Qa testing (18 resultados)
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Serie: Libro 3 de 6 - QA Testing
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Paperback. Condición: new. Paperback. Take Your ETL Testing Skills to the Cloud, at Scale, and into the Age of AIModern ETL Testing with AI - Volume 2 picks up where foundational ETL testing leaves off. If you can already validate a row count, compare source and target, and write a solid Python assertion, this book takes you the… rest of the way: into cloud data warehouses, data lakes, Spark, Kafka, CDC pipelines, enterprise CI/CD, and the growing role of AI agents in building and maintaining test coverage.Written for testers, data engineers, and QA professionals now responsible for pipelines spanning multiple clouds, near-real-time streams, and audit-grade reporting.What's InsideCloud Data Platforms: Test Snowflake, Redshift, BigQuery, and Synapse for clustering drift, materialized view staleness, and cost-aware validation using zero-copy cloning and time travel.Data Lakes & Storage: Catch the small-file problem, validate Delta Lake/Iceberg/Hudi schema enforcement, and test object storage access control.Orchestration: Build three-layer test suites for Airflow DAGs, catch trigger-rule misconfigurations, and test Glue, Data Factory, and Dataflow pipelines.Big Data & Streaming: Diagnose data skew in Spark, test Kafka delivery guarantees and idempotent consumers, and validate CDC pipelines for snapshot gaps, tombstones, and out-of-order events.Enterprise Practices: Manage test data with masking and synthetic generation, enforce data contracts, build observability, design CI/CD with canary deployments, and performance-test at scale.AI-Powered Testing: Use AI agents to generate test coverage across hundreds of tables with mandatory human review, apply LLM-assisted triage to correlate anomalies, and build a governed, audited AI-augmented framework.Real Enterprise Case Studies: Three full case studies-a multi-cloud retail platform, a real-time banking fraud detection system, and a HIPAA-governed healthcare data lake-show how these techniques combine under real business and regulatory pressure.Interview Preparation: A large bank of interview questions across beginner through lead/architecture levels, covering cloud, Spark, Kafka, Snowflake, dbt, Airflow, CI/CD, and AI-specific topics, plus four complete mock interview transcripts with evaluator commentary.Why This Book Is DifferentEvery chapter follows the same discipline: explain why the problem matters before showing how to solve it, ground every technique in runnable SQL, Python, PySpark, and YAML code, and close with testing checkpoints you can use as a QA checklist. Real-world examples throughout-a skewed join that broke a telecom billing pipeline, a silent delete gap in an e-commerce inventory feed, a currency conversion bug caught by a canary deployment-show how these techniques catch real, costly defects before they reach production.The AI chapters take a disciplined approach: agents accelerate test generation and anomaly triage, but every consequential decision stays under human review, with clear guardrails against AI quietly locking in bugs.Who This Book Is ForETL testers and QA engineers moving from foundational to cloud-scale, enterprise-scale testingData engineers building reliable, well-tested pipelines on AWS, Azure, or GCPSenior and lead engineers preparing for cloud, big data, or architecture-level interviewsTeams evaluating how to responsibly adopt AI-assisted testing and observabilityWhether you're preparing for your next interview, building a testing practice for a growing data platform, or leading a team through the shift to cloud-native, AI-augmented data engineering, this volume gives you practical, tested, immediately usable techniques to get there. T Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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EUR 18,39
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Paperback. Condición: new. Paperback. Master API Automation Testing with Python - and Become Job-ReadyAre you ready to move beyond manual testing and build automation skills that companies are actively hiring for? Do you want to write real API tests, build a professional framework, and walk into interviews with something concret…e to show?This book is your complete, practical guide to making that happen.API Automation Testing with Python: Requests, PyTest, and AI-Powered Testing takes you from foundational understanding to real-world application - step by step, without assuming prior automation experience. Every concept is grounded in what you will actually do on the job. What You Will Learn?Write API tests using Python, Requests, and PyTestTest GET, POST, PUT, and DELETE operations with full validationHandle authentication flows and perform security testingBuild a complete, professional API automation frameworkIntegrate your test suite into a CI/CD pipelineUse AI tools to generate test cases and improve efficiencyPrepare confidently for QA and automation interviewsA Real Project, Built by YouThis book includes a complete end-to-end API testing project - structured the way professional teams build theirs, with real endpoints, CRUD operations, CI/CD integration, and reporting. Push it to GitHub and present it in any interview with confidence. AI-Powered Testing - Built Into the CurriculumYou will learn to use AI to generate test scenarios, write automation code faster, and diagnose failures more efficiently - while developing the critical judgment to validate everything AI produces.AI is not replacing testers. It is raising the bar for what skilled testers can accomplish. This book shows you how to clear it.Who This Book Is For?Beginners entering QA, manual testers transitioning to automation, students preparing for IT careers, and professionals adding Python automation to their skill set. No prior automation experience required.Start building your skills. Start building your career. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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EUR 18,51
