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azure data factory cost optimization: Azure Data Factory Cookbook Dmitry Foshin, Tonya Chernyshova, Dmitry Anoshin, Xenia Ireton, 2024-02-28 Data Engineers guide to solve real-world problems encountered while building and transforming data pipelines using Azure's data integration tool Key Features Solve real-world data problems and create data-driven workflows with ease using Azure Data Factory Build an ADF pipeline that operates on pre-built ML model and Azure AI Get up and running with Fabric Data Explorer and extend ADF with Logic Apps and Azure functions Book DescriptionThis new edition of the Azure Data Factory book, fully updated to reflect ADS V2, will help you get up and running by showing you how to create and execute your first job in ADF. There are updated and new recipes throughout the book based on developments happening in Azure Synapse, Deployment with Azure DevOps, and Azure Purview. The current edition also runs you through Fabric Data Factory, Data Explorer, and some industry-grade best practices with specific chapters on each. You’ll learn how to branch and chain activities, create custom activities, and schedule pipelines, as well as discover the benefits of cloud data warehousing, Azure Synapse Analytics, and Azure Data Lake Gen2 Storage. With practical recipes, you’ll learn how to actively engage with analytical tools from Azure Data Services and leverage your on-premises infrastructure with cloud-native tools to get relevant business insights. You'll familiarize yourself with the common errors that you may encounter while working with ADF and find out the solutions to them. 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 with its latest advancements as the main ETL and orchestration tool for your data warehouse projects.What you will learn Build and Manage data pipelines with ease using the latest version of ADF Configure, load data, and operate data flows with Azure Synapse Get up and running with Fabric Data Factory Working with Azure Data Factory and Azure Purview Create big data pipelines using Databricks and Delta tables Integrate ADF with commonly used Azure services such as Azure ML, Azure Logic Apps, and Azure Functions Learn industry-grade best practices for using Azure Data Factory Who this book is for This book is for ETL developers, data warehouse and ETL architects, software professionals, and anyone else 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 a prerequisite. |
azure data factory cost optimization: Mastering Azure Synapse Analytics: guide to modern data integration Sultan Yerbulatov, 2024-06-26 Drawing from my extensive hands-on experience as a data engineer, this book presents a deep exploration of Azure Synapse Analytics through detailed explanations, practical examples, and expert insights. Readers will learn to navigate the complexities of modern data analytics, from data ingestion and transformation to dynamic data masking and compliance reporting. |
azure data factory cost optimization: Hands-On Azure Data Platform Sagar Lad, Abhishek Mishra, Ashirwad Satapathi, 2022-02-10 Plan, build, deploy, and monitor data solutions on Azure KEY FEATURES ● Work with PostgreSQL, MySQL, and CosmosDB databases on Microsoft Azure. ● Work with whole data architecture, leverage Azure Storage, Azure Synapse, and Azure Data Lake. ● Data integration strategies with Azure Data Factory and Data Bricks. DESCRIPTION 'Hands-On Azure Data Platform' helps readers get a fundamental understanding of the Database, Data Warehouse, and Data Lake and their management on the Azure Data Platform. The book describes how to work efficiently with Relational and Non-Relational Databases, Azure Synapse Analytics, and Azure Data Lake. The readers will use Azure Databricks and Azure Data Factory to experience data processing and transformation. The book delves deeply into topics like continuous integration, continuous delivery, and the use of Azure DevOps. The book focuses on the integration of Azure DevOps with CI/CD pipelines for data ops solutions. The book teaches readers how to migrate data from an on-premises system or another cloud service provider to Azure. After reading the book, readers will develop end-to-end data solutions using the Azure data platform. Additionally, data engineers and ETL developers can streamline their ETL operations using various efficient Azure services. WHAT YOU WILL LEARN ● In-depth knowledge of the principles of the data warehouse and the data lake. ● Acquaint yourself with Azure Storage Files, Blobs, and Queues. ● Create relational databases on the Azure platform using SQL, PostgreSQL, and MySQL. ● With Cosmos DB, you can create extremely scalable databases and data warehouses. ● Utilize Azure Databricks and Data Factory to develop data integration solutions. WHO THIS BOOK IS FOR This book is designed for big data engineers, data architects, and cloud engineers who want to understand how to use the Azure Data Platform to build enterprise-grade solutions. Learning about databases and the Azure Data Platform would be helpful but not necessary. TABLE OF CONTENTS 1. Getting Started with the Azure Data Platform 2. Working with Relational Databases on Azure 3. Working with Azure Synapse Analytics 4. Working with Azure Data Lake 5. Working with Azure Cosmos DB 6. Working with Azure Databricks 7. Working with Azure Data Factory 8. DevOps with the Azure Data Platform 9. Planning and Migrating On-Premises Azure Workloads to the Azure Data platform 10. Design and Implement Data Solutions on Azure |
azure data factory cost optimization: Practical Guide to Azure Cognitive Services Chris Seferlis, Christopher Nellis, Andy Roberts, 2023-05-12 Streamline your complex processes and optimize your organization's operational efficiency, cost-effectiveness, and customer experience by unlocking the potential of Microsoft Azure Cognitive Services and OpenAI Purchase of the print or Kindle book includes a free PDF eBook Key Features Minimize costs and maximize operations by automating mundane activities using AI tools Ideate solutions using real-world examples for manufacturing process improvement with AI Master TCO and ROI analysis for implementing AI solutions, automating operations, and ideating innovative manufacturing solutions with real-world examples Book Description Azure Cognitive Services and OpenAI are a set of pre-built artificial intelligence (AI) solution APIs that can be leveraged from existing applications, allowing customers to take advantage of Microsoft's award-winning Vision, Speech, Text, Decision, and GPT-4 AI capabilities. With Practical Guide to Azure Cognitive Services, you'll work through industry-specific examples of implementations to get a head-start in your production journey. You'll begin with an overview of the categorization of Azure Cognitive Services and the benefits of embracing AI solutions for practical business applications. After that, you'll explore the benefits of using Azure Cognitive Services to optimize efficiency and improve predictive capabilities. Then, you'll learn how to leverage Vision capabilities for quality control, Form Recognizer to streamline supply chain nuances, language understanding to improve customer service, and Cognitive Search for next-generation knowledge-mining solutions. By the end of this book, you'll be able to implement various Cognitive Services solutions that will help you enhance efficiency, reduce costs, and improve the customer experience at your organization. You'll also be well equipped to automate mundane tasks by reaping the full potential of OpenAI. What you will learn Master cost-effective deployment of Azure Cognitive Services Develop proven solutions from an architecture and development standpoint Understand how Cognitive Services are deployed and customized Evaluate various uses of Cognitive Services with different mediums Disseminate Azure costs for Cognitive Services workloads smoothly Deploy next-generation Knowledge Mining solutions with Cognitive Search Explore the current and future journey of OpenAI Understand the value proposition of different AI projects Who this book is for This book is for data scientists, technology leaders, and software engineers looking to implement Azure Cognitive Services with the help of sample use cases derived from success stories. Experience with Python as well as an overall understanding of the Azure Portal with related services such as Azure Data Lake Storage and Azure Functions will help you make the most of this book. |
