Snowflake Data Platform Engineering
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Snowflake Data Platform Engineering
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Author : Richard Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-06-09
Snowflake Data Platform Engineering written by Richard Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-09 with Computers categories.
"Snowflake Data Platform Engineering" "Snowflake Data Platform Engineering" is a comprehensive guide to mastering Snowflake, the modern cloud data platform enabling enterprise-grade analytics and data engineering at scale. This book demystifies Snowflake's foundational multi-cluster architecture, detailing the separation of storage and compute, virtual warehouse optimization, secure data management, and cloud provider-agnostic features. Readers are introduced to robust security frameworks, including encryption, RBAC, and data masking, alongside governance strategies vital for regulatory compliance and data protection. Building on architectural insights, the book systematically explores modern ingestion and integration patterns—from batch and bulk loading to real-time streaming with Snowpipe, effective handling of semi-structured data, and seamless connectivity to external data lakes and third-party ETL tools. In-depth chapters on data modeling, schema evolution, transformation, and lineage equip practitioners to implement advanced analytics solutions with agility and performance, harnessing Snowflake’s capabilities for materialized views, procedural SQL, and automated workflows. Best practices in performance tuning, query optimization, and resource governance are paired with detailed troubleshooting techniques for high-impact and cost-effective solutions. Further, the book addresses mission-critical themes such as high availability, disaster recovery, automation with Infrastructure as Code, and extensibility through APIs, Snowpark, and data marketplace integration. Real-world case studies, industry-specific blueprints, and practical lessons offer guidance for both newcomers and seasoned data engineers. "Snowflake Data Platform Engineering" is an essential resource for unlocking the full power, resilience, and innovation potential of the Snowflake ecosystem in today’s cloud-driven landscape.
Snowflake Data Engineering
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Author : Maja Ferle
language : en
Publisher: Simon and Schuster
Release Date : 2025-01-28
Snowflake Data Engineering written by Maja Ferle and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-28 with Computers categories.
Snowflake Data Engineering guides you skill-by-skill through accomplishing on-the-job data engineering tasks using Snowflake. You’ll start by building your first simple pipeline and then expand it by adding increasingly powerful features, including data governance and security, adding CI/CD into your pipelines, and even augmenting data with generative AI. You’ll be amazed how far you can go in just a few short chapters! --
Data Mesh In Action
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Author : Jacek Majchrzak
language : en
Publisher: Simon and Schuster
Release Date : 2023-03-21
Data Mesh In Action written by Jacek Majchrzak and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-21 with Computers categories.
Revolutionize the way your organization approaches data with a data mesh! This new decentralized architecture outpaces monolithic lakes and warehouses and can work for a company of any size. In Data Mesh in Action you will learn how to: Implement a data mesh in your organization Turn data into a data product Move from your current data architecture to a data mesh Identify data domains, and decompose an organization into smaller, manageable domains Set up the central governance and local governance levels over data Balance responsibilities between the two levels of governance Establish a platform that allows efficient connection of distributed data products and automated governance Data Mesh in Action reveals how this groundbreaking architecture looks for both small startups and large enterprises. You won’t need any new technology—this book shows you how to start implementing a data mesh with flexible processes and organizational change. You’ll explore both an extended case study and multiple real-world examples. As you go, you’ll be expertly guided through discussions around Socio-Technical Architecture and Domain-Driven Design with the goal of building a sleek data-as-a-product system. Plus, dozens of workshop techniques for both in-person and remote meetings help you onboard colleagues and drive a successful transition. About the technology Business increasingly relies on efficiently storing and accessing large volumes of data. The data mesh is a new way to decentralize data management that radically improves security and discoverability. A well-designed data mesh simplifies self-service data consumption and reduces the bottlenecks created by monolithic data architectures. About the book Data Mesh in Action teaches you pragmatic ways to decentralize your data and organize it into an effective data mesh. You’ll start by building a minimum viable data product, which you’ll expand into a self-service data platform, chapter-by-chapter. You’ll love the book’s unique “sliders” that adjust the mesh to meet your specific needs. You’ll also learn processes and leadership techniques that will change the way you and your colleagues think about data. What's inside Decompose an organization into manageable domains Turn data into a data product Set up central and local governance levels Build a fit-for-purpose data platform Improve management, initiation, and support techniques About the reader For data professionals. Requires no specific programming stack or data platform. About the author Jacek Majchrzak is a hands-on lead data architect. Dr. Sven Balnojan manages data products and teams. Dr. Marian Siwiak is a data scientist and a management consultant for IT, scientific, and technical projects. Table of Contents PART 1 FOUNDATIONS 1 The what and why of the data mesh 2 Is a data mesh right for you? 3 Kickstart your data mesh MVP in a month PART 2 THE FOUR PRINCIPLES IN PRACTICE 4 Domain ownership 5 Data as a product 6 Federated computational governance 7 The self-serve data platform PART 3 INFRASTRUCTURE AND TECHNICAL ARCHITECTURE 8 Comparing self-serve data platforms 9 Solution architecture design
Computer And Information Technology
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Author : Prasad Yarlagadda
language : en
Publisher: Trans Tech Publications Ltd
Release Date : 2014-02-06
Computer And Information Technology written by Prasad Yarlagadda and has been published by Trans Tech Publications Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-06 with Technology & Engineering categories.
