Azure Modern Data Architecture
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Azure Modern Data Architecture
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Author : Anouar BEN ZAHRA
language : en
Publisher: Anouar BEN ZAHRA
Release Date :
Azure Modern Data Architecture written by Anouar BEN ZAHRA and has been published by Anouar BEN ZAHRA this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Key Features Discover the key drivers of successful Azure architecture Practical guidance Focus on scalability and performance Expert authorship Book Description This book presents a guide to design and implement scalable, secure, and efficient data solutions in the Azure cloud environment. It provides Data Architects, developers, and IT professionals who are responsible for designing and implementing data solutions in the Azure cloud environment with the knowledge and tools needed to design and implement data solutions using the latest Azure data services. It covers a wide range of topics, including data storage, data processing, data analysis, and data integration. In this book, you will learn how to select the appropriate Azure data services, design a data processing pipeline, implement real-time data processing, and implement advanced analytics using Azure Databricks and Azure Synapse Analytics. You will also learn how to implement data security and compliance, including data encryption, access control, and auditing. Whether you are building a new data architecture from scratch or migrating an existing on premises solution to Azure, the Azure Data Architecture Guidelines are an essential resource for any organization looking to harness the power of data in the cloud. With these guidelines, you will gain a deep understanding of the principles and best practices of Azure data architecture and be equipped to build data solutions that are highly scalable, secure, and cost effective. What You Need to Use this Book? To use this book, it is recommended that readers have a basic understanding of data architecture concepts and data management principles. Some familiarity with cloud computing and Azure services is also helpful. The book is designed for data architects, data engineers, data analysts, and anyone involved in designing, implementing, and managing data solutions on the Azure cloud platform. It is also suitable for students and professionals who want to learn about Azure data architecture and its best practices.
Modern Data Architecture On Azure
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Author : Sagar Lad
language : en
Publisher: Apress
Release Date : 2023-11-08
Modern Data Architecture On Azure written by Sagar Lad and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-08 with Computers categories.
This book is an exhaustive guide to designing and implementing data solutions on Azure. It covers the process of managing data from end to end, starting from data collection all the way through transformation, distribution, and consumption. Modern Data Architecture on Azure begins with an introduction to the fundaments of data management, followed by a demonstration of how to build relational and non-relational data solutions on Azure. Here, you will learn data processing for complex analysis and how to work with CSV and JSON files. Moving forward, you will learn the foundational concepts of big data architecture, along with data management patterns and technology options offered by Azure. From there, you’ll be walked through the data architecture process, including data consortium on Azure, enterprise data governance, and much more. The book culminates with a deep dive into data architecture frameworks with data modeling. After reading this book, you will have a thorough understanding of data design and analytics using Azure, allowing you to collect and analyze massive amounts of data to optimize business performance, forecast future results, and more. What Will You Learn Understand the fundamentals of data architecture including data management, data handling ethics, data governance, and metadata management Analyze and understand business needs to choose the right Azure services and make informed business decisions Understand Azure Cloud Data design patterns for relational and non-relational data, batch real-time processing, and ETL/ELT pipelines Modernize data architecture using Azure to leverage data and AI to enable digital transformation by securing and optimizing overall data lifecycle management Who Is This Book For: Data solution architects, data engineers, and IT consultants who want to gain a better understanding of modern data architecture design and implementation on Azure.
The Modern Data Warehouse In Azure
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Author : Matt How
language : en
Publisher: Apress
Release Date : 2020-06-15
The Modern Data Warehouse In Azure written by Matt How and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-15 with Computers categories.