azure data factory cost optimization: Azure Data Factory by Example Richard Swinbank, |
azure data factory cost optimization: Optimizing Databricks Workloads Anirudh Kala, Anshul Bhatnagar, Sarthak Sarbahi, 2021-12-24 Accelerate computations and make the most of your data effectively and efficiently on Databricks Key FeaturesUnderstand Spark optimizations for big data workloads and maximizing performanceBuild efficient big data engineering pipelines with Databricks and Delta LakeEfficiently manage Spark clusters for big data processingBook Description Databricks is an industry-leading, cloud-based platform for data analytics, data science, and data engineering supporting thousands of organizations across the world in their data journey. It is a fast, easy, and collaborative Apache Spark-based big data analytics platform for data science and data engineering in the cloud. In Optimizing Databricks Workloads, you will get started with a brief introduction to Azure Databricks and quickly begin to understand the important optimization techniques. The book covers how to select the optimal Spark cluster configuration for running big data processing and workloads in Databricks, some very useful optimization techniques for Spark DataFrames, best practices for optimizing Delta Lake, and techniques to optimize Spark jobs through Spark core. It contains an opportunity to learn about some of the real-world scenarios where optimizing workloads in Databricks has helped organizations increase performance and save costs across various domains. By the end of this book, you will be prepared with the necessary toolkit to speed up your Spark jobs and process your data more efficiently. What you will learnGet to grips with Spark fundamentals and the Databricks platformProcess big data using the Spark DataFrame API with Delta LakeAnalyze data using graph processing in DatabricksUse MLflow to manage machine learning life cycles in DatabricksFind out how to choose the right cluster configuration for your workloadsExplore file compaction and clustering methods to tune Delta tablesDiscover advanced optimization techniques to speed up Spark jobsWho this book is for This book is for data engineers, data scientists, and cloud architects who have working knowledge of Spark/Databricks and some basic understanding of data engineering principles. Readers will need to have a working knowledge of Python, and some experience of SQL in PySpark and Spark SQL is beneficial. |
azure data factory cost optimization: Azure Data Factory Cookbook Dmitry Anoshin, Dmitry Foshin, Roman Storchak, Xenia Ireton, 2020-12-24 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. |
azure data factory cost optimization: Microsoft Certified Exam guide - Azure Data Engineer Associate (DP-203) Cybellium Ltd, Unlock the Power of Data with Azure Data Engineering! Are you ready to become a Microsoft Azure Data Engineer Associate and harness the transformative potential of data in the cloud? Look no further than the Microsoft Certified Exam Guide - Azure Data Engineer Associate (DP-203). This comprehensive book is your ultimate companion on the journey to mastering Azure data engineering and acing the DP-203 exam. In today's data-driven world, organizations depend on the efficient management, processing, and analysis of data to make critical decisions and drive innovation. Microsoft Azure provides a cutting-edge platform for data engineers to design and implement data solutions, and the demand for skilled professionals in this field is soaring. Whether you're an experienced data engineer or just starting your journey, this book equips you with the knowledge and skills needed to excel in Azure data engineering. Inside this book, you will discover: ✔ Comprehensive Coverage: A deep dive into all the key concepts, tools, and best practices required for designing, building, and maintaining data solutions on Azure. ✔ Real-World Scenarios: Practical examples and case studies that illustrate how Azure is used to solve complex data challenges, making learning engaging and relevant. ✔ Exam-Ready Preparation: Thorough coverage of DP-203 exam objectives, complete with practice questions and expert tips to ensure you're well-prepared for exam day. ✔ Proven Expertise: Authored by Azure data engineering professionals who hold the certification and have hands-on experience in developing data solutions, offering you invaluable insights and practical guidance. Whether you aspire to advance your career, validate your expertise, or simply become a proficient Azure Data Engineer, Microsoft Certified Exam Guide - Azure Data Engineer Associate (DP-203) is your trusted companion on this journey. Don't miss this opportunity to become a sought-after data engineering expert in a competitive job market. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com |
azure data factory cost optimization: A Developer's Guide to Building Resilient Cloud Applications with Azure Hamida Rebai Trabelsi, Lori Lalonde, 2023-02-24 Successfully modernize your apps on Azure using APIs, event-driven systems, functions, and Service Fabric and connect them to different relational and non-relational databases Purchase of the print or Kindle book includes a free PDF eBook Key FeaturesUnderstand Function-as-a-Service and Azure Service Fabric for distributed applicationsDevelop event-based and message-based solutions using Event Grid and Azure Event HubsExplore continuous deployment for Docker with Azure DevOps and integrate Docker Hub with CI/CD pipelinesBook Description To deliver software at a faster rate and reduced costs, companies with stable legacy systems and growing data volumes are trying to modernize their applications and accelerate innovation, but this is no easy matter. A Developer's Guide to Building Resilient Cloud Applications with Azure helps you overcome these application modernization challenges to build secure and reliable cloud-based applications on Azure and connect them to databases with the help of easy-to-follow examples. The book begins with a basic definition of serverless and event-driven architecture and Database-as-a-Service, before moving on to an exploration of the different services in Azure, namely Azure API Management using the gateway pattern, event-driven architecture, Event Grid, Azure Event Hubs, Azure message queues, FaaS using Azure Functions, and the database-oriented cloud. Throughout the chapters, you'll learn about creating, importing, and managing APIs and Service Fabric in Azure, and discover how to ensure continuous integration and deployment in Azure to fully automate the software delivery process, that is, the build and release process. By the end of this book, you'll be able to build and deploy cloud-oriented applications using APIs, serverless, Service Fabric, Azure Functions, and Event Grid technologies. What you will learnUnderstand the architecture of Azure Functions and Azure Service FabricExplore Platform-as-a-Service options for deploying SQL Server in AzureCreate and manage Azure Storage and Azure Cosmos DB resourcesLeverage big data storage in Azure servicesSelect Azure services to deploy according to a specific scenarioSet up CI/CD pipelines to deploy container applications on Azure DevOpsGet to grips with API gateway patterns and Azure API ManagementWho this book is for This book is for cloud developers, software architects, system administrators, database administrators, data engineers, developers, and computer science students who want to understand the role of the software architect or developer in the cloud world. Professionals looking to enhance their cloud and cloud-native programming concepts on Azure will also find this book useful. A solid background in C#, ASP.NET Core, and any recent version of Visual Studio and basic knowledge of cloud computing, Microsoft Azure, and databases will be helpful when using this book. |
