[PDF] Ultimate Azure Data Engineering Build Robust Data Engineering Systems On Azure With Sql Etl Data Modeling And Power Bi For Business Insights And Crack Azure Certifications - eBooks Review

Ultimate Azure Data Engineering Build Robust Data Engineering Systems On Azure With Sql Etl Data Modeling And Power Bi For Business Insights And Crack Azure Certifications


Ultimate Azure Data Engineering Build Robust Data Engineering Systems On Azure With Sql Etl Data Modeling And Power Bi For Business Insights And Crack Azure Certifications
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Ultimate Azure Data Engineering


Ultimate Azure Data Engineering
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Author : Ashish Agarwal
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2024-07-22

Ultimate Azure Data Engineering written by Ashish Agarwal and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-22 with Computers categories.


TAGLINE Discover the world of data engineering in an on-premises setting versus the Azure cloud KEY FEATURES ● Explore Azure data engineering from foundational concepts to advanced techniques, spanning SQL databases, ETL processes, and cloud-native solutions. ● Learn to implement real-world data projects with Azure services, covering data integration, storage, and analytics, tailored for diverse business needs. ● Prepare effectively for Azure data engineering certifications with detailed exam-focused content and practical exercises to reinforce learning. DESCRIPTION Embark on a comprehensive journey into Azure data engineering with “Ultimate Azure Data Engineering”. Starting with foundational topics like SQL and relational database concepts, you'll progress to comparing data engineering practices in Azure versus on-premises environments. Next, you will dive deep into Azure cloud fundamentals, learning how to effectively manage heterogeneous data sources and implement robust Extract, Transform, Load (ETL) concepts using Azure Data Factory, mastering the orchestration of data workflows and pipeline automation. The book then moves to explore advanced database design strategies and discover best practices for optimizing data performance and ensuring stringent data security measures. You will learn to visualize data insights using Power BI and apply these skills to real-world scenarios. Whether you're aiming to excel in your current role or preparing for Azure data engineering certifications, this book equips you with practical knowledge and hands-on expertise to thrive in the dynamic field of Azure data engineering. WHAT WILL YOU LEARN ● Master the core principles and methodologies that drive data engineering such as data processing, storage, and management techniques. ● Gain a deep understanding of Structured Query Language (SQL) and relational database management systems (RDBMS) for Azure Data Engineering. ● Learn about Azure cloud services for data engineering, such as Azure SQL Database, Azure Data Factory, Azure Synapse Analytics, and Azure Blob Storage. ● Gain proficiency to orchestrate data workflows, schedule data pipelines, and monitor data integration processes across cloud and hybrid environments. ● Design optimized database structures and data models tailored for performance and scalability in Azure. ● Implement techniques to optimize data performance such as query optimization, caching strategies, and resource utilization monitoring. ● Learn how to visualize data insights effectively using tools like Power BI to create interactive dashboards and derive data-driven insights. ● Equip yourself with the knowledge and skills needed to pass Microsoft Azure data engineering certifications. WHO IS THIS BOOK FOR? This book is tailored for a diverse audience including aspiring and current Azure data engineers, data analysts, and data scientists, along with database and BI developers, administrators, and analysts. It is an invaluable resource for those aiming to obtain Azure data engineering certifications. TABLE OF CONTENTS 1. Introduction to Data Engineering 2. Understanding SQL and RDBMS Concepts 3. Data Engineering: Azure Versus On-Premises 4. Azure Cloud Concepts 5. Working with Heterogenous Data Sources 6. ETL Concepts 7. Database Design and Modeling 8. Performance Best Practices and Data Security 9. Data Visualization and Application in Real World 10. Data Engineering Certification Guide Index



Ultimate Azure Data Engineering Build Robust Data Engineering Systems On Azure With Sql Etl Data Modeling And Power Bi For Business Insights And Crack Azure Certifications


Ultimate Azure Data Engineering Build Robust Data Engineering Systems On Azure With Sql Etl Data Modeling And Power Bi For Business Insights And Crack Azure Certifications
DOWNLOAD
Author : Ashish Agarwal
language : en
Publisher: Orange Education Pvt Limited
Release Date : 2024-07-22

Ultimate Azure Data Engineering Build Robust Data Engineering Systems On Azure With Sql Etl Data Modeling And Power Bi For Business Insights And Crack Azure Certifications written by Ashish Agarwal and has been published by Orange Education Pvt Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-22 with Computers categories.