Build a modern data warehouse on Microsoft's Azure Platform that is flexible, adaptable, and fast—fast to snap together, reconfigure, and fast at delivering results to drive good decision making in your business. Gone are the days when data warehousing projects were lumbering dinosaur-style projects that took forever, drained budgets, and produced business intelligence (BI) just in time to tell you what to do 10 years ago. This book will show you how to assemble a data warehouse solution like a jigsaw puzzle by connecting specific Azure technologies that address your own needs and bring value to your business. You will see how to implement a range of architectural patterns using batches, events, and streams for both data lake technology and SQL databases. You will discover how to manage metadata and automation to accelerate the development of your warehouse while establishing resilience at every level. And you will know how to feed downstream analytic solutions such as Power BI and Azure Analysis Services to empower data-driven decision making that drives your business forward toward a pattern of success. This book teaches you how to employ the Azure platform in a strategy to dramatically improve implementation speed and flexibility of data warehousing systems. You will know how to make correct decisions in design, architecture, and infrastructure such as choosing which type of SQL engine (from at least three options) best meets the needs of your organization. You also will learn about ETL/ELT structure and the vast number of accelerators and patterns that can be used to aid implementation and ensure resilience. Data warehouse developers and architects will find this book a tremendous resource for moving their skills into the future through cloud-based implementations. What You Will Learn Choose the appropriate Azure SQL engine for implementing a given data warehouse Develop smart, reusable ETL/ELT processes that are resilient and easily maintained Automate mundane development tasks through tools such as PowerShell Ensure consistency of data by creating and enforcing data contracts Explore streaming and event-driven architectures for data ingestion Create advanced staging layers using Azure Data Lake Gen 2 to feed your data warehouse Who This Book Is For Data warehouse or ETL/ELT developers who wish to implement a data warehouse project in the Azure cloud, and developers currently working in on-premise environments who want to move to the cloud, and for developers with Azure experience looking to tighten up their implementation and consolidate their knowledge
Building Cloud Data Platforms Solutions
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Author : Anouar BEN ZAHRA
language : en
Publisher: Anouar BEN ZAHRA
Release Date :
Building Cloud Data Platforms Solutions written by Anouar BEN ZAHRA and has been published by Anouar BEN ZAHRA this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
"Building Cloud Data Platforms Solutions: An End-to-End Guide for Designing, Implementing, and Managing Robust Data Solutions in the Cloud" comprehensively covers a wide range of topics related to building data platforms in the cloud. This book provides a deep exploration of the essential concepts, strategies, and best practices involved in designing, implementing, and managing end-to-end data solutions. The book begins by introducing the fundamental principles and benefits of cloud computing, with a specific focus on its impact on data management and analytics. It covers various cloud services and architectures, enabling readers to understand the foundation upon which cloud data platforms are built. Next, the book dives into key considerations for building cloud data solutions, aligning business needs with cloud data strategies, and ensuring scalability, security, and compliance. It explores the process of data ingestion, discussing various techniques for acquiring and ingesting data from different sources into the cloud platform. The book then delves into data storage and management in the cloud. It covers different storage options, such as data lakes and data warehouses, and discusses strategies for organizing and optimizing data storage to facilitate efficient data processing and analytics. It also addresses data governance, data quality, and data integration techniques to ensure data integrity and consistency across the platform. A significant portion of the book is dedicated to data processing and analytics in the cloud. It explores modern data processing frameworks and technologies, such as Apache Spark and serverless computing, and provides practical guidance on implementing scalable and efficient data processing pipelines. The book also covers advanced analytics techniques, including machine learning and AI, and demonstrates how these can be integrated into the data platform to unlock valuable insights. Furthermore, the book addresses an aspects of data platform monitoring, security, and performance optimization. It explores techniques for monitoring data pipelines, ensuring data security, and optimizing performance to meet the demands of real-time data processing and analytics. Throughout the book, real-world examples, case studies, and best practices are provided to illustrate the concepts discussed. This helps readers apply the knowledge gained to their own data platform projects.
Cloud Scale Analytics With Azure Data Services
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Author : Patrik Borosch
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-07-23
Cloud Scale Analytics With Azure Data Services written by Patrik Borosch 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 2021-07-23 with Computers categories.