azure data factory cost optimization: The Definitive Guide to Data Integration Pierre-Yves BONNEFOY, Emeric CHAIZE, Raphaël MANSUY, Mehdi TAZI, 2024-03-29 Learn the essentials of data integration with this comprehensive guide, covering everything from sources to solutions, and discover the key to making the most of your data stack Key Features Learn how to leverage modern data stack tools and technologies for effective data integration Design and implement data integration solutions with practical advice and best practices Focus on modern technologies such as cloud-based architectures, real-time data processing, and open-source tools and technologies Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe Definitive Guide to Data Integration is an indispensable resource for navigating the complexities of modern data integration. Focusing on the latest tools, techniques, and best practices, this guide helps you master data integration and unleash the full potential of your data. This comprehensive guide begins by examining the challenges and key concepts of data integration, such as managing huge volumes of data and dealing with the different data types. You’ll gain a deep understanding of the modern data stack and its architecture, as well as the pivotal role of open-source technologies in shaping the data landscape. Delving into the layers of the modern data stack, you’ll cover data sources, types, storage, integration techniques, transformation, and processing. The book also offers insights into data exposition and APIs, ingestion and storage strategies, data preparation and analysis, workflow management, monitoring, data quality, and governance. Packed with practical use cases, real-world examples, and a glimpse into the future of data integration, The Definitive Guide to Data Integration is an essential resource for data eclectics. By the end of this book, you’ll have the gained the knowledge and skills needed to optimize your data usage and excel in the ever-evolving world of data.What you will learn Discover the evolving architecture and technologies shaping data integration Process large data volumes efficiently with data warehousing Tackle the complexities of integrating large datasets from diverse sources Harness the power of data warehousing for efficient data storage and processing Design and optimize effective data integration solutions Explore data governance principles and compliance requirements Who this book is for This book is perfect for data engineers, data architects, data analysts, and IT professionals looking to gain a comprehensive understanding of data integration in the modern era. Whether you’re a beginner or an experienced professional enhancing your knowledge of the modern data stack, this definitive guide will help you navigate the data integration landscape. |
azure data factory cost optimization: The Road to Azure Cost Governance Paola E. Annis, Giuliano Caglio, Marco Barra Caracciolo, 2022-02-18 Get to grips with Microsoft Azure cost management and gain complete, reliable, and sustainable control of your cloud spend Key FeaturesExplore resource rightsizing and cleanup methods and their implementationLearn key resource usage optimization conceptsUnderstand app optimization and plan for optimized and sustainable cloud native applicationsBook Description Cloud teams and ICT cost controllers working with Azure will be able to put their knowledge to work with this practical guide, introducing a process model for structured cost governance. The Road to Azure Cost Governance is a must-read if you find yourself facing the harsh reality of monthly cloud costs gradually getting out of control. Starting with how resources are created and managed, everything you need to know in order to track, display, optimize, rightsize, and clean up cloud resources will be tackled with a workflow approach that will leave the choice of operation to you (be it the Azure CLI, automation, logic apps, or even custom code). Using real-world datasets, you'll learn everything from basic cost management to modeling your cloud spend across your technical resources in a sustainable way. The book will also show you how to create a recursive optimization process that will give you full control of spending and savings, while helping you reserve budget for future cloud projects and innovation. By the end of this Azure book, you'll have a clear understanding and control of your cloud spend along with knowledge of a number of cost-saving techniques used by companies around the world, application optimization patterns, and the carbon impact of your cloud infrastructure. What you will learnUse Azure reporting, monitoring, and configurations to model your cloud resources and make costs clearerDiscover resource-saving techniques and put them into practiceEstablish a continuous clean-up and rightsizing processExplore and implement automation to drive recurrent savingsFind out how to use Azure Reservations in the best possible wayGet started with building cloud native, cost-optimized applicationsGet to grips with implementing cost- and carbon-aware applications on AzureWho this book is for If you're someone who deals with Azure cloud costs and has a technical background, this book will help you understand and control your cloud spending. This book is for decision-makers, cloud managers, cloud architects, cost controllers, and software solution professionals working with Microsoft cloud services in Azure and looking to build optimized solutions for their enterprise operations. |
azure data factory cost optimization: Microsoft Certified: Azure Data Scientist Associate (DP-100) , Welcome to the forefront of knowledge with Cybellium, your trusted partner in mastering the cutting-edge fields of IT, Artificial Intelligence, Cyber Security, Business, Economics and Science. Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com |