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 18,00
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Taschenbuch. Condición: Neu. Neuware - Modern ETL Testing with AISQL, Python & AI for Real-World Data ValidationModern ETL Testing Series - Volume 1Are you looking to start a career in ETL Testing or upgrade your skills with SQL, Python, and AI Do you find traditional ETL books too theoretical and difficult to follow Modern ETL…Testing with AI - Volume 1 is a beginner-friendly, practical guide designed to help you learn ETL testing step by step using simple language, real-world examples, and hands-on projects.Instead of overwhelming you with theory, this book focuses on what ETL testers actually do in real projects-validating data, writing SQL queries, automating checks with Python, and using AI tools to work faster and smarter. What You'll LearnUnderstand ETL architecture and data flow from source systems to data warehousesMaster SQL fundamentals for ETL testing, including: - SELECT, WHERE, GROUP BY, ORDER BY- INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL OUTER JOIN- Aggregations and reconciliation queries- Practical data validation techniquesLearn Python for ETL testing: - pandas basics- Database connectivity- Automated validation scripts- PASS/FAIL reportingExplore Data Warehouse concepts: - Fact and Dimension tables- Star Schema- Slowly Changing Dimensions (SCD)Perform common ETL validations: - Row count validation- Null value validation- Duplicate record checks- Aggregate validation- Source-to-target reconciliationDiscover how AI can assist ETL testers: - Generate SQL queries- Create Python scripts- Write test cases- Analyze validation failures- Use ChatGPT, Claude, and Gemini effectivelyUnderstand modern Cloud ETL architecture and industry trendsBuild confidence with two real-world projects: - Banking ETL Testing Project- Insurance ETL Testing ProjectWhy This Book Is Different- Unlike many ETL books that focus heavily on concepts, this book emphasizes: - Simple explanations with minimal jargon- Practical SQL and Python examples- AI-assisted testing techniques- Real enterprise scenarios- Interview-oriented insights- Beginner to intermediate learning pathWho Should Read This Book This book is ideal for: - Beginners starting their ETL Testing journey- QA Engineers transitioning to Data Testing- Manual Testers learning automation- Automation Testers exploring ETL and Data Quality- Freshers preparing for ETL Testing interviews- Professionals interested in AI-powered testingModern ETL Testing SeriesThis book is Volume 1 of the Modern ETL Testing Series, a practical series that teaches ETL testing using modern technologies and real-world examples.Upcoming volumes cover: - Advanced ETL Testing with AI- Cloud ETL Testing with AI- Python Automation for ETL Testing- CDC, SCD & Incremental Load Testing- Snowflake, Databricks & Modern Data Pipelines.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 22,00
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Taschenbuch. Condición: Neu. Neuware - Master API Automation Testing with Python - and Become Job-ReadyAre you ready to move beyond manual testing and build automation skills that companies are actively hiring for Do you want to write real API tests, build a professional framework, and walk into interviews with something concret…e to show This book is your complete, practical guide to making that happen.API Automation Testing with Python: Requests, PyTest, and AI-Powered Testing takes you from foundational understanding to real-world application - step by step, without assuming prior automation experience. Every concept is grounded in what you will actually do on the job. What You Will Learn - Write API tests using Python, Requests, and PyTest- Test GET, POST, PUT, and DELETE operations with full validation- Handle authentication flows and perform security testing- Build a complete, professional API automation framework- Integrate your test suite into a CI/CD pipeline- Use AI tools to generate test cases and improve efficiency- Prepare confidently for QA and automation interviewsA Real Project, Built by You>AI-Powered Testing - Built Into the CurriculumYou will learn to use AI to generate test scenarios, write automation code faster, and diagnose failures more efficiently - while developing the critical judgment to validate everything AI produces.AI is not replacing testers. It is raising the bar for what skilled testers can accomplish. This book shows you how to clear it.Who This Book Is For Beginners entering QA, manual testers transitioning to automation, students preparing for IT careers, and professionals adding Python automation to their skill set. No prior automation experience required.Start building your skills. Start building your career.
