Реклама. ООО «ЛитРес», ИНН: 7719571260.
Chapter 1. Introduction
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Chapter 4. Data Exploration and Transformation
Chapter 7. Data Orchestration and Monitoring
Chapter 9. Security and Compliance
Chapter 10. Scaling and Performance Optimization
10.2 Performance Optimization Techniques
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Chapter 12. Best Practices and Tips
Welcome to «Mastering Azure Synapse Analytics: Guide to Modern Data Integration.» In this book, we embark on a journey through the intricate world of Azure Synapse Analytics, Microsoft’s cutting-edge cloud analytics service designed to empower organizations with powerful data integration, management, and analysis capabilities. Whether you’re a seasoned data professional looking to expand your skills or a newcomer eager to harness the full potential of Azure Synapse Analytics, this book is your comprehensive companion. Through detailed explanations, practical examples, and expert insights, we delve into the core concepts, best practices, and advanced techniques necessary to navigate the complexities of modern data analytics. From data ingestion and transformation to dynamic data masking, compliance reporting, and beyond, each chapter is meticulously crafted to provide you with the knowledge and skills needed to succeed in today’s data-driven world.
Throughout my career as a data engineer, I have had extensive hands-on experience with various data platforms, culminating in a deep expertise in Azure Synapse Analytics. This book draws on my practical knowledge and industry insights, providing readers with step-by-step instructions, best practices, and detailed examples of how to implement, optimize, and secure data solutions using Synapse Analytics. Key topics include data ingestion, integration with Power BI for reporting, ensuring compliance with data regulations, dynamic data masking, and advanced monitoring and troubleshooting techniques.
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Applications: Data generated by business applications, software systems, or enterprise resource planning (ERP) systems constitutes a valuable source for analysis.
Sensors and IoT Devices: In the context of the Internet of Things (IoT), data sources extend to sensors, devices, and edge computing environments, generating real-time data streams.
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