Selected, peer reviewed papers from the International Forum on Computer and Information Technology (IFCIT 2013), December 24-25, 2013, Shenzhen, China
Proceedings Of The 1997 International Database Engineering Applications Symposium
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Author : Bipin C. Desai
language : en
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
Release Date : 1997
Proceedings Of The 1997 International Database Engineering Applications Symposium written by Bipin C. Desai and has been published by Institute of Electrical & Electronics Engineers(IEEE) this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Computers categories.
Written for researchers, professors, practitioners, students and other computing professionals, this book covers the 1997 International Database Engineering and Applications Symposium."
Dbt Analytics Engineering Ithome
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Author : 謝秉芳（Karen Hsieh）、黃郁豪（Bruce Huang）、韓衣錦（Michael Han）、羅可涵（Stacy Lo）
language : zh-CN
Publisher: 博碩文化
Release Date : 2024-11-15
Dbt Analytics Engineering Ithome written by 謝秉芳（Karen Hsieh）、黃郁豪（Bruce Huang）、韓衣錦（Michael Han）、羅可涵（Stacy Lo） and has been published by 博碩文化 this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-15 with Computers categories.
♛ 第一本 dbt 繁體中文書 ♛ 資料分析師與工程師必讀的技術及職涯實戰指南 本書改編自第 15 屆 iThome 鐵人賽 AI & Data 組優選系列文章《被 dbt 帶入門的數據工作體驗 30 想》及其團隊夥伴作品。四位作者由不同身份和視角出發，分享如何透過 dbt 實踐 Analytics Engineering（分析工程）。 dbt 是一個以 SQL 為基底的開源資料轉換工具，採用軟體工程原則，如版本控制、測試、模組化，讓資料轉換更可靠且高效。本書將帶你動手建立 dbt 專案，親自體驗其優勢。 Analytics Engineering 則是隨著資料產業演化而發展出的新興領域，介於資料分析和資料工程之間，且和兩者的部分任務重疊。 除技術外，書中也會討論資料文化、如何打造資料團隊，以及資料專業的職涯規劃和發展。無論新手或老手，本書都是能為你提供獨到見解的實用指南。 【重點摘要】 ✦ dbt 由淺入深 dbt Cloud 及 dbt Core 實作應用 ✦ 動手操作 附範例、語法、操作截圖 ✦ 資料分析必備 資料品質及建模最佳實踐 ✦ 打造資料文化 資料團隊現代化經典案例 【目標讀者】 任何工作中使用資料的人。包含： ◆ 參與資料專案的成員，不論你在資料部門，或是支援資料專案的軟體部門。你負責資料轉換成資訊的過程，想嘗試新工具，解決原本資料流程遇到的痛點。 ◆ 在工作上經常使用資料的角色，例如：行銷、Sales、PM、財務、營運人員等。你對資料、報表有好奇心、想知道資料轉換成資訊的過程，並且喜歡動手操作。 【專業推薦】 透過真實案例與深入見解，引導你有效導入 dbt，營造資料驅動環境。無論你是資料處理老手或新手，本書皆提供所需知識與工具，幫助組織進入資料引導決策的未來。 ──── 高嘉良（CL Kao）｜Recce, CEO 這本書涵蓋了打造優秀數據團隊所需的全方位知識，不僅適合技術人員閱讀，也非常適合產品經理、商業分析師等角色參考。 ──── Richard Lee｜TNL Mediagene 技術長 因緣際會被我推坑的 Taipei dbt Meetup 熱血志工群，融合真實經驗，以案例故事呈現 Data 如何貫穿企業，讓你認識 dbt 並一窺 Data Team 的重要定位。 ──── 陳正瑋（艦長）｜DevOps Taiwan Community 志工／前 Organizer
Data Engineering With Dbt
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Author : Roberto Zagni
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-06-30
Data Engineering With Dbt written by Roberto Zagni and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-30 with Computers categories.