azure data factory cost optimization: Hands-On Data Warehousing with Azure Data Factory Christian Coté, Michelle Kamrat Gutzait, Giuseppe Ciaburro, 2018-05-31 Leverage the power of Microsoft Azure Data Factory v2 to build hybrid data solutions Key Features Combine the power of Azure Data Factory v2 and SQL Server Integration Services Design and enhance performance and scalability of a modern ETL hybrid solution Interact with the loaded data in data warehouse and data lake using Power BI Book Description ETL is one of the essential techniques in data processing. Given data is everywhere, ETL will always be the vital process to handle data from different sources. Hands-On Data Warehousing with Azure Data Factory starts with the basic concepts of data warehousing and ETL process. You will learn how Azure Data Factory and SSIS can be used to understand the key components of an ETL solution. You will go through different services offered by Azure that can be used by ADF and SSIS, such as Azure Data Lake Analytics, Machine Learning and Databrick’s Spark with the help of practical examples. You will explore how to design and implement ETL hybrid solutions using different integration services with a step-by-step approach. Once you get to grips with all this, you will use Power BI to interact with data coming from different sources in order to reveal valuable insights. By the end of this book, you will not only learn how to build your own ETL solutions but also address the key challenges that are faced while building them. What you will learn Understand the key components of an ETL solution using Azure Data Factory and Integration Services Design the architecture of a modern ETL hybrid solution Implement ETL solutions for both on-premises and Azure data Improve the performance and scalability of your ETL solution Gain thorough knowledge of new capabilities and features added to Azure Data Factory and Integration Services Who this book is for This book is for you if you are a software professional who develops and implements ETL solutions using Microsoft SQL Server or Azure cloud. It will be an added advantage if you are a software engineer, DW/ETL architect, or ETL developer, and know how to create a new ETL implementation or enhance an existing one with ADF or SSIS. |
azure data factory cost optimization: Mastering Data Ingestion Cybellium Ltd, Efficiently Capture and Prepare Data for Analysis Are you ready to optimize the way your organization captures and prepares data for analysis? Mastering Data Ingestion is your definitive guide to mastering the art of efficiently collecting, transforming, and organizing data for insights. Whether you're a data engineer streamlining data pipelines or a business leader aiming to leverage accurate information, this book equips you with the knowledge and strategies to excel in data ingestion. Key Features: 1. Enter the World of Data Ingestion: Immerse yourself in the realm of data ingestion, understanding its significance, challenges, and opportunities. Build a strong foundation that empowers you to design seamless processes for data collection. 2. Data Collection Techniques: Master various data collection techniques. Learn about batch processing, real-time streaming, and event-driven approaches for ingesting data from diverse sources. 3. Data Transformation and Enrichment: Delve into data transformation and enrichment during ingestion. Explore techniques for cleansing, structuring, and augmenting data to ensure its quality and usability. 4. Ingestion Patterns and Architectures: Uncover the power of data ingestion patterns and architectures. Learn how to design scalable and fault-tolerant data pipelines that handle high volumes of information. 5. Data Formats and Serialization: Explore data formats and serialization techniques. Learn how to handle diverse data structures, choose appropriate serialization methods, and ensure interoperability. 6. Ingestion Tools and Platforms: Discover a range of tools and platforms for data ingestion. Explore ETL (Extract, Transform, Load) tools, message brokers, and cloud-based services for efficient data movement. 7. Real-Time Data Ingestion: Master real-time data ingestion techniques. Learn how to capture and process streaming data for instant insights and timely decision-making. 8. Data Ingestion Best Practices: Delve into best practices for successful data ingestion projects. Learn how to handle data schema evolution, ensure data integrity, and optimize performance. 9. Cloud Data Ingestion: Explore cloud-based data ingestion strategies. Learn how to ingest data from cloud services, integrate with cloud databases, and leverage serverless architectures. 10. Real-World Applications: Gain insights into real-world use cases of data ingestion across industries. From IoT data streams to social media feeds, discover how organizations leverage efficient data collection for competitive advantage. Who This Book Is For: Mastering Data Ingestion is an essential resource for data engineers, analysts, and business professionals aiming to excel in efficiently collecting and preparing data for analysis. Whether you're enhancing your technical skills or optimizing data workflows, this book will guide you through the intricacies and empower you to harness the full potential of data ingestion. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com |
azure data factory cost optimization: Microsoft Certified Exam guide - Azure Solutions Architect Expert (AZ-303 and AZ-304) Cybellium Ltd, Unlock Your Azure Solutions Architect Expert Potential! Are you ready to elevate your career and become a Microsoft Azure Solutions Architect Expert? Look no further! Microsoft Certified Exam Guide - Azure Solutions Architect Expert (AZ-303 and AZ-304) is your comprehensive roadmap to success in the exciting world of Azure cloud computing. In today's rapidly evolving tech landscape, Azure has emerged as a dominant force, and Azure Solutions Architects are in high demand. Whether you're a seasoned IT professional or just starting your cloud journey, this book provides the knowledge and skills you need to excel in AZ-303 and AZ-304 exams, setting you on the path to achieving Expert certification. Inside this book, you will find: ✔ In-Depth Coverage: A detailed exploration of all the key concepts, skills, and best practices needed to design and manage complex Azure solutions. ✔ Real-World Scenarios: Practical examples and case studies that illustrate how to solve real-world challenges using Azure services and solutions. ✔ Exam-Ready Preparation: Thorough coverage of exam objectives, along with practice questions and tips to help you ace the AZ-303 and AZ-304 exams. ✔ Architectural Insights: Gain a deep understanding of Azure architecture and learn how to design robust, secure, and scalable solutions. ✔ Expert Guidance: Written by experienced Azure professionals who have not only passed the exams but have also worked in the field, bringing you valuable insights and practical wisdom. Whether you're looking to enhance your skills, advance your career, or simply master the Azure cloud platform, Microsoft Certified Exam Guide - Azure Solutions Architect Expert (AZ-303 and AZ-304) is your trusted companion on the journey to becoming an Azure Solutions Architect Expert. Don't miss this opportunity to take your Azure expertise to the next level! Prepare, practice, and succeed with the ultimate resource for Azure Solutions Architect Expert certification. Order your copy today and embrace the limitless possibilities of the cloud! © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com |
azure data factory cost optimization: AI Fundamentals Courseware Reinier van den Biggelaar, 2023-09-26 The AI Fundamentals courseware offers an AI training course designed for professionals in business or government environments who want to understand the benefits and applications of AI in their work environment. This course covers topics such as data management for AI, building and assessing AI applications, ethics and trustworthiness, and organizational success factors for enabling humans and machines to work together. The course addresses key questions such as “Where does Data Management end and AI application begin?” from a management perspective. Subjects covered include the applications and benefits of AI, data and robots, predictions and algorithms, machine and deep learning, building and reviewing AI applications, data management for AI, ethics and trustworthiness, organizational success factors for helping humans and machines work together, and the future of AI. This courseware educates for three certifications within it’s three-day combined program. It’s also possible to cut the material in pieces for a module teaching approach. The EXIN BCS Artificial Intelligence Essentials, testing the fundamental concepts of AI. This AI for Business and Government certification (the AI Brevet) which was established by the Netherlands AI Coalition (NL AIC) as a standard for professionals who want to use Artificial Intelligence. EXIN BCS Artificial Intelligence Foundation, which has a more IT-technical perspective. |