Discover the world of data engineering in an on-premises setting versus the Azure cloud Key Features● Explore Azure data engineering from foundational concepts to advanced techniques, spanning SQL databases, ETL processes, and cloud-native solutions. ● Learn to implement real-world data projects with Azure services, covering data integration, storage, and analytics, tailored for diverse business needs. ● Prepare effectively for Azure data engineering certifications with detailed exam-focused content and practical exercises to reinforce learning. Book DescriptionEmbark on a comprehensive journey into Azure data engineering with “Ultimate Azure Data Engineering”. Starting with foundational topics like SQL and relational database concepts, you'll progress to comparing data engineering practices in Azure versus on-premises environments. Next, you will dive deep into Azure cloud fundamentals, learning how to effectively manage heterogeneous data sources and implement robust Extract, Transform, Load (ETL) concepts using Azure Data Factory, mastering the orchestration of data workflows and pipeline automation. The book then moves to explore advanced database design strategies and discover best practices for optimizing data performance and ensuring stringent data security measures. You will learn to visualize data insights using Power BI and apply these skills to real-world scenarios.Whether you're aiming to excel in your current role or preparing for Azure data engineering certifications, this book equips you with practical knowledge and hands-on expertise to thrive in the dynamic field of Azure data engineering. What you will learn ● Master the core principles and methodologies that drive data engineering such as data processing, storage, and management techniques. ● Gain a deep understanding of Structured Query Language (SQL) and relational database management systems (RDBMS) for Azure Data Engineering. ● Learn about Azure cloud services for data engineering, such as Azure SQL Database, Azure Data Factory, Azure Synapse Analytics, and Azure Blob Storage. ● Gain proficiency to orchestrate data workflows, schedule data pipelines, and monitor data integration processes across cloud and hybrid environments. ● Design optimized database structures and data models tailored for performance and scalability in Azure. ● Implement techniques to optimize data performance such as query optimization, caching strategies, and resource utilization monitoring. ● Learn how to visualize data insights effectively using tools like Power BI to create interactive dashboards and derive data-driven insights. Table of Contents1. Introduction to Data Engineering 2. Understanding SQL and RDBMS Concepts 3. Data Engineering: Azure Versus On-Premises 4. Azure Cloud Concepts 5. Working with Heterogenous Data Sources 6. ETL Concepts 7. Database Design and Modeling 8. Performance Best Practices and Data Security 9. Data Visualization and Application in Real World 10. Data Engineering Certification Guide Index



Exam Ref Dp 900 Microsoft Azure Data Fundamentals


Exam Ref Dp 900 Microsoft Azure Data Fundamentals
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Author : Daniel A. Seara
language : en
Publisher: Microsoft Press
Release Date : 2021-03-12

Exam Ref Dp 900 Microsoft Azure Data Fundamentals written by Daniel A. Seara and has been published by Microsoft Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-12 with Computers categories.


Prepare for Microsoft Exam DP-900 Demonstrate your real-world foundational knowledge of core data concepts and how they are implemented using Microsoft Azure data services. Designed for business users, functional consultants, and other professionals, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Azure Data Fundamentals level. Focus on the expertise measured by these objectives: Describe core data concepts Describe how to work with relational data on Azure Describe how to work with non-relational data on Azure Describe an analytics workload on Azure This Microsoft Exam Ref: Organizes its coverage by exam objectives Features strategic, what-if scenarios to challenge you Assumes you have foundational knowledge of core data concepts and their implementation with Microsoft Azure data services, and are beginning to work with data in the cloud About the Exam Exam DP-900 focuses on core knowledge for describing fundamental database concepts and skills for cloud environments; cloud data services within Azure; cloud data roles, tasks, and responsibilities; Azure relational and non-relational data offerings, provisioning, and deployment; querying Azure relational databases; working with Azure non-relational data stores; building modern Azure data analytics solutions; and exploring Azure Data Factory, Azure Synapse Analytics, Azure Databricks, and Azure HDInsight. About Microsoft Certification Passing this exam fulfills your requirements for the Microsoft Certified: Azure Data Fundamentals certification, demonstrating your understanding of the core capabilities of Azure data services and their use with relational data, non-relational data, and analytics workloads. See full details at: www.microsoft.com/learn