Use easy-to-apply patterns in SQL and Python to adopt modern analytics engineering to build agile platforms with dbt that are well-tested and simple to extend and run Purchase of the print or Kindle book includes a free PDF eBook Key Features Build a solid dbt base and learn data modeling and the modern data stack to become an analytics engineer Build automated and reliable pipelines to deploy, test, run, and monitor ELTs with dbt Cloud Guided dbt + Snowflake project to build a pattern-based architecture that delivers reliable datasets Book Descriptiondbt Cloud helps professional analytics engineers automate the application of powerful and proven patterns to transform data from ingestion to delivery, enabling real DataOps. This book begins by introducing you to dbt and its role in the data stack, along with how it uses simple SQL to build your data platform, helping you and your team work better together. You’ll find out how to leverage data modeling, data quality, master data management, and more to build a simple-to-understand and future-proof solution. As you advance, you’ll explore the modern data stack, understand how data-related careers are changing, and see how dbt enables this transition into the emerging role of an analytics engineer. The chapters help you build a sample project using the free version of dbt Cloud, Snowflake, and GitHub to create a professional DevOps setup with continuous integration, automated deployment, ELT run, scheduling, and monitoring, solving practical cases you encounter in your daily work. By the end of this dbt book, you’ll be able to build an end-to-end pragmatic data platform by ingesting data exported from your source systems, coding the needed transformations, including master data and the desired business rules, and building well-formed dimensional models or wide tables that’ll enable you to build reports with the BI tool of your choice.What you will learn Create a dbt Cloud account and understand the ELT workflow Combine Snowflake and dbt for building modern data engineering pipelines Use SQL to transform raw data into usable data, and test its accuracy Write dbt macros and use Jinja to apply software engineering principles Test data and transformations to ensure reliability and data quality Build a lightweight pragmatic data platform using proven patterns Write easy-to-maintain idempotent code using dbt materialization Who this book is for This book is for data engineers, analytics engineers, BI professionals, and data analysts who want to learn how to build simple, futureproof, and maintainable data platforms in an agile way. Project managers, data team managers, and decision makers looking to understand the importance of building a data platform and foster a culture of high-performing data teams will also find this book useful. Basic knowledge of SQL and data modeling will help you get the most out of the many layers of this book. The book also includes primers on many data-related subjects to help juniors get started.
Snowflake Snowpro Advanced Data Engineer Dea C02 Certification Practice 300 Questions Answer
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Author : Rashmi Shah
language : en
Publisher: QuickTechie.com | A career growth machine
Release Date :
Snowflake Snowpro Advanced Data Engineer Dea C02 Certification Practice 300 Questions Answer written by Rashmi Shah and has been published by QuickTechie.com | A career growth machine this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
The Advanced Snowflake Data Engineer: A Comprehensive Guide to DEA-C02 Certification, available through QuickTechie.com, is the definitive resource for data professionals seeking to validate their advanced knowledge and skills in applying comprehensive data engineering principles using Snowflake. This book is specifically tailored for individuals with two or more years of hands-on experience as a Data Engineer in a production environment, building upon the foundational expertise gained from the SnowPro Core Certification. This comprehensive guide takes readers beyond the basics, diving deep into the intricate world of advanced data engineering on the Snowflake Data Cloud. It equips professionals to architect, implement, and manage robust, scalable, and highly performant data pipelines that span various data sources and destinations. From sourcing data from diverse origins like Data Lakes, APIs, and on-premises systems, to designing end-to-end near real-time streams and evaluating complex performance metrics, this book provides the practical knowledge and strategic insights essential for a senior Snowflake Data Engineer. Key Learning Objectives and Comprehensive Coverage: The book's content is meticulously aligned with the SnowPro® Advanced: Data Engineer Certification (DEA-C02) exam, ensuring comprehensive and targeted preparation across all critical domains: Data Movement (26%): Covers mastering techniques for sourcing data from a wide array of origins, including cloud-based Data Lakes (S3, ADLS, GCS), various APIs, and traditional on-premises data sources into Snowflake. It delves into external stage concepts, designing and implementing continuous data ingestion with Snowpipe, utilizing Snowflake connectors and integrations, applying data loading best practices for various file formats (Parquet, ORC, JSON, Avro, XML), error handling, data validation during ingest, and understanding data replication for cross-cloud or cross-region data movement. Performance Optimization (21%): Develops expertise in Virtual Warehouse optimization, including sizing, scaling policies, multi-cluster warehouses, and workload management for data engineering tasks. It focuses on query performance tuning by utilizing Query Profile, optimizing SQL queries, understanding query history and execution plans, comprehending Snowflake's storage architecture with Micro-partitions and Clustering, leveraging the Search Optimization Service for point lookups, and designing and