azure data factory cost optimization: Microsoft Azure Security Center Yuri Diogenes, Tom Shinder, 2018-06-04 Discover high-value Azure security insights, tips, and operational optimizations This book presents comprehensive Azure Security Center techniques for safeguarding cloud and hybrid environments. Leading Microsoft security and cloud experts Yuri Diogenes and Dr. Thomas Shinder show how to apply Azure Security Center’s full spectrum of features and capabilities to address protection, detection, and response in key operational scenarios. You’ll learn how to secure any Azure workload, and optimize virtually all facets of modern security, from policies and identity to incident response and risk management. Whatever your role in Azure security, you’ll learn how to save hours, days, or even weeks by solving problems in most efficient, reliable ways possible. Two of Microsoft’s leading cloud security experts show how to: • Assess the impact of cloud and hybrid environments on security, compliance, operations, data protection, and risk management • Master a new security paradigm for a world without traditional perimeters • Gain visibility and control to secure compute, network, storage, and application workloads • Incorporate Azure Security Center into your security operations center • Integrate Azure Security Center with Azure AD Identity Protection Center and third-party solutions • Adapt Azure Security Center’s built-in policies and definitions for your organization • Perform security assessments and implement Azure Security Center recommendations • Use incident response features to detect, investigate, and address threats • Create high-fidelity fusion alerts to focus attention on your most urgent security issues • Implement application whitelisting and just-in-time VM access • Monitor user behavior and access, and investigate compromised or misused credentials • Customize and perform operating system security baseline assessments • Leverage integrated threat intelligence to identify known bad actors |
azure data factory cost optimization: Exam Prep AZ-305 Lalit Rawat, 2024-07-24 DESCRIPTION “Exam Prep AZ-305: Designing Microsoft Azure Infrastructure Solutions” book is a comprehensive guide for IT professionals preparing for the Microsoft Azure AZ-305 certification exam. This book offers detailed insights into designing scalable, secure, and resilient infrastructure solutions on the Azure platform, aligning with the latest exam objectives. It covers critical topics such as designing governance, security, storage, and networking solutions, ensuring readers have the necessary knowledge to architect effective Azure solutions. Through a blend of theoretical concepts and practical exercises, this guide equips readers with the skills needed to apply Azure best practices in real-world scenarios. Each chapter covers specific areas of infrastructure design, providing step-by-step instructions, expert tips, and real-life examples to illustrate complex concepts. This practical approach not only helps in mastering the exam content but also enhances the reader's ability to solve real-world challenges in their job roles. It not only prepares you for certification but also empowers you to design and implement robust Azure infrastructure solutions, thereby enhancing your capabilities and career prospects in the evolving field of cloud technology. KEY FEATURES ● Expertise in Azure networking, storage, compute, identity management, monitoring, security, hybrid cloud solutions, and disaster recovery. ● Learn to design and implement robust Azure infrastructure solutions. ● Prepare for the AZ-305 Azure Infrastructure Architect certification exam. ● Utilize up-to-date Microsoft AZ-305 curriculum. WHAT YOU WILL LEARN ● Master Azure governance principles. ● Design secure authentication and authorization solutions. ● Architect scalable compute solutions on Azure. ● Implement effective data storage and integration strategies. ● Design robust backup and disaster recovery solutions. ● Learn key migration strategies for transitioning to Azure. WHO THIS BOOK IS FOR Whether you are an aspiring cloud architect, a seasoned IT professional, or someone looking to advance their career in cloud computing, this book serves as an essential resource. TABLE OF CONTENTS 1. Designing Governance 2. Designing Authentication and Authorization Solutions 3. Designing a Solution Monitor of Azure Resources 4. Designing an Azure Compute Solution 5. Designing a Data Storage Solution for Non-relational Data 6. Designing Data Integration 7. Designing Data Storage Solutions for Relational Data 8. Designing Network Solutions 9. Designing a Solution for Backup and Disaster Recovery 10. Designing Migration 11. Azure Well-Architected Framework 12. Exam Preparation Guidelines and Assessment Questions 13. Azure Architect Exam Mock Test |
azure data factory cost optimization: Data Modeling for Azure Data Services Peter ter Braake, 2021-07-30 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 cost optimization: Azure FinOps Essentials Parag Bhardwaj, Arun Kumar Samayam, 2024-09-30 DESCRIPTION Azure FinOps, the intersection of finance, operations, and technology, has become paramount in optimizing cloud spending. “Azure FinOps Essentials “is a guide to help you navigate easily with cost management and optimization within Microsoft Cloud. This book is a practical guide to cutting cloud costs in Microsoft Azure. It covers everything from understanding Azure services and cost management to advanced strategies like Infrastructure as Code and serverless computing. You will learn to set up Azure Cost Management, optimize resources with tools like Reserved Instances, and enforce governance using Azure Policy. The book also highlights case studies and best practices to help you build a FinOps culture, streamline costs, and enhance cost-efficiency in your cloud environment. If you are new to cloud financial management or need a refresher on some of the best practices, Azure FinOps Essentials is designed for anyone running an operational workload in both public and private clouds who wants to improve their expense management within the environment. KEY FEATURES ● An in-depth guide to the fundamentals of Azure cost management. ● Detailed instructions for creating cost alerts and establishing budgets. ● Practical strategies to enhance cloud resource efficiency. WHAT YOU WILL LEARN ● Establish and enforce standards for Azure cloud cost management through auditing. ● Learn cost-saving tactics like rightsizing and using Reserved Instances. ● Master Azure tools for monitoring spending, budgeting, and setting up alerts. ● Build custom dashboards to accurately display key financial metrics. ● Implement governance and compliance for effective cloud financial management. WHO THIS BOOK IS FOR This book is for cloud architects, DevOps engineers and IT professionals managing costs in Azure environments. It provides the necessary knowledge and skills to optimize cloud spending, improve efficiency, and drive business value. TABLE OF CONTENTS 1. Introduction to Azure FinOps 2. Azure Fundamentals for FinOps 3. Azure Cost Management and Billing 4. Cost Optimization Strategies 5. Azure Monitoring 6. Cost Allocation and Chargebacks 7. Governance and Compliance 8. Advanced Azure FinOps Techniques 9. Azure FinOps Best Practices 10. Azure Case Studies and Real-world Examples 11. Future Trends and Innovations in Azure FinOps 12. Final Thoughts and Next Steps |
