Data extreme usa - 18-teilige buchserie (4 Ergebnisse)

Zustand: New. In English.

Taschenbuch. Zustand: Neu. Neuware - LEARN PostgreSQL Master the World's Most Powerful Relational DatabaseThis book is ideal for professionals and students who want to master PostgreSQL in a practical and applied way. With a technical and progressive approach, you will learn how to create, manage, and optimize robust databases for modern applications.You will learn to: - Install and configure PostgreSQL environments on multiple operating systems- Build tables, schemas, indexes, and constraints to ensure data integrity- Perform CRUD operations with optimization techniques and transaction control- Model secure, scalable, and highly available relational databases- Integrate PostgreSQL with Python and Node.js applications using specialized libraries- Implement replication, data partitioning, and high-performance strategies- Automate backups, restore databases, and monitor performance with advanced practices- Work with JSON, custom functions, triggers, and powerful extensionsMaster PostgreSQL and accelerate your professional growth in critical data projects, technical consulting, and scalable system architectures. …

Taschenbuch. Zustand: 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.…

Taschenbuch. Zustand: Neu. Neuware - LEARN PYDANTIC V2 Master Data Modeling and Validation with High PerformanceThis book is intended for students and professionals in data, software engineering, machine learning, and cloud who want to master advanced validation, schema automation, and robust integrations with Pydantic V2. Learn to apply high-performance models in Python environments by integrating FastAPI, SQLAlchemy, Pandas, Dataclasses, Typer, Poetry, Alembic, Celery, Airflow, Kafka, MongoDB, PostgreSQL, AWS Lambda, and Google Cloud Functions. The content covers asynchronous validation, dynamic typing, efficient parsing, automated testing, JSON serialization, OpenAPI documentation, deployment via Docker, Kubernetes, and full integration with CI/CD, DataOps, and MLOps pipelines.Includes: - Dynamic schema structuring and automation with Pydantic V2- Integration with FastAPI, Typer, SQLAlchemy, Pandas, Dataclasses- Data consumption and validation in REST APIs, Kafka, and microservices- Orchestration with Airflow, Celery, and scalable deployment via Docker/Kubernetes- Complex data modeling for machine learning and analytics- Testing, OpenAPI documentation, serialization, and advanced validation- Compatibility with PostgreSQL, MongoDB, AWS, Google CloudMaster Pydantic V2 to build resilient, scalable, and secure applications, optimizing integrations, data automation, and performance in modern environments.pydantic, fastapi, sqlalchemy, pandas, airflow, kafka, celery, docker, kubernetes, data validation, automation, api integration, cloud, mlops, dataops.…