Cloud Scale Analytics With Azure Data Services
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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.
Cloud Analytics With Microsoft Azure
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Author : Has Altaiar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-01-28
Cloud Analytics With Microsoft Azure written by Has Altaiar 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 2021-01-28 with Computers categories.
Learn to extract actionable insights from your big data in real time using a range of Microsoft Azure features Key FeaturesUpdated with the latest features and new additions to Microsoft AzureMaster the fundamentals of cloud analytics using AzureLearn to use Azure Synapse Analytics (formerly known as Azure SQL Data Warehouse) to derive real-time customer insightsBook Description Cloud Analytics with Microsoft Azure serves as a comprehensive guide for big data analysis and processing using a range of Microsoft Azure features. This book covers everything you need to build your own data warehouse and learn numerous techniques to gain useful insights by analyzing big data The book begins by introducing you to the power of data with big data analytics, the Internet of Things (IoT), machine learning, artificial intelligence, and DataOps. You will learn about cloud-scale analytics and the services Microsoft Azure offers to empower businesses to discover insights. You will also be introduced to the new features and functionalities added to the modern data warehouse. Finally, you will look at two real-world business use cases to demonstrate high-level solutions using Microsoft Azure. The aim of these use cases will be to illustrate how real-time data can be analyzed in Azure to derive meaningful insights and make business decisions. You will learn to build an end-to-end analytics pipeline on the cloud with machine learning and deep learning concepts. By the end of this book, you will be proficient in analyzing large amounts of data with Azure and using it effectively to benefit your organization. What you will learnExplore the concepts of modern data warehouses and data pipelinesDiscover unique design considerations while applying a cloud analytics solutionDesign an end-to-end analytics pipeline on the cloudDifferentiate between structured, semi-structured, and unstructured dataChoose a cloud-based service for your data analytics solutionsUse Azure services to ingest, store, and analyze data of any scaleWho this book is for This book is designed to benefit software engineers, Azure developers, cloud consultants, and anyone who is keen to learn the process of deriving business insights from huge amounts of data using Azure. Though not necessary, a basic understanding of data analytics concepts such as data streaming, data types, the machine learning life cycle, and Docker containers will help you get the most out of the book.
Engineering Data Mesh In Azure Cloud
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Author : Aniruddha Deswandikar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-03-29
Engineering Data Mesh In Azure Cloud written by Aniruddha Deswandikar 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 2024-03-29 with Computers categories.
Overcome data mesh adoption challenges using the cloud-scale analytics framework and make your data analytics landscape agile and efficient by using standard architecture patterns for diverse analytical workloads Key Features Delve into core data mesh concepts and apply them to real-world situations Safely reassess and redesign your framework for seamless data mesh integration Conquer practical challenges, from domain organization to building data contracts Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDecentralizing data and centralizing governance are practical, scalable, and modern approaches to data analytics. However, implementing a data mesh can feel like changing the engine of a moving car. Most organizations struggle to start and get caught up in the concept of data domains, spending months trying to organize domains. This is where Engineering Data Mesh in Azure Cloud can help. The book starts by assessing your existing framework before helping you architect a practical design. As you progress, you’ll focus on the Microsoft Cloud Adoption Framework for Azure and the cloud-scale analytics framework, which will help you quickly set up a landing zone for your data mesh in the cloud. The book also resolves common challenges related to the adoption and implementation of a data mesh faced by real customers. It touches on the concepts of data contracts and helps you build practical data contracts that work for your organization. The last part of the book covers some common architecture patterns used for modern analytics frameworks such as artificial intelligence (AI). By the end of this book, you’ll be able to transform existing analytics frameworks into a streamlined data mesh using Microsoft Azure, thereby navigating challenges and implementing advanced architecture patterns for modern analytics workloads.What you will learn Build a strategy to implement a data mesh in Azure Cloud Plan your data mesh journey to build a collaborative analytics platform Address challenges in designing, building, and managing data contracts Get to grips with monitoring and governing a data mesh Understand how to build a self-service portal for analytics Design and implement a secure data mesh architecture Resolve practical challenges related to data mesh adoption Who this book is for This book is for chief data officers and data architects of large and medium-size organizations who are struggling to maintain silos of data and analytics projects. Data architects and data engineers looking to understand data mesh and how it can help their organizations democratize data and analytics will also benefit from this book. Prior knowledge of managing centralized analytical systems, as well as experience with building data lakes, data warehouses, data pipelines, data integrations, and transformations is needed to get the most out of this book.