azure data factory cost optimization: Architecting IoT Solutions on Azure Blaize Stewart, 2024-01-09 How can you make sense of the complex IoT landscape? With dozens of components ranging from devices to metadata about the devices, it's easy to get lost among the possibilities. But it's not impossible if you have the right guide to help you navigate all the complexities. This practical book shows developers, architects, and IT managers how to build IoT solutions on Azure. Author Blaize Stewart presents a comprehensive view of the IoT landscape. You'll learn about devices, device management at scale, and the tools Azure provides for building globally distributed systems. You'll also explore ways to organize data by choosing the appropriate dataflow and data storage technologies. The final chapters examine data consumption and solutions for delivering data to consumers with Azure. Get the architectural guidance you need to create holistic solutions with devices, data, and everything in between. This book helps you: Meet the demands of an IoT solution with Azure-provided functionality Use Azure to create complete scalable and secure IoT systems Understand how to articulate IoT architecture and solutions Guide conversations around common problems that IoT applications solve Select the appropriate technologies in the Azure space to build IoT applications |
azure data factory cost optimization: Data Engineering Best Practices Richard J. Schiller, David Larochelle, 2024-10-11 Explore modern data engineering techniques and best practices to build scalable, efficient, and future-proof data processing systems across cloud platforms Key Features Architect and engineer optimized data solutions in the cloud with best practices for performance and cost-effectiveness Explore design patterns and use cases to balance roles, technology choices, and processes for a future-proof design Learn from experts to avoid common pitfalls in data engineering projects Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionRevolutionize your approach to data processing in the fast-paced business landscape with this essential guide to data engineering. Discover the power of scalable, efficient, and secure data solutions through expert guidance on data engineering principles and techniques. Written by two industry experts with over 60 years of combined experience, it offers deep insights into best practices, architecture, agile processes, and cloud-based pipelines. You’ll start by defining the challenges data engineers face and understand how this agile and future-proof comprehensive data solution architecture addresses them. As you explore the extensive toolkit, mastering the capabilities of various instruments, you’ll gain the knowledge needed for independent research. Covering everything you need, right from data engineering fundamentals, the guide uses real-world examples to illustrate potential solutions. It elevates your skills to architect scalable data systems, implement agile development processes, and design cloud-based data pipelines. The book further equips you with the knowledge to harness serverless computing and microservices to build resilient data applications. By the end, you'll be armed with the expertise to design and deliver high-performance data engineering solutions that are not only robust, efficient, and secure but also future-ready.What you will learn Architect scalable data solutions within a well-architected framework Implement agile software development processes tailored to your organization's needs Design cloud-based data pipelines for analytics, machine learning, and AI-ready data products Optimize data engineering capabilities to ensure performance and long-term business value Apply best practices for data security, privacy, and compliance Harness serverless computing and microservices to build resilient, scalable, and trustworthy data pipelines Who this book is for If you are a data engineer, ETL developer, or big data engineer who wants to master the principles and techniques of data engineering, this book is for you. A basic understanding of data engineering concepts, ETL processes, and big data technologies is expected. This book is also for professionals who want to explore advanced data engineering practices, including scalable data solutions, agile software development, and cloud-based data processing pipelines. |
azure data factory cost optimization: Efficient Cloud FinOps Alfonso San Miguel Sánchez, Danny Obando García, 2024-02-23 Explore cloud economics and cost optimization for Azure, AWS, and GCP with this practical guide covering methods, strategies, best practices, and real-world examples, bridging theory and application Key Features Learn cost optimization best practices on different cloud services using FinOps principles and examples Gain hands-on expertise in improving cost estimations and devising cost reduction plans for Azure, AWS, and GCP Analyze case studies that illustrate the application of FinOps in diverse real-world scenarios Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionIn response to the escalating challenges of cloud adoption, where balancing costs and maximizing cloud values is paramount, FinOps practices have emerged as the cornerstone of fi nancial optimization. This book serves as your comprehensive guide to understanding how FinOps is implemented in organizations worldwide through team collaboration and proper cloud governance. Presenting FinOps from a practical point of view, covering the three phases—inform, optimize, and operate—this book demonstrates an end-to-end methodology for optimizing costs and performing financial management in the cloud. You’ll learn how to design KPIs and dashboards for judicious cost allocation, covering key features of cloud services such as reserved instances, rightsizing, scaling, and automation for cost optimization. This book further simplifi es architectural concepts and best practices, enabling you to design superior and more optimized solutions. Finally, you’ll discover potential synergies and future challenges, from the integration of artifi cial intelligence to cloud sustainability considerations, to prepare for the future of cloud FinOps. By the end of this book, you’ll have built the expertise to seamlessly implement FinOps practices across major public clouds, armed with insights and ideas to propel your organization toward business growth.What you will learn Examine challenges in cloud adoption and cost optimization Gain insight into the integration of FinOps within organizations Explore the synergies between FinOps and DevOps, IaC, and change management Leverage tools such as Azure Advisor, AWS CUDOS, and GCP cost reports Estimate and optimize costs using cloud services key features and best practices Implement cost dashboards and reports to improve visibility and control Understand FinOps roles and processes crucial for organizational success Apply FinOps through real-life examples and multicloud architectures Who this book is for This book is for cloud engineers, cloud and solutions architects, as well as DevOps and SysOps engineers interested in learning more about FinOps and cloud financial management for efficiently architecting, designing, and operating software solutions and infrastructure using the public clouds. Additionally, team leads, project managers, and financial teams aiming to optimize cloud resources will also find this book useful. Prior knowledge of cloud computing and major public clouds is assumed. |