using Materialized Views for query acceleration. Storage and Data Protection (14%): Provides insights into Snowflake's storage layer, data compression, and cost implications. It details utilizing data retention policies for data recovery and protection through Time Travel and Fail-safe, understanding data encryption at rest and in transit, and implementing secure data sharing for consumers within and outside an organization. Data Governance (14%): Explores designing and implementing robust Role-Based Access Control (RBAC) for data engineering roles, managing object access and security through row access policies, dynamic data masking, and external functions for tokenization/obfuscation. It also covers managing and monitoring credit consumption with Resource Monitors and implementing data classification and tagging for governance and compliance. Data Transformation (25%): Addresses designing and implementing various ELT/ETL patterns in Snowflake. It covers advanced SQL constructs, window functions, User-Defined Functions (UDFs), User-Defined Table Functions (UDTFs), leveraging Snowpark with Python (or other languages) for complex, programmatic transformations, orchestrating complex data pipelines with Stored Procedures, and scheduling with Tasks. Additionally, it focuses on implementing data quality checks and validation rules within pipelines. Who This Book Is For: This book is specifically designed for the SnowPro® Advanced: Data Engineer candidate and other professionals, including: Experienced Data Engineers: Those responsible for designing, building, and maintaining complex data pipelines, ETL/ELT processes, and data integration solutions on Snowflake. Data Architects: Individuals involved in designing enterprise-level data platforms on Snowflake, requiring a deep understanding of data movement, storage, and transformation best practices. Cloud Engineers/DevOps Specialists: Professionals who manage the operational aspects and infrastructure of Snowflake data solutions. Professionals aiming for the SnowPro® Advanced: Data Engineer Certification (DEA-C02): This book serves as an essential guide for in-depth preparation. Individuals with 2 or more years of hands-on experience as a Data Engineer in a production environment. Exam Details and How This Book Prepares You: The book's structure and content are precisely mapped to the SnowPro® Advanced: Data Engineer Certification (DEA-C02) exam, ensuring comprehensive and targeted preparation. It covers all relevant topics with conceptual explanations, practical examples, and potentially practice questions integrated within chapters to reinforce understanding. The guide addresses various question types, including Multiple Select, Multiple Choice, and Interactive questions, through detailed explanations of concepts and their practical applications. It prepares candidates for the 115-minute time limit and aims to equip them with the knowledge required to confidently achieve and exceed the 750+ passing score (scaled from 0-1000). The content is solely in English and assumes the reader is SnowPro Core Certified, building directly on that foundational knowledge with advanced data engineering concepts. Key Features of This Book: This essential guide, available through QuickTechie.com, offers several key features: Comprehensive Coverage: Aligned meticulously with the DEA-C02 exam blueprint, ensuring no critical topic is left out. Practical Examples and Use Cases: Numerous real-world scenarios and code examples demonstrate the application of data engineering principles in Snowflake. Best Practices for Production Systems: Provides insights and recommendations for building scalable, robust, and maintainable data pipelines in production environments. Focus on Performance and Optimization: Dedicated sections and tips for evaluating, troubleshooting, and enhancing the performance of Snowflake data engineering workloads. Strategic Guidance: Beyond technical details, the book provides strategic advice on designing end-to-end data solutions. This book, presented by QuickTechie.com, is an essential investment for any data engineer serious about mastering Snowflake and achieving the prestigious SnowPro® Advanced: Data Engineer Certification, solidifying their role as a leader in modern cloud data engineering.
Handbook Of Data Management 2nd Edition
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Author : Bhavani Thuraisingham
language : en
Publisher: Auerbach Publications
Release Date : 1997-12-16
Handbook Of Data Management 2nd Edition written by Bhavani Thuraisingham and has been published by Auerbach Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-12-16 with Business & Economics categories.
Data Cloud
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Author : Vaughn Matuszek
language : en
Publisher: Independently Published
Release Date : 2021-03
Data Cloud written by Vaughn Matuszek and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03 with categories.
Over 400 million SaaS data sets remained siloed globally, isolated in cloud data storage and on-premise data centers. The Data Cloud eliminates these silos, allowing you to seamlessly unify, analyze, share, and even monetize your data This Data Cloud Information book will give you an understanding of what we've built to help you create a business with data as its most robust foundation. Snowflake delivers the Data Cloud -- a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance. Inside the Data Cloud, organizations unite their siloes of data, easily discover and securely share governed data, and execute diverse analytic workloads. Wherever data or users live, Snowflake delivers a single and seamless experience across multiple public clouds, helping power the data economy. Snowflake's platform is the engine that powers and provides access to the Data Cloud, creating a solution for data warehousing, data lakes, data engineering, data science, data application development, and data sharing.