everything from job creation, execution, and monitoring to advanced integration with AWS S3, Redshift, Athena, RDS, DynamoDB, Lake Formation, Glue Data Catalog, as well as connection with tools like Databricks, Apache Spark, Airflow, Python, PySpark, Pandas, Grafana, Kibana, and multi-cloud integrations with Azure and Google Cloud. Learn how to transform, catalog, and automate data flows, create scalable workflows, apply validation, tuning, partitioning, and optimize big data analytics in professional environments.Gain autonomy to build robust pipelines, implement data lakes, governance, and secure large-scale integrations.You will learn: - Configure and run serverless ETL jobs with Glue and PySpark- Integrate AWS Glue with S3, Redshift, Athena, RDS, and DynamoDB- Orchestrate multi-cloud pipelines, data lakes, and data automation- Manage Glue Data Catalog, workflows, triggers, and crawlers- Apply validation, tuning, partitioning, and performance in big data- Connect Glue to Databricks, Airflow, Python, Pandas, and Spark- Monitor and audit pipelines with Grafana, Kibana, and CloudWatch- Ensure security, governance, and automation of data routines- Optimize analytics, reporting, and corporate BI processesBy the end, you will master AWS Glue to build serverless, scalable, and secure ETL solutions ready for data projects, analytics, multi-cloud integration, and corporate automation.aws glue, etl, serverless, pipelines, s3, redshift, athena, data catalog, pyspark, airflow, databricks, big data, automation, cloud integration, governance, analytics, monitoring, partitioning, tuning This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Lingua: Inglese
Editore: Independently published, 2025
- Brossura
- Print on Demand
Da: California Books, Miami, FL, U.S.A.California Books
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Altre immaginiLingua: Inglese
Editore: Independently Published, 2025
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Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 18,11
EUR 76,94 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Paperback. Condizione: New.

Lingua: Inglese
Editore: Independently Published, 2025
- Brossura
- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
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EUR 21,93
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Paperback. Condizione: new. Paperback. LEARN AWS GLUE Create Serverless ETL Pipelines and Data CatalogsRecommended for students and professionals seeking practical mastery in data orchestration, serverless ETL, and corporate pipeline automation with AWS Glue. The content covers everything from job creation, execution, and monitoring to advanced integration with AWS S3, Redshift, Athena, RDS, DynamoDB, Lake Formation, Glue Data Catalog, as well as connection with tools like Databricks, Apache Spark, Airflow, Python, PySpark, Pandas, Grafana, Kibana, and multi-cloud integrations with Azure and Google Cloud. Learn how to transform, catalog, and automate data flows, create scalable workflows, apply validation, tuning, partitioning, and optimize big data analytics in professional environments.Gain autonomy to build robust pipelines, implement data lakes, governance, and secure large-scale integrations.You will learn: - Configure and run serverless ETL jobs with Glue and PySpark- Integrate AWS Glue with S3, Redshift, Athena, RDS, and DynamoDB- Orchestrate multi-cloud pipelines, data lakes, and data automation- Manage Glue Data Catalog, workflows, triggers, and crawlers- Apply validation, tuning, partitioning, and performance in big data- Connect Glue to Databricks, Airflow, Python, Pandas, and Spark- Monitor and audit pipelines with Grafana, Kibana, and CloudWatch- Ensure security, governance, and automation of data routines- Optimize analytics, reporting, and corporate BI processesBy the end, you will master AWS Glue to build serverless, scalable, and secure ETL solutions ready for data projects, analytics, multi-cloud integration, and corporate automation.aws glue, etl, serverless, pipelines, s3, redshift, athena, data catalog, pyspark, airflow, databricks, big data, automation, cloud integration, governance, analytics, monitoring, partitioning, tuning This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…