Azure Data Factory Cookbook


Azure Data Factory Cookbook
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Author : Dmitry Anoshin
language : en
Publisher:
Release Date : 2020-12-24

Azure Data Factory Cookbook written by Dmitry Anoshin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-24 with Computers categories.




Threat Hunting In The Cloud


Threat Hunting In The Cloud
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Author : Chris Peiris
language : en
Publisher: John Wiley & Sons
Release Date : 2021-08-31

Threat Hunting In The Cloud written by Chris Peiris and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-31 with Computers categories.


Implement a vendor-neutral and multi-cloud cybersecurity and risk mitigation framework with advice from seasoned threat hunting pros In Threat Hunting in the Cloud: Defending AWS, Azure and Other Cloud Platforms Against Cyberattacks, celebrated cybersecurity professionals and authors Chris Peiris, Binil Pillai, and Abbas Kudrati leverage their decades of experience building large scale cyber fusion centers to deliver the ideal threat hunting resource for both business and technical audiences. You'll find insightful analyses of cloud platform security tools and, using the industry leading MITRE ATT&CK framework, discussions of the most common threat vectors. You'll discover how to build a side-by-side cybersecurity fusion center on both Microsoft Azure and Amazon Web Services and deliver a multi-cloud strategy for enterprise customers. And you will find out how to create a vendor-neutral environment with rapid disaster recovery capability for maximum risk mitigation. With this book you'll learn: Key business and technical drivers of cybersecurity threat hunting frameworks in today's technological environment Metrics available to assess threat hunting effectiveness regardless of an organization's size How threat hunting works with vendor-specific single cloud security offerings and on multi-cloud implementations A detailed analysis of key threat vectors such as email phishing, ransomware and nation state attacks Comprehensive AWS and Azure "how to" solutions through the lens of MITRE Threat Hunting Framework Tactics, Techniques and Procedures (TTPs) Azure and AWS risk mitigation strategies to combat key TTPs such as privilege escalation, credential theft, lateral movement, defend against command & control systems, and prevent data exfiltration Tools available on both the Azure and AWS cloud platforms which provide automated responses to attacks, and orchestrate preventative measures and recovery strategies Many critical components for successful adoption of multi-cloud threat hunting framework such as Threat Hunting Maturity Model, Zero Trust Computing, Human Elements of Threat Hunting, Integration of Threat Hunting with Security Operation Centers (SOCs) and Cyber Fusion Centers The Future of Threat Hunting with the advances in Artificial Intelligence, Machine Learning, Quantum Computing and the proliferation of IoT devices. Perfect for technical executives (i.e., CTO, CISO), technical managers, architects, system admins and consultants with hands-on responsibility for cloud platforms, Threat Hunting in the Cloud is also an indispensable guide for business executives (i.e., CFO, COO CEO, board members) and managers who need to understand their organization's cybersecurity risk framework and mitigation strategy.



Aws Certified Data Analytics Study Guide With Online Labs


Aws Certified Data Analytics Study Guide With Online Labs
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Author : Asif Abbasi
language : en
Publisher: John Wiley & Sons
Release Date : 2021-04-13

Aws Certified Data Analytics Study Guide With Online Labs written by Asif Abbasi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-13 with Computers categories.