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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EUR 23,80
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Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
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EUR 19,82
Envío por EUR 43,19Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: new. Paperback. Modern ETL Testing with AISQL, Python & AI for Real-World Data ValidationModern ETL Testing Series - Volume 1Are you looking to start a career in ETL Testing or upgrade your skills with SQL, Python, and AI?Do you find traditional ETL books too theoretical and difficult to follow?Modern ETL T…esting with AI - Volume 1 is a beginner-friendly, practical guide designed to help you learn ETL testing step by step using simple language, real-world examples, and hands-on projects.Instead of overwhelming you with theory, this book focuses on what ETL testers actually do in real projects-validating data, writing SQL queries, automating checks with Python, and using AI tools to work faster and smarter. What You'll LearnUnderstand ETL architecture and data flow from source systems to data warehousesMaster SQL fundamentals for ETL testing, including: SELECT, WHERE, GROUP BY, ORDER BYINNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL OUTER JOINAggregations and reconciliation queriesPractical data validation techniquesLearn Python for ETL testing: pandas basicsDatabase connectivityAutomated validation scriptsPASS/FAIL reportingExplore Data Warehouse concepts: Fact and Dimension tablesStar SchemaSlowly Changing Dimensions (SCD)Perform common ETL validations: Row count validationNull value validationDuplicate record checksAggregate validationSource-to-target reconciliationDiscover how AI can assist ETL testers: Generate SQL queriesCreate Python scriptsWrite test casesAnalyze validation failuresUse ChatGPT, Claude, and Gemini effectivelyUnderstand modern Cloud ETL architecture and industry trendsBuild confidence with two real-world projects: Banking ETL Testing ProjectInsurance ETL Testing ProjectWhy This Book Is DifferentUnlike many ETL books that focus heavily on concepts, this book emphasizes: Simple explanations with minimal jargonPractical SQL and Python examplesAI-assisted testing techniquesReal enterprise scenariosInterview-oriented insightsBeginner to intermediate learning pathWho Should Read This Book?This book is ideal for: Beginners starting their ETL Testing journeyQA Engineers transitioning to Data TestingManual Testers learning automationAutomation Testers exploring ETL and Data QualityFreshers preparing for ETL Testing interviewsProfessionals interested in AI-powered testingModern ETL Testing SeriesThis book is Volume 1 of the Modern ETL Testing Series, a practical series that teaches ETL testing using modern technologies and real-world examples.Upcoming volumes cover: Advanced ETL Testing with AICloud ETL Testing with AIPython Automation for ETL TestingCDC, SCD & Incremental Load TestingSnowflake, Databricks & Modern Data Pipelines This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
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EUR 22,23
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Paperback. Condición: new. Paperback. Master API Automation Testing with Python - and Become Job-ReadyAre you ready to move beyond manual testing and build automation skills that companies are actively hiring for? Do you want to write real API tests, build a professional framework, and walk into interviews with something concret…e to show?This book is your complete, practical guide to making that happen.API Automation Testing with Python: Requests, PyTest, and AI-Powered Testing takes you from foundational understanding to real-world application - step by step, without assuming prior automation experience. Every concept is grounded in what you will actually do on the job. What You Will Learn?Write API tests using Python, Requests, and PyTestTest GET, POST, PUT, and DELETE operations with full validationHandle authentication flows and perform security testingBuild a complete, professional API automation frameworkIntegrate your test suite into a CI/CD pipelineUse AI tools to generate test cases and improve efficiencyPrepare confidently for QA and automation interviewsA Real Project, Built by YouThis book includes a complete end-to-end API testing project - structured the way professional teams build theirs, with real endpoints, CRUD operations, CI/CD integration, and reporting. Push it to GitHub and present it in any interview with confidence. AI-Powered Testing - Built Into the CurriculumYou will learn to use AI to generate test scenarios, write automation code faster, and diagnose failures more efficiently - while developing the critical judgment to validate everything AI produces.AI is not replacing testers. It is raising the bar for what skilled testers can accomplish. This book shows you how to clear it.Who This Book Is For?Beginners entering QA, manual testers transitioning to automation, students preparing for IT careers, and professionals adding Python automation to their skill set. No prior automation experience required.Start building your skills. Start building your career. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