A practical guide to implementing a scalable and fast state-of-the-art analytical data estate Key FeaturesStore and analyze data with enterprise-grade security and auditingPerform batch, streaming, and interactive analytics to optimize your big data solutions with easeDevelop and run parallel data processing programs using real-world enterprise scenariosBook Description Azure Data Lake, the modern data warehouse architecture, and related data services on Azure enable organizations to build their own customized analytical platform to fit any analytical requirements in terms of volume, speed, and quality. This book is your guide to learning all the features and capabilities of Azure data services for storing, processing, and analyzing data (structured, unstructured, and semi-structured) of any size. You will explore key techniques for ingesting and storing data and perform batch, streaming, and interactive analytics. The book also shows you how to overcome various challenges and complexities relating to productivity and scaling. Next, you will be able to develop and run massive data workloads to perform different actions. Using a cloud-based big data-modern data warehouse-analytics setup, you will also be able to build secure, scalable data estates for enterprises. Finally, you will not only learn how to develop a data warehouse but also understand how to create enterprise-grade security and auditing big data programs. By the end of this Azure book, you will have learned how to develop a powerful and efficient analytical platform to meet enterprise needs. What you will learnImplement data governance with Azure servicesUse integrated monitoring in the Azure Portal and integrate Azure Data Lake Storage into the Azure MonitorExplore the serverless feature for ad-hoc data discovery, logical data warehousing, and data wranglingImplement networking with Synapse Analytics and Spark poolsCreate and run Spark jobs with Databricks clustersImplement streaming using Azure Functions, a serverless runtime environment on AzureExplore the predefined ML services in Azure and use them in your appWho this book is for This book is for data architects, ETL developers, or anyone who wants to get well-versed with Azure data services to implement an analytical data estate for their enterprise. The book will also appeal to data scientists and data analysts who want to explore all the capabilities of Azure data services, which can be used to store, process, and analyze any kind of data. A beginner-level understanding of data analysis and streaming will be required.
Microsoft Power Bi Performance Best Practices
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Author : Bhavik Merchant
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-04-22
Microsoft Power Bi Performance Best Practices written by Bhavik Merchant 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 2022-04-22 with Computers categories.
Supercharge performance analytics and create repeatable patterns to ensure you get the best performance and scalability from your analytics solutions with Power BI Key Features Learn how to build performant data models and apply Row-Level Security Identify and fix performance issues in reports, DAX, and datasets using DAX Studio/VertiPaq Analyzer Use a formal process to manage performance, from setting targets to monitoring and remediating issues Book DescriptionThis book comprehensively covers every layer of Power BI, from the report canvas to data modeling, transformations, storage, and architecture. Developers and architects working with any area of Power BI will be able to put their knowledge to work with this practical guide to design and implement at every stage of the analytics solution development process. This book is not only a unique collection of best practices and tips, but also provides you with a hands-on approach to identifying and fixing common performance issues. Complete with explanations of essential concepts and practical examples, you’ll learn about common design choices that affect performance and consume more resources and how to avoid these problems. You’ll grasp the general architectural issues and settings that broadly affect most solutions. As you progress, you’ll walk through each layer of a typical Power BI solution, learning how to ensure your designs can handle scale while not sacrificing usability. You’ll focus on the data layer and then work your way up to report design. We will also cover Power BI Premium and load testing. By the end of this Power BI book, you’ll be able to confidently maintain well-performing Power BI solutions with reduced effort and know how to use freely available tools and a systematic process to monitor and diagnose performance problems.What you will learn Understand how to set realistic performance targets and address performance proactively Understand how architectural options and configuration affect performance Build efficient Power BI reports and data transformations Explore best practices for data modeling, DAX, and large datasets Understand the inner workings of Power BI Premium Explore options for extreme scale with Azure services Understand how to use tools that help identify and fix performance issues Who this book is for Data analysts, BI developers, and data professionals who have learnt the basics of Power BI and now want to understand how to build advanced analytics solutions will find this business intelligence book useful. Familiarity with the major components of Power BI and a beginner-level understanding of their purpose and use cases are required.