azure data factory cost optimization: Ultimate Azure Synapse Analytics Swapnil Mule, 2024-06-29 TAGLINE Empower Your Data Insights with Azure Synapse Analytics KEY FEATURES ● Leverage Azure Synapse Analytics for data warehousing, big data analytics, and machine learning in one environment. ● Integrate with Azure services like Azure Data Lake Storage and Azure Machine Learning to enhance analytics. ● Gain insights from real-world examples and best practices to solve complex data challenges. DESCRIPTION Unlock the full potential of Azure Synapse Analytics with Ultimate Azure Synapse Analytics, your definitive roadmap to mastering the art of data analytics in the cloud era. From the foundational concepts to advanced techniques, each chapter offers practical insights and hands-on tutorials to streamline your data workflows and drive actionable insights. Discover how Azure Synapse Analytics revolutionizes data processing and integration, empowering you to harness the vast capabilities of the Azure ecosystem. Seamlessly transition from traditional data warehousing to cutting-edge big data analytics, leveraging serverless and dedicated resources for optimal performance. Dive deep into Synapse SQL, explore advanced data engineering with Apache Spark, and delve into machine learning and DevOps practices to stay ahead in today's data-driven landscape. Whether you're seeking to optimize performance, ensure compliance, or facilitate seamless migration, this book provides the expertise needed to excel in your role. Gain valuable insights into industry best practices, enhance your data engineering skills, and drive innovation within your organization. WHAT WILL YOU LEARN ● Understand the significance of Azure Synapse Analytics in modern data analytics. ● Learn to set up and configure your Synapse workspace for efficient data processing. ● Dive into Synapse SQL and discover techniques for data exploration and analysis. ● Master advanced techniques for seamless data integration into Azure Synapse Analytics. ● Explore big data engineering concepts and leverage Apache Spark for scalable data processing. ● Discover how to implement machine learning models and algorithms using Synapse Analytics. ● Ensure data security and regulatory compliance with effective security measures in Azure Synapse Analytics. ● Optimize performance and efficiency through performance tuning strategies and optimization techniques. ● Implement DevOps practices for effective data engineering and continuous integration and deployment. ● Gain insights into best practices for successful implementation and migration to Azure Synapse Analytics for streamlined data operations. WHO IS THIS BOOK FOR? This comprehensive book is crafted for data engineers, analysts, architects, and developers eager to master Azure Synapse Analytics, providing practical insights and advanced techniques. Whether you're a novice or a seasoned professional in the field of data analytics, this book offers invaluable resources to elevate your skills. TABLE OF CONTENTS 1. The World of Azure Synapse Analytics 2. Setting Up the Synapse Workspace 3. Synapse SQL and Data Exploration 4. Data Integration Technique 5. Big Data Engineering with Apache Spark 6. Machine Learning with Synapse 7. Implementing Security and Compliance 8. Performance Tuning and Optimization 9. DevOps for Data Engineering 10. Ensuring Implementation Success and Effective Migration Index |
azure data factory cost optimization: Azure Data Engineer Associate Certification Guide Giacinto Palmieri, Surendra Mettapalli, Newton Alex, 2024-05-23 Achieve Azure Data Engineer Associate certification success with this DP-203 exam guide Purchase of this book unlocks access to web-based exam prep resources including mock exams, flashcards, and exam tips, and the eBook PDF Key Features Prepare for the DP-203 exam with expert insights, real-world examples, and practice resources Gain up-to-date skills to thrive in the dynamic world of cloud data engineering Build secure and sustainable data solutions using Azure services Book DescriptionOne of the top global cloud providers, Azure offers extensive data hosting and processing services, driving widespread cloud adoption and creating a high demand for skilled data engineers. The Azure Data Engineer Associate (DP-203) certification is a vital credential, demonstrating your proficiency as an Azure data engineer to prospective employers. This comprehensive exam guide is designed for both beginners and seasoned professionals, aligned with the latest DP-203 certification exam, to help you pass the exam on your first try. The book provides a foundational understanding of IaaS, PaaS, and SaaS, starting with core concepts like virtual machines (VMs), VNETS, and App Services and progressing to advanced topics such as data storage, processing, and security. What sets this exam guide apart is its hands-on approach, seamlessly integrating theory with practice through real-world examples, practical exercises, and insights into Azure's evolving ecosystem. Additionally, you'll unlock lifetime access to supplementary practice material on an online platform, including mock exams, interactive flashcards, and exam tips, ensuring a comprehensive exam prep experience. By the end of this book, you’ll not only be ready to excel in the DP-203 exam, but also be equipped to tackle complex challenges as an Azure data engineer.What you will learn Design and implement data lake solutions with batch and stream pipelines Secure data with masking, encryption, RBAC, and ACLs Perform standard extract, transform, and load (ETL) and analytics operations Implement different table geometries in Azure Synapse Analytics Write Spark code, design ADF pipelines, and handle batch and stream data Use Azure Databricks or Synapse Spark for data processing using Notebooks Leverage Synapse Analytics and Purview for comprehensive data exploration Confidently manage VMs, VNETS, App Services, and more Who this book is for This book is for data engineers who want to take the Azure Data Engineer Associate (DP-203) exam and delve deep into the Azure cloud stack. Engineers and product managers new to Azure or preparing for interviews with companies working on Azure technologies will find invaluable hands-on experience with Azure data technologies through this book. A basic understanding of cloud technologies, ETL, and databases will assist with understanding the concepts covered. |
azure data factory cost optimization: Microsoft Azure Essentials - Fundamentals of Azure Michael Collier, Robin Shahan, 2015-01-29 Microsoft Azure Essentials from Microsoft Press is a series of free ebooks designed to help you advance your technical skills with Microsoft Azure. The first ebook in the series, Microsoft Azure Essentials: Fundamentals of Azure, introduces developers and IT professionals to the wide range of capabilities in Azure. The authors - both Microsoft MVPs in Azure - present both conceptual and how-to content for key areas, including: Azure Websites and Azure Cloud Services Azure Virtual Machines Azure Storage Azure Virtual Networks Databases Azure Active Directory Management tools Business scenarios Watch Microsoft Press’s blog and Twitter (@MicrosoftPress) to learn about other free ebooks in the “Microsoft Azure Essentials” series. |
