Data engineering (26 Ergebnisse)
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Sprache: Englisch
Verlag: Independently Published Apr 2026, 2026
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Taschenbuch. Zustand: Neu. Neuware - Stop Learning. Start Building. Become Job-Ready in Data Engineering.Data engineering is one of the fastest-growing careers in tech - but most resources teach theory, not real-world skills. This book is different.Instead of long explanations, you will build 12 complete, real-world data enginee…ring projects using Python and SQL. Every project simulates a genuine business scenario, follows a professional structure, and gives you something tangible to show employers.What You Will BuildWorking through this book, you will create end-to-end data pipelines including CSV and file-based ingestion systems, API data pipelines with error handling, data cleaning and validation workflows, JSON to SQL transformation pipelines, a star schema data warehouse, reporting data marts for analytics, e-commerce and log processing pipelines, incremental loading systems, fault-tolerant and reliable pipelines, performance-optimized data workflows, and automated testing for data quality.Learn by Doing - Not Just ReadingEvery project follows the same professional structure: business problem, pipeline architecture, step-by-step implementation, working code, expected output, resume-ready bullet points, and interview questions. You won't just understand the concepts - you will know how to apply them.Become Job-ReadyThis book is designed to help you build a strong GitHub portfolio, write powerful resume project points, answer real data engineering interview questions with confidence, and develop the end-to-end thinking that employers are looking for. By the last page, you will have practical, demonstrable experience that sets you apart from other candidates.Who This Book Is ForThis book is written for beginners starting a career in data engineering, developers and software engineers transitioning into data roles, QA and automation engineers looking to upskill, and anyone who learns best through hands-on, project-based work. Basic knowledge of Python and SQL is all you need to get started.Why This Book Is DifferentNo unnecessary theory. No long academic explanations. No abstract concepts disconnected from practice. Only real projects, practical learning, and job-focused skills built through doing.Your Learning PathStart with simple file-based pipelines. Progress through API ingestion, data warehousing, and analytics systems. Finish with production-ready patterns including incremental loading, fault tolerance, performance optimization, and automated testing.By the End of This Book, You Will Have: Built 12 real-world data engineering projects. Developed end-to-end pipeline thinking. Created a job-ready portfolio. And gained the confidence to apply for data engineering roles - not someday, but now.
Sprache: Englisch
Verlag: Independently Published Jun 2026, 2026
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Taschenbuch. Zustand: Neu. Neuware.
Sprache: Englisch
Verlag: Independently Published Jun 2026, 2026
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Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Taschenbuch. Zustand: Neu. Neuware - Walk into your data engineering interview ready for every round.Most people don't fail data engineering interviews because they lack skill. They fail because no one showed them what each round is really testing, or how to answer under pressure. This book fixes that. Data Engineering Interview… Mastery & System Design is a complete, end-to-end preparation guide that follows the real shape of a modern DE interview, from SQL and Python fundamentals to the senior system design rounds where the best offers are won and lost. What you'll master: - SQL interview problems: joins, window functions, CTEs, indexing, and query optimization- Python for data engineers: generators, decorators, OOP, concurrency, and 'what does this print ' questions- Warehousing & modeling: OLTP vs OLAP, star and snowflake schemas, slowly changing dimensions, and Data Vault- Lakes & lakehouses: Delta/Iceberg, ACID on files, schema evolution, and the medallion architecture- Big data & cloud: Spark internals, shuffles and data skew, Kafka delivery guarantees, AWS, and Airflow- System design: a repeatable framework plus four full designs - Batch ETL, Real-Time Streaming, Data Lakehouse, and a 5-billion-events/day Clickstream platform- Career mastery: resume, LinkedIn, portfolio projects, mock interviews, and salary negotiationWhy this book is different : Every key question follows a proven 8-part format - Question, Why Interviewers Ask, Simple Answer, Detailed Explanation, Real Business Example, Common Mistakes, Follow-up Questions, and Difficulty - so you don't just memorize an answer, you understand it and handle the follow-ups that actually decide the outcome. You also get 285+ rapid-fire questions in the appendices (Top 100 SQL, Top 50 Python, Top 50 Spark, Top 30 Kafka, Top 30 AWS, Top 25 System Design) and quick-reference cheat sheets for last-minute revision the night before. Who it's for : Freshers and career switchers, ETL/QA/analyst professionals moving into data engineering, software engineers crossing over, and experienced engineers targeting senior roles. Nobody is talked down to, and nothing is padded. This isn't a list of facts to memorize. It teaches you to think the way a data engineer thinks: clarify the problem, reason about how systems behave and fail, weigh the trade-offs, and say it all clearly out loud. The work ahead is real, and it's learnable. Scroll up, grab your copy, and start preparing the way the engineers who get hired do.
Sprache: Englisch
Verlag: Independently Published Jun 2026, 2026
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Taschenbuch. Zustand: Neu. Neuware.