Virtual, hands-on learning labs allow you to apply your technical skills in realistic environments. So Sybex has bundled AWS labs from XtremeLabs with our popular AWS Certified Data Analytics Study Guide to give you the same experience working in these labs as you prepare for the Certified Data Analytics Exam that you would face in a real-life application. These labs in addition to the book are a proven way to prepare for the certification and for work as an AWS Data Analyst. AWS Certified Data Analytics Study Guide: Specialty (DAS-C01) Exam is intended for individuals who perform in a data analytics-focused role. This UPDATED exam validates an examinee's comprehensive understanding of using AWS services to design, build, secure, and maintain analytics solutions that provide insight from data. It assesses an examinee's ability to define AWS data analytics services and understand how they integrate with each other; and explain how AWS data analytics services fit in the data lifecycle of collection, storage, processing, and visualization. The book focuses on the following domains: • Collection • Storage and Data Management • Processing • Analysis and Visualization • Data Security This is your opportunity to take the next step in your career by expanding and validating your skills on the AWS cloud. AWS is the frontrunner in cloud computing products and services, and the AWS Certified Data Analytics Study Guide: Specialty exam will get you fully prepared through expert content, and real-world knowledge, key exam essentials, chapter review questions, and much more. Written by an AWS subject-matter expert, this study guide covers exam concepts, and provides key review on exam topics. Readers will also have access to Sybex's superior online interactive learning environment and test bank, including chapter tests, practice exams, a glossary of key terms, and electronic flashcards. And included with this version of the book, XtremeLabs virtual labs that run from your browser. The registration code is included with the book and gives you 6 months of unlimited access to XtremeLabs AWS Certified Data Analytics Labs with 3 unique lab modules based on the book.



Azure Data Factory Cookbook


Azure Data Factory Cookbook
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Author : Dmitry Anoshin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-12-24

Azure Data Factory Cookbook written by Dmitry Anoshin 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 2020-12-24 with Computers categories.


Solve real-world data problems and create data-driven workflows for easy data movement and processing at scale with Azure Data Factory Key FeaturesLearn how to load and transform data from various sources, both on-premises and on cloudUse Azure Data Factory’s visual environment to build and manage hybrid ETL pipelinesDiscover how to prepare, transform, process, and enrich data to generate key insightsBook Description Azure Data Factory (ADF) is a modern data integration tool available on Microsoft Azure. This Azure Data Factory Cookbook helps you get up and running by showing you how to create and execute your first job in ADF. You’ll learn how to branch and chain activities, create custom activities, and schedule pipelines. This book will help you to discover the benefits of cloud data warehousing, Azure Synapse Analytics, and Azure Data Lake Gen2 Storage, which are frequently used for big data analytics. With practical recipes, you’ll learn how to actively engage with analytical tools from Azure Data Services and leverage your on-premise infrastructure with cloud-native tools to get relevant business insights. As you advance, you’ll be able to integrate the most commonly used Azure Services into ADF and understand how Azure services can be useful in designing ETL pipelines. The book will take you through the common errors that you may encounter while working with ADF and show you how to use the Azure portal to monitor pipelines. You’ll also understand error messages and resolve problems in connectors and data flows with the debugging capabilities of ADF. By the end of this book, you’ll be able to use ADF as the main ETL and orchestration tool for your data warehouse or data platform projects. What you will learnCreate an orchestration and transformation job in ADFDevelop, execute, and monitor data flows using Azure SynapseCreate big data pipelines using Azure Data Lake and ADFBuild a machine learning app with Apache Spark and ADFMigrate on-premises SSIS jobs to ADFIntegrate ADF with commonly used Azure services such as Azure ML, Azure Logic Apps, and Azure FunctionsRun big data compute jobs within HDInsight and Azure DatabricksCopy data from AWS S3 and Google Cloud Storage to Azure Storage using ADF's built-in connectorsWho this book is for This book is for ETL developers, data warehouse and ETL architects, software professionals, and anyone who wants to learn about the common and not-so-common challenges faced while developing traditional and hybrid ETL solutions using Microsoft's Azure Data Factory. You’ll also find this book useful if you are looking for recipes to improve or enhance your existing ETL pipelines. Basic knowledge of data warehousing is expected.



Data Modeling For Azure Data Services


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.



Azure Data Factory By Example


Azure Data Factory By Example
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Author : Richard Swinbank
language : en
Publisher: Springer Nature
Release Date : 2024-03-22

Azure Data Factory By Example written by Richard Swinbank and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-22 with Computers categories.