Data Modeling For Azure Data Services
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Author : Peter ter Braake
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-07-30
Data Modeling For Azure Data Services written by Peter ter Braake 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 2021-07-30 with Computers categories.
Choose the right Azure data service and correct model design for successful implementation of your data model with the help of this hands-on guide Key FeaturesDesign a cost-effective, performant, and scalable database in AzureChoose and implement the most suitable design for a databaseDiscover how your database can scale with growing data volumes, concurrent users, and query complexityBook Description Data is at the heart of all applications and forms the foundation of modern data-driven businesses. With the multitude of data-related use cases and the availability of different data services, choosing the right service and implementing the right design becomes paramount to successful implementation. Data Modeling for Azure Data Services starts with an introduction to databases, entity analysis, and normalizing data. The book then shows you how to design a NoSQL database for optimal performance and scalability and covers how to provision and implement Azure SQL DB, Azure Cosmos DB, and Azure Synapse SQL Pool. As you progress through the chapters, you'll learn about data analytics, Azure Data Lake, and Azure SQL Data Warehouse and explore dimensional modeling, data vault modeling, along with designing and implementing a Data Lake using Azure Storage. You'll also learn how to implement ETL with Azure Data Factory. By the end of this book, you'll have a solid understanding of which Azure data services are the best fit for your model and how to implement the best design for your solution. What you will learnModel relational database using normalization, dimensional, or Data Vault modelingProvision and implement Azure SQL DB and Azure Synapse SQL PoolsDiscover how to model a Data Lake and implement it using Azure StorageModel a NoSQL database and provision and implement an Azure Cosmos DBUse Azure Data Factory to implement ETL/ELT processesCreate a star schema model using dimensional modelingWho this book is for This book is for business intelligence developers and consultants who work on (modern) cloud data warehousing and design and implement databases. Beginner-level knowledge of cloud data management is expected.
Scalable Data Analytics With Azure Data Explorer
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Author : Jason Myerscough
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-03-17
Scalable Data Analytics With Azure Data Explorer written by Jason Myerscough 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.
Write efficient and powerful KQL queries to query and visualize your data and implement best practices to improve KQL execution performance Key FeaturesApply Azure Data Explorer best practices to manage your data at scale and reduce KQL execution timeDiscover how to query and visualize your data using the powerful KQLManage cluster performance and monthly costs by understanding how to size your ADX cluster correctlyBook Description Azure Data Explorer (ADX) enables developers and data scientists to make data-driven business decisions. This book will help you rapidly explore and query your data at scale and secure your ADX clusters. The book begins by introducing you to ADX, its architecture, core features, and benefits. You'll learn how to securely deploy ADX instances and navigate through the ADX Web UI, cover data ingestion, and discover how to query and visualize your data using the powerful Kusto Query Language (KQL). Next, you'll get to grips with KQL operators and functions to efficiently query and explore your data, as well as perform time series analysis and search for anomalies and trends in your data. As you progress through the chapters, you'll explore advanced ADX topics, including deploying your ADX instances using Infrastructure as Code (IaC). The book also shows you how to manage your cluster performance and monthly ADX costs by handling cluster scaling and data retention periods. Finally, you'll understand how to secure your ADX environment by restricting access with best practices for improving your KQL query performance. By the end of this Azure book, you'll be able to securely deploy your own ADX instance, ingest data from multiple sources, rapidly query your data, and produce reports with KQL and Power BI. What you will learnBecome well-versed with the core features of the Azure Data Explorer architectureDiscover how ADX can help manage your data at scale on AzureGet to grips with deploying your ADX environment and ingesting and analyzing your dataExplore KQL and learn how to query your dataQuery and visualize your data using the ADX UI and Power BIIngest structured and unstructured data types from an array of sourcesUnderstand how to deploy, scale, secure, and manage ADXWho this book is for This book is for data analysts, data engineers, and data scientists who are responsible for analyzing and querying their team's large volumes of data on Azure. SRE and DevOps engineers who deploy, maintain, and secure infrastructure will also find this book useful. Prior knowledge of Azure and basic data querying will help you to get the most out of this book.