Sprache: Englisch
Verlag: Independently Published Mai 2026, 2026
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Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Taschenbuch. Zustand: Neu. Neuware - Build production-grade data engineering systems used in modern cloud environments - not just beginner ETL scripts.As organizations continue shifting toward cloud-native analytics, real-time processing, and distributed data platforms, the demand for skilled data engineers has never been higher…. Yet most learning resources still focus on isolated concepts rather than showing how production systems are actually designed, built, and operated at scale.This book changes that.Advanced Data Engineering Projects with Python, SQL & Cloud is a hands-on, project-based guide that takes you beyond the basics and develops the practical engineering skills that modern data engineering roles demand. Every chapter is built around realistic production scenarios - not toy examples - using technologies widely adopted across the industry.What you will learn - Build scalable ETL and ELT pipelines using Python and SQL- Process large datasets with Apache Spark and PySpark- Design real-time streaming systems using Apache Kafka- Orchestrate complex workflows with Apache Airflow- Implement cloud-native architectures using AWS S3, Glue, Redshift, and Lambda- Build distributed analytics warehouses with performance-optimized table design- Create Bronze, Silver, and Gold Medallion data lakehouse architectures- Implement Change Data Capture and incremental loading strategies- Monitor pipeline health with logging, metrics, and automated alerting- Build automated data quality validation frameworks and production quality gates- Optimize distributed systems for scalability, performance, and cloud cost efficiency- Design complete enterprise-level data platforms from requirements to deploymentWho this book is for This book is written for aspiring data engineers building their first serious portfolio, ETL developers transitioning into cloud and big data platforms, backend engineers exploring distributed data systems, analytics engineers deepening their technical foundation, and professionals preparing for mid-level or senior data engineering interviews.Why this book is different Most technical books teach tools in isolation. This book teaches how modern systems work together - and more importantly, how to think like an engineer who builds them.You will learn not only how to use these technologies, but how to design for scalability, build for reliability, optimise for performance, and solve the kinds of problems that appear in real production environments at 2 a.m. when something breaks.By the end of this book, you will have a collection of advanced portfolio-quality projects, a strong foundation in enterprise architecture patterns, interview preparation material covering system design and production troubleshooting, and the practical engineering mindset that separates strong candidates in today's competitive data engineering job market.
Sprache: Englisch
Verlag: Independently Published Jul 2026, 2026
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Taschenbuch. Zustand: Neu. Neuware.
Sprache: Englisch
Verlag: Mercer Education Press Mai 2026, 2026
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Taschenbuch. Zustand: Neu. Neuware - SQL for Data Engineering - ETL, Warehousing, Cloud Platforms & AI WorkflowsMost SQL books teach you to write queries. This one teaches you to build systems.If you know basic SQL but struggle to apply it in production environments, or you are preparing for data engineering interviews and want…experience beyond simple SELECT statements, this book was written for you.SQL for Data Engineering bridges the gap between tutorial SQL and the skills that data engineering roles actually demand - ETL pipelines, warehouse design, query optimization, and the architectural thinking that separates engineers who build reliable data systems from those who only query them.What you will learn: - Advanced querying - joins, CTEs, subqueries, window functions, and analytical SQL patterns- Data transformation - cleaning, standardisation, safe casting, and deduplication techniques- ETL architecture - incremental loading, staging patterns, Slowly Changing Dimensions, and idempotent pipeline design- Warehouse design - star schemas, dimensional modelling, partitioning, indexing, and materialised views- Performance optimisation - EXPLAIN ANALYZE, execution plans, query tuning, and production-grade optimisation- Semi-structured data - JSON and JSONB processing, schema drift handling, and event pipeline patterns- Cloud platforms - Snowflake, BigQuery, Redshift, and Databricks with practical SQL for each- AI workflows - prompt engineering for SQL tasks, AI-assisted debugging, and the risks of generated codeFour industry projects you will build: - E-Commerce Analytics Warehouse- SaaS Subscription Metrics Platform- Banking Transaction Fraud Monitoring System- Food Delivery ETL and Operations PipelineEach project covers a realistic business problem, complete ETL pipeline, warehouse schema, KPI queries, and interview preparation - designed to go directly into your portfolio.You also get: - Integrated interview Q&A in every chapter drawn from real hiring panels- Resume bullet points after every chapter and project- A complete career roadmap for aspiring data engineers- Appendices covering SQL functions, data types, troubleshooting, glossary, and a tool landscape guide.
Sprache: Englisch
Verlag: Independently Published Jun 2026, 2026
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Taschenbuch. Zustand: Neu. Neuware - Master Data Engineering System Design - From Fundamentals to Real-World Production SystemsSystem design interviews trip up data engineers who are strong on execution but have never been shown how to structure a complete architectural answer. This book fixes that gap - and gives you the produc…tion knowledge to back it up.What you will learn: - How to approach any system design question using a six-step framework that works every time- The fundamentals of distributed systems: CAP theorem, replication, partitioning, consistency models, and message delivery guarantees- How to design batch pipelines, streaming pipelines, and CDC architectures from scratch- Modern data architectures: data warehouse (Kimball, Inmon, Medallion), data lake (Bronze/Silver/Gold), and lakehouse (Delta Lake, Iceberg, Hudi)- AWS, Azure, and GCP data services - and how to combine them into production-ready platforms- Five complete real-world case studies: Uber GPS platform, Netflix analytics, e-commerce data platform, real-time fraud detection, and an AI/ML platform with feature store and RAG- 20 most-asked system design interview questions with full answers, architectures, and common mistakes- Where data engineering is heading: AI-assisted pipelines, the real-time lakehouse, vector databases, and Data MeshWho this book is for: - Junior to mid-level data engineers preparing for system design interviews- Data engineering beginners who want to understand how components fit together into real systems- College students and freshers entering the data engineering field- Professionals moving from analytics or software engineering into data engineeringEvery chapter follows a consistent structure: core concepts, real-world examples, architecture diagrams, common mistakes, and interview questions. The writing is practitioner-level - no academic jargon, short paragraphs, and honest trade-off discussions throughout.This is a standalone book. No prior system design experience required - only a basic familiarity with SQL and Python.Topics covered: system design fundamentals - scalability - distributed systems - OLTP vs OLAP - data modeling - star schema - SCD Type 2 - storage formats - Parquet - Avro - Delta Lake - Apache Iceberg - batch pipelines - Airflow - streaming pipelines - Apache Kafka - Flink - CDC - Debezium - data warehouse - data lake - lakehouse - AWS - Azure - GCP - Redshift - Snowflake - BigQuery - feature store - RAG - vector databases - fraud detection - A/B testing - interview framework.