Data engineers who need to hit the ground running will use this book to build skills in Azure Data Factory v2 (ADF). The tutorial-first approach to ADF taken in this book gets you working from the first chapter, explaining key ideas naturally as you encounter them. From creating your first data factory to building complex, metadata-driven nested pipelines, the book guides you through essential concepts in Microsoft’s cloud-based ETL/ELT platform. It introduces components indispensable for the movement and transformation of data in the cloud. Then it demonstrates the tools necessary to orchestrate, monitor, and manage those components. This edition, updated for 2024, includes the latest developments to the Azure Data Factory service: Enhancements to existing pipeline activities such as Execute Pipeline, along with the introduction of new activities such as Script, and activities designed specifically to interact with Azure Synapse Analytics. Improvements to flow control provided by activity deactivation and the Fail activity. The introduction of reusable data flow components such as user-defined functions and flowlets. Extensions to integration runtime capabilities including Managed VNet support. The ability to trigger pipelines in response to custom events. Tools for implementing boilerplate processes such as change data capture and metadata-driven data copying. What You Will Learn Create pipelines, activities, datasets, and linked services Build reusable components using variables, parameters, and expressions Move data into and around Azure services automatically Transform data natively using ADF data flows and Power Query data wrangling Master flow-of-control and triggers for tightly orchestrated pipeline execution Publish and monitor pipelines easily and with confidence Who This Book Is For Data engineers and ETL developers taking their first steps in Azure Data Factory, SQL Server Integration Services users making the transition toward doing ETL in Microsoft’s Azure cloud, and SQL Server database administrators involved in data warehousing and ETL operations



Azure Data Engineer Associate Certification Guide


Azure Data Engineer Associate Certification Guide
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Author : Newton Alex
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-02-28

Azure Data Engineer Associate Certification Guide written by Newton Alex 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 2022-02-28 with Computers categories.


Become well-versed with data engineering concepts and exam objectives to achieve Azure Data Engineer Associate certification Key Features Understand and apply data engineering concepts to real-world problems and prepare for the DP-203 certification exam Explore the various Azure services for building end-to-end data solutions Gain a solid understanding of building secure and sustainable data solutions using Azure services Book DescriptionAzure is one of the leading cloud providers in the world, providing numerous services for data hosting and data processing. Most of the companies today are either cloud-native or are migrating to the cloud much faster than ever. This has led to an explosion of data engineering jobs, with aspiring and experienced data engineers trying to outshine each other. Gaining the DP-203: Azure Data Engineer Associate certification is a sure-fire way of showing future employers that you have what it takes to become an Azure Data Engineer. This book will help you prepare for the DP-203 examination in a structured way, covering all the topics specified in the syllabus with detailed explanations and exam tips. The book starts by covering the fundamentals of Azure, and then takes the example of a hypothetical company and walks you through the various stages of building data engineering solutions. Throughout the chapters, you'll learn about the various Azure components involved in building the data systems and will explore them using a wide range of real-world use cases. Finally, you’ll work on sample questions and answers to familiarize yourself with the pattern of the exam. By the end of this Azure book, you'll have gained the confidence you need to pass the DP-203 exam with ease and land your dream job in data engineering.What you will learn Gain intermediate-level knowledge of Azure the data infrastructure Design and implement data lake solutions with batch and stream pipelines Identify the partition strategies available in Azure storage technologies Implement different table geometries in Azure Synapse Analytics Use the transformations available in T-SQL, Spark, and Azure Data Factory Use Azure Databricks or Synapse Spark to process data using Notebooks Design security using RBAC, ACL, encryption, data masking, and more Monitor and optimize data pipelines with debugging tips Who this book is for This book is for data engineers who want to take the DP-203: Azure Data Engineer Associate exam and are looking to gain in-depth knowledge of the Azure cloud stack. The book will also help engineers and product managers who are new to Azure or interviewing with companies working on Azure technologies, to get hands-on experience of Azure data technologies. A basic understanding of cloud technologies, extract, transform, and load (ETL), and databases will help you get the most out of this book.