Architecting The Future Of Data Oracle Sharding Cloud Intelligence And Scalable Enterprise Systems 2025
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Author : Author:1- Sarvesh Kumar Gupta, Author:2-Dr. Lalit Kumar
language : en
Publisher: RAVEENA PRAKASHAN OPC PVT LTD
Release Date :
Architecting The Future Of Data Oracle Sharding Cloud Intelligence And Scalable Enterprise Systems 2025 written by Author:1- Sarvesh Kumar Gupta, Author:2-Dr. Lalit Kumar and has been published by RAVEENA PRAKASHAN OPC PVT LTD this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
PREFACE In the digital age, data has become the driving force behind business decision-making, customer experiences, and technological innovation. As organizations strive to harness the full potential of their data, the need for scalable, efficient, and resilient data architectures has never been greater. Traditional monolithic database systems are often insufficient to handle the massive volumes, variety, and velocity of data generated by modern enterprises. Enter Oracle Sharding, Cloud Intelligence, and scalable enterprise systems—the cornerstone technologies that enable organizations to meet the demands of the data-driven future.Architecting the Future of Data: Oracle Sharding, Cloud Intelligence, and Scalable Enterprise Systems offers a comprehensive exploration of how these cutting-edge technologies are reshaping the landscape of enterprise data management. This book provides in-depth insights into how organizations can design and implement scalable, cloud-native database architectures that allow for seamless data distribution, faster processing, and enhanced performance. By focusing on Oracle Sharding, cloud intelligence, and enterprise scalability, this book aims to equip IT professionals, data architects, and business leaders with the knowledge and tools required to build the next generation of enterprise systems. The foundation of this book is Oracle’s Sharding technology, which offers an innovative approach to database architecture by horizontally partitioning data across multiple databases, or shards. This approach enhances both performance and scalability, allowing organizations to process vast amounts of data across distributed environments while ensuring high availability, fault tolerance, and efficient resource utilization. As businesses increasingly adopt cloud platforms, Oracle Sharding proves to be a critical tool for managing data in distributed cloud environments, ensuring seamless data access and faster query performance even as data volumes grow exponentially. Furthermore, cloud intelligence plays a pivotal role in enabling organizations to build smarter, more adaptive systems. As cloud technologies evolve, leveraging intelligent data processing, machine learning (ML), and artificial intelligence (AI) has become a game-changer for businesses looking to extract deeper insights from their data and improve operational efficiencies. This book delves into how cloud intelligence, when integrated with scalable data architectures like Oracle Sharding, allows enterprises to process, analyze, and gain real-time insights from massive datasets. The ability to deploy AI models directly within the cloud infrastructure enhances predictive capabilities, automates decision-making processes, and drives innovation. Scalable enterprise systems are essential for organizations to maintain their competitive edge in a rapidly changing business environment. As companies expand their digital footprints and create more data-intensive applications, the need for scalable, distributed data architectures has become crucial. This book explores the design principles and best practices for creating cloud-native enterprise systems that can adapt to growing data demands while ensuring high performance and security. By understanding the synergy between Oracle Sharding and cloud intelligence, organizations can build resilient systems capable of handling the complexities of modern data workflows. Throughout the chapters, we will cover not only the technical aspects of these technologies but also real-world use cases and best practices from leading companies who have successfully adopted Oracle Sharding and cloud-based data architectures. This book aims to bridge the gap between theoretical concepts and practical implementation, offering readers actionable strategies for building scalable, cloud-native data systems that align with business goals and technological advancements. As organizations continue to embrace digital transformation and the cloud becomes the backbone of modern IT infrastructure, understanding how to design and implement scalable, intelligent data architectures is more critical than ever. Whether you are an IT architect, database administrator, or business leader, Architecting the Future of Data will provide you with the insights and strategies necessary to navigate the challenges and opportunities of modern data management. The future of data is distributed, intelligent, and scalable—this book will guide you in shaping that future within your organization. Authors
Data Lake Analytics On Microsoft Azure
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Author : Harsh Chawla
language : en
Publisher: Apress
Release Date : 2020-11-15
Data Lake Analytics On Microsoft Azure written by Harsh Chawla and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-15 with Computers categories.
