Fivetran Data Integration Essentials
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Fivetran Data Integration Essentials
"Fivetran Data Integration Essentials" "Fivetran Data Integration Essentials" is the definitive guide for professionals seeking to modernize, automate, and optimize their organization’s data movement and analytics capabilities. The book opens by grounding readers in the evolution from traditional ETL to contemporary ELT paradigms, highlighting the unique challenges of today’s distributed architectures and the pivotal role that automated data pipelines play in overcoming them. Comprehensive coverage is given to the business and technical criteria that underpin successful Fivetran deployments, including nuanced cost, performance, and compliance considerations essential for both IT and business stakeholders. Building on this foundation, the book delivers an in-depth exploration of Fivetran’s technical architecture. Readers gain a granular understanding of connector lifecycles, internal workflows, change data capture techniques, and robust security models. Practical chapters detail how to integrate diverse source systems—from SQL and NoSQL databases to SaaS platforms—into cloud warehouses and lakes, while providing strategies for custom connector development, schema management, and high-throughput data integration at scale. The interplay between operational automation, resource optimization, and high-availability design is methodically unpacked, guiding architects and engineers in building resilient, future-proof data pipelines. Beyond implementation, "Fivetran Data Integration Essentials" addresses the critical topics of data quality, governance, platform interoperability, and incident response. Readers will find proven methods for automated validation, regulatory compliance, metadata management, and lineage tracking—ensuring both data trust and auditability. The final chapters chart the course for the next generation of data integration, detailing emerging trends such as real-time streaming, AI-driven optimization, serverless architectures, data mesh principles, and the open-source connector ecosystem. This book is an essential resource for data engineers, architects, and analytics leaders aiming to maximize the value and reliability of their cloud data infrastructure with Fivetran.
Data Quality Fundamentals
Do your product dashboards look funky? Are your quarterly reports stale? Is the data set you're using broken or just plain wrong? These problems affect almost every team, yet they're usually addressed on an ad hoc basis and in a reactive manner. If you answered yes to these questions, this book is for you. Many data engineering teams today face the "good pipelines, bad data" problem. It doesn't matter how advanced your data infrastructure is if the data you're piping is bad. In this book, Barr Moses, Lior Gavish, and Molly Vorwerck, from the data observability company Monte Carlo, explain how to tackle data quality and trust at scale by leveraging best practices and technologies used by some of the world's most innovative companies. Build more trustworthy and reliable data pipelines Write scripts to make data checks and identify broken pipelines with data observability Learn how to set and maintain data SLAs, SLIs, and SLOs Develop and lead data quality initiatives at your company Learn how to treat data services and systems with the diligence of production software Automate data lineage graphs across your data ecosystem Build anomaly detectors for your critical data assets
Essential Solutions Architect’s Handbook
Author: Bikramjit Debnath
language: en
Publisher: BPB Publications
Release Date: 2025-04-30
DESCRIPTION In an era where cloud computing, AI, and automation are reshaping industries, this book offers a comprehensive guide for IT professionals seeking to master modern software architecture. It will help bridge the gap between technical expertise and strategic leadership, empowering developers and mid-career professionals to stay ahead in an AI-driven, cloud-first world. Structured into six categories, this book covers key areas such as cloud foundations and migration, modern application development, and AI and advanced technologies. Readers will learn strategies for seamless cloud migration, microservices, serverless computing, and real-time data processing. This book will also provide insights into AI architecture, MLOps, and cloud data warehousing. The book’s focus on infrastructure automation, observability, and FinOps ensures operational efficiency while preparing you for future technological trends like hybrid/multi-cloud strategies, quantum computing, and sustainable IT practices. After reading this book, readers will have gained practical skills in cloud architecture, AI deployment, and data-driven decision-making. With strategic insights and industry best practices, they will be well-equipped to take on leadership roles such as solution architect, enterprise architect, or CTO, driving innovation and shaping the future of technology in their organizations. WHAT YOU WILL LEARN ● Understand solution architecture principles and design scalable solutions. ● Learn cloud migration strategies, including data center and application assessments. ● Explore modern application design practices like microservices and serverless. ● Master data management, governance, and real-time data processing techniques. ● Gain insights into generative AI, AI operationalization, and MLOps. ● Automate infrastructure with IaC, observability, and site reliability engineering. WHO THIS BOOK IS FOR This book is designed for experienced cloud engineers, cloud developers, systems administrators, and solutions architects who aim to expand their expertise toward a CTO-level understanding. It is perfect for professionals with intermediate to advanced knowledge of cloud technologies, systems architecture, and programming, seeking to elevate their strategic and technical skills. TABLE OF CONTENTS 1. Introduction to Solution Architecture 2. Cloud Migration Essentials 3. Operational Excellence in Cloud 4. Modern Application Architecture 5. Development Practices and Tools 6. Data Architecture and Processing 7. Data Strategy and Governance 8. Advanced Analytics 9. Generative AI and Machine Learning 10. Automation and Infra Management 11. FinOps Foundations 12. Security, Privacy, and Ethics 13. Innovation and Future Technologies 14. CTO’s Playbook for Transformation APPENDIX: Additional Resources for Further Learning