Mapping Data Flows In Azure Data Factory
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Author : Mark Kromer
language : en
Publisher: Apress
Release Date : 2022-09-06
Mapping Data Flows In Azure Data Factory written by Mark Kromer and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-06 with Computers categories.
Build scalable ETL data pipelines in the cloud using Azure Data Factory’s Mapping Data Flows. Each chapter of this book addresses different aspects of an end-to-end data pipeline that includes repeatable design patterns based on best practices using ADF’s code-free data transformation design tools. The book shows data engineers how to take raw business data at cloud scale and turn that data into business value by organizing and transforming the data for use in data science projects and analytics systems. The book begins with an introduction to Azure Data Factory followed by an introduction to its Mapping Data Flows feature set. Subsequent chapters show how to build your first pipeline and corresponding data flow, implement common design patterns, and operationalize your result. By the end of the book, you will be able to apply what you’ve learned to your complex data integration and ETL projects in Azure. These projects will enable cloud-scale big analytics and data loading and transformation best practices for data warehouses. What You Will Learn Build scalable ETL jobs in Azure without writing code Transform big data for data quality and data modeling requirements Understand the different aspects of Azure Data Factory ETL pipelines from datasets and Linked Services to Mapping Data Flows Apply best practices for designing and managing complex ETL data pipelines in Azure Data Factory Add cloud-based ETL patterns to your set of data engineering skills Build repeatable code-free ETL design patterns Who This Book Is For Data engineers who are new to building complex data transformation pipelines in the cloud with Azure; and data engineers who need ETL solutions that scale to match swiftly growing volumes of data
Unlocking Retail Success Leveraging Analytics Stack Solutions For Data Driven Decision Making And Competitive Edge
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Author : Olalekan Olaniru
language : en
Publisher: GRIN Verlag
Release Date : 2024-01-15
Unlocking Retail Success Leveraging Analytics Stack Solutions For Data Driven Decision Making And Competitive Edge written by Olalekan Olaniru and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-15 with Computers categories.
Seminar paper from the year 2023 in the subject Computer Science - Commercial Information Technology, grade: 2,0, (International University of Applied Sciences), course: Analytical Software & Framework, language: English, abstract: This study focused on how an analytics stack solution can help a traditional retail company leverage the massive amount of data generated by various sales channels to improve its decision-making, productivity, and competitiveness. The analytics stack solution enables real-time tracking and analysis of customer behavior, sales performance, and market trends across physical stores, e-commerce, wholesale, and other channels. The study also examines the best deployment option (on-premise or cloud) for the analytics stack solution, considering the data type, volume, security, privacy, flexibility, and scaling factors. Furthermore, the study discusses the change management issues, essential components of a retail analytics stack and recommendations for adoption.
Dp 500 Designing And Implementing Enterprise Scale Analytics Solutions Using Microsoft Azure And Microsoft Power Bi Exam Guide
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Author : Anand Venula
language : en
Publisher: Anand Vemula
Release Date :
Dp 500 Designing And Implementing Enterprise Scale Analytics Solutions Using Microsoft Azure And Microsoft Power Bi Exam Guide written by Anand Venula and has been published by Anand Vemula this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
The DP-500: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI study guide is designed to help professionals prepare for the DP-500 certification exam. This exam is aimed at Azure Enterprise Data Analyst Associates who want to validate their skills in designing and implementing data analytics solutions using Microsoft Azure and Power BI. The study guide covers several core topics. First, it emphasizes the configuration and management of Power BI workspaces, datasets, and dataflows, as well as ensuring security and governance. This is followed by the use of Power Query for transforming and cleaning data, and integrating data from various sources like Azure Synapse Analytics. Next, it explores the creation of tabular models in Power BI and the implementation of DAX measures, calculated columns, and performance optimizations. The guide also focuses on advanced analytics, teaching users how to visualize and interpret data with Power BI, use advanced techniques like AI visuals and R integration, and enable self-service analytics for users. Lastly, it covers the deployment of assets and managing lifecycle processes in the Power BI environment, including setting up and monitoring data refresh schedules and using version control for deployments. By the end of the study guide, readers will gain the expertise to design, implement, and manage data solutions that meet the needs of large-scale organizations, enabling them to pass the DP-500 exam and confidently work with Microsoft’s cloud-based analytics tools.