Get a 360-degree view of how the journey of data analytics solutions has evolved from monolithic data stores and enterprise data warehouses to data lakes and modern data warehouses. You will This book includes comprehensive coverage of how: To architect data lake analytics solutions by choosing suitable technologies available on Microsoft Azure The advent of microservices applications covering ecommerce or modern solutions built on IoT and how real-time streaming data has completely disrupted this ecosystem These data analytics solutions have been transformed from solely understanding the trends from historical data to building predictions by infusing machine learning technologies into the solutions Data platform professionals who have been working on relational data stores, non-relational data stores, and big data technologies will find the content in this book useful. The book also can help you start your journey into the data engineer world as it provides an overview of advanced data analytics and touches on data science concepts and various artificial intelligence and machine learning technologies available on Microsoft Azure. What Will You Learn You will understand the: Concepts of data lake analytics, the modern data warehouse, and advanced data analytics Architecture patterns of the modern data warehouse and advanced data analytics solutions Phases—such as Data Ingestion, Store, Prep and Train, and Model and Serve—of data analytics solutions and technology choices available on Azure under each phase In-depth coverage of real-time and batch mode data analytics solutions architecture Various managed services available on Azure such as Synapse analytics, event hubs, Stream analytics, CosmosDB, and managed Hadoop services such as Databricks and HDInsight Who This Book Is For Data platform professionals, database architects, engineers, and solution architects
Building Medallion Architectures
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Author : Piethein Strengholt
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-03-28
Building Medallion Architectures written by Piethein Strengholt and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-28 with Computers categories.
To deliver the insights that give them a competitive advantage, organizations increasingly turn to the proven Medallion architecture. Yet implementing a robust data architecture can be difficult, particularly when it comes to using the Medallion architecture's Bronze, Silver, and Gold layers—done wrong, it can hamper your ability to make data-driven decisions. This practical guide helps you build a Medallion architecture the right way with Azure Databricks and Microsoft Fabric. Drawing on hands-on experience from the field, Piethein Strengholt demystifies common assumptions and complex problems you'll face when embarking on a new data architecture. Architects and engineers of all stripes will find answers to the most typical questions along with insights from real organizations about what's worked, what hasn't, and why. You'll learn: Learn how to build a Medallion architecture with Azure Databricks and Microsoft Fabric Gain insights from three real case studies that illustrate practical field experience and lessons learned Explore scaling considerations, including governance, security, generative AI, and more Make informed decisions when designing or implementing new data architectures Get proven patterns for success that align with broader organizational objectives
Data Lakehouse In Action
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Author : Pradeep Menon
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-03-17
Data Lakehouse In Action written by Pradeep Menon 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 2022-03-17 with Computers categories.
Propose a new scalable data architecture paradigm, Data Lakehouse, that addresses the limitations of current data architecture patterns Key FeaturesUnderstand how data is ingested, stored, served, governed, and secured for enabling data analyticsExplore a practical way to implement Data Lakehouse using cloud computing platforms like AzureCombine multiple architectural patterns based on an organization's needs and maturity levelBook Description The Data Lakehouse architecture is a new paradigm that enables large-scale analytics. This book will guide you in developing data architecture in the right way to ensure your organization's success. The first part of the book discusses the different data architectural patterns used in the past and the need for a new architectural paradigm, as well as the drivers that have caused this change. It covers the principles that govern the target architecture, the components that form the Data Lakehouse architecture, and the rationale and need for those components. The second part deep dives into the different layers of Data Lakehouse. It covers various scenarios and components for data ingestion, storage, data processing, data serving, analytics, governance, and data security. The book's third part focuses on the practical implementation of the Data Lakehouse architecture in a cloud computing platform. It focuses on various ways to combine the Data Lakehouse pattern to realize macro-patterns, such as Data Mesh and Data Hub-Spoke, based on the organization's needs and maturity level. The frameworks introduced will be practical and organizations can readily benefit from their application. By the end of this book, you'll clearly understand how to implement the Data Lakehouse architecture pattern in a scalable, agile, and cost-effective manner. What you will learnUnderstand the evolution of the Data Architecture patterns for analyticsBecome well versed in the Data Lakehouse pattern and how it enables data analyticsFocus on methods to ingest, process, store, and govern data in a Data Lakehouse architectureLearn techniques to serve data and perform analytics in a Data Lakehouse architectureCover methods to secure the data in a Data Lakehouse architectureImplement Data Lakehouse in a cloud computing platform such as AzureCombine Data Lakehouse in a macro-architecture pattern such as Data MeshWho this book is for This book is for data architects, big data engineers, data strategists and practitioners, data stewards, and cloud computing practitioners looking to become well-versed with modern data architecture patterns to enable large-scale analytics. Basic knowledge of data architecture and familiarity with data warehousing concepts are required.