Cloud Analytics With Microsoft Azure
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Author : Has Altaiar
language : en
Publisher:
Release Date : 2019-11-22
Cloud Analytics With Microsoft Azure written by Has Altaiar and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-22 with Computers categories.
Leverage the power of Azure to get efficient data insights from your big data in real time Key Features Explore the basics of cloud analytics using Azure Discover different ways to process and visualize your data easily Learn to use Azure Synapse Analytics (formerly known as Azure SQL Data Warehouse) to derive real-time customer insights Book Description With data being generated at an exponential speed, organizations all over the world are migrating their infrastructure to the cloud. Application management becomes much easier when you use a cloud platform to build, manage, and deploy your services and applications. Cloud Analytics with Microsoft Azure covers all that you need to extract useful insights from your data. You'll explore the power of data with big data analytics, the Internet of Things (IoT), machine learning, artificial intelligence, and DataOps. You'll also delve into data analytics by studying use cases that focus on creating actionable insights from near-real-time data. As you advance, you'll learn to build an end-to-end analytics pipeline on the cloud with machine learning and deep learning concepts. By the end of this book, you'll have developed a solid understanding of data analytics with Azure and its practical implementation. What you will learn Explore the concepts of modern data warehouses and data pipelines Discover different design considerations while applying a cloud analytics solution Design an end-to-end analytics pipeline on the cloud Differentiate between structured, semi-structured, and unstructured data Choose a cloud-based service for your data analytics solutions Use Azure services to ingest, store and analyze data of any scale Who this book is for If you're planning to adopt the cloud analytics model for your business, this book will help you understand the design and business considerations that you must keep in mind. Though not necessary, a basic understanding of data analytics concepts such as data streaming, data types, the machine learning life cycle, and Docker containers will help you get the most out of the book.
Azure
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Author : 葉心寬（Leo Yeh）
language : zh-CN
Publisher: 博碩
Release Date : 2022-11-27
Azure written by 葉心寬（Leo Yeh） and has been published by 博碩 this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-27 with Computers categories.
本書涵蓋Azure證照報考、專案實務到求職準備 為自己考取第一張Azure雲端證照！ 想要進入Azure雲端產業嗎？想要考取微軟Azure證照，卻不知道該從何報考？本書針對Azure證照進行詳細解說，帶領讀者快速掌握Azure雲端的關鍵服務：從基礎概念、核心服務，到安全性、成本管理，每單元搭配英文模擬測試考題。最後作者以自身角度，分享面試Azure工作的準備方向、面試技巧。 本書特色： 【證照流程】 認識Azure證照種類、報考流程、繪製架構流程圖。你還可以透過本書的Azure模擬英文考題進行練習衝刺，加深雲端知識。 【基礎概念】 你將從雲端運算、Azure服務層級起步，接著進一步理解計算、網路及儲存分析等概念。 【核心服務】 深入認識核心解決方案和管理工具，例如Azure IoT、Azure AI、Azure Serverless等等，針對不同情境使用不同工具。 【進階管理】 學習Azure安全管理、方法與原則、身分識別、個人隱私和合規性、成本管理、備份教學和提高雲端安全的管理。 【考題練習】 本書的每單元皆搭配英文模擬測試考題，此外你還可以透過下載範例檔，額外練習更多英文考題，強化並加深Azure雲端知識。 【面試求職】 考完證照只是獲得面試的入場券。因此，你更應該善用對的職缺平台、有效進行面試準備、活用面試STAR原則、熟悉遠距面試流程，讓自己的努力更亮眼。