azure data factory cost optimization: Azure Storage, Streaming, and Batch Analytics Richard L. Nuckolls, 2020-11-03 The Microsoft Azure cloud is an ideal platform for data-intensive applications. Designed for productivity, Azure provides pre-built services that make collection, storage, and analysis much easier to implement and manage. Azure Storage, Streaming, and Batch Analytics teaches you how to design a reliable, performant, and cost-effective data infrastructure in Azure by progressively building a complete working analytics system. Summary The Microsoft Azure cloud is an ideal platform for data-intensive applications. Designed for productivity, Azure provides pre-built services that make collection, storage, and analysis much easier to implement and manage. Azure Storage, Streaming, and Batch Analytics teaches you how to design a reliable, performant, and cost-effective data infrastructure in Azure by progressively building a complete working analytics system. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Microsoft Azure provides dozens of services that simplify storing and processing data. These services are secure, reliable, scalable, and cost efficient. About the book Azure Storage, Streaming, and Batch Analytics shows you how to build state-of-the-art data solutions with tools from the Microsoft Azure platform. Read along to construct a cloud-native data warehouse, adding features like real-time data processing. Based on the Lambda architecture for big data, the design uses scalable services such as Event Hubs, Stream Analytics, and SQL databases. Along the way, you’ll cover most of the topics needed to earn an Azure data engineering certification. What's inside Configuring Azure services for speed and cost Constructing data pipelines with Data Factory Choosing the right data storage methods About the reader For readers familiar with database management. Examples in C# and PowerShell. About the author Richard Nuckolls is a senior developer building big data analytics and reporting systems in Azure. Table of Contents 1 What is data engineering? 2 Building an analytics system in Azure 3 General storage with Azure Storage accounts 4 Azure Data Lake Storage 5 Message handling with Event Hubs 6 Real-time queries with Azure Stream Analytics 7 Batch queries with Azure Data Lake Analytics 8 U-SQL for complex analytics 9 Integrating with Azure Data Lake Analytics 10 Service integration with Azure Data Factory 11 Managed SQL with Azure SQL Database 12 Integrating Data Factory with SQL Database 13 Where to go next |
azure data factory cost optimization: Microsoft Certified: Microsoft Azure Cosmos DB Developer Specialty (DP-420) , Welcome to the forefront of knowledge with Cybellium, your trusted partner in mastering the cutting-edge fields of IT, Artificial Intelligence, Cyber Security, Business, Economics and Science. Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com |
azure data factory cost optimization: The Modern Data Warehouse in Azure Matt How, 2020-06-15 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 LearnChoose 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 ingestionCreate 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 |
azure data factory cost optimization: Exam Ref DP-900 Microsoft Azure Data Fundamentals Nicola Farquharson, 2024-04-22 Prepare for Microsoft Exam DP-900 and 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 within Microsoft Azure Describe how to work with both relational and non-relational data types on Azure Describe strategic application, data management, storage and processing in the Azure cloud environment Describe an analytics workload on Azure This Microsoft Exam Ref: Organizes its coverage by the Skills Measured list published for the exam 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 a general grasp of cloud concepts |
azure data factory cost optimization: Enterprise Cloud Strategy Barry Briggs, Eduardo Kassner, 2016-01-07 How do you start? How should you build a plan for cloud migration for your entire portfolio? How will your organization be affected by these changes? This book, based on real-world cloud experiences by enterprise IT teams, seeks to provide the answers to these questions. Here, you’ll see what makes the cloud so compelling to enterprises; with which applications you should start your cloud journey; how your organization will change, and how skill sets will evolve; how to measure progress; how to think about security, compliance, and business buy-in; and how to exploit the ever-growing feature set that the cloud offers to gain strategic and competitive advantage. |
azure data factory cost optimization: Building Cloud Data Platforms Solutions Anouar BEN ZAHRA, 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. |
azure data factory cost optimization: Azure Data Scientist Associate Certification Guide Andreas Botsikas, Michael Hlobil, 2021-12-03 Develop the skills you need to run machine learning workloads in Azure and pass the DP-100 exam with ease Key FeaturesCreate end-to-end machine learning training pipelines, with or without codeTrack experiment progress using the cloud-based MLflow-compatible process of Azure ML servicesOperationalize your machine learning models by creating batch and real-time endpointsBook Description The Azure Data Scientist Associate Certification Guide helps you acquire practical knowledge for machine learning experimentation on Azure. It covers everything you need to pass the DP-100 exam and become a certified Azure Data Scientist Associate. Starting with an introduction to data science, you'll learn the terminology that will be used throughout the book and then move on to the Azure Machine Learning (Azure ML) workspace. You'll discover the studio interface and manage various components, such as data stores and compute clusters. Next, the book focuses on no-code and low-code experimentation, and shows you how to use the Automated ML wizard to locate and deploy optimal models for your dataset. You'll also learn how to run end-to-end data science experiments using the designer provided in Azure ML Studio. You'll then explore the Azure ML Software Development Kit (SDK) for Python and advance to creating experiments and publishing models using code. The book also guides you in optimizing your model's hyperparameters using Hyperdrive before demonstrating how to use responsible AI tools to interpret and debug your models. Once you have a trained model, you'll learn to operationalize it for batch or real-time inferences and monitor it in production. By the end of this Azure certification study guide, you'll have gained the knowledge and the practical skills required to pass the DP-100 exam. What you will learnCreate a working environment for data science workloads on AzureRun data experiments using Azure Machine Learning servicesCreate training and inference pipelines using the designer or codeDiscover the best model for your dataset using Automated MLUse hyperparameter tuning to optimize trained modelsDeploy, use, and monitor models in productionInterpret the predictions of a trained modelWho this book is for This book is for developers who want to infuse their applications with AI capabilities and data scientists looking to scale their machine learning experiments in the Azure cloud. Basic knowledge of Python is needed to follow the code samples used in the book. Some experience in training machine learning models in Python using common frameworks like scikit-learn will help you understand the content more easily. |
azure data factory cost optimization: Professional Azure SQL Database Administration Ahmad Osama, 2018-07-31 Discover how you can migrate a traditional on-premise SQL server database to a cloud-based solution with Microsoft Azure. Built with database administrators in mind, this book emulates different scenarios you might come across while working with large, complex SQL database migrations and provides solutions for effectively managing the migrated databases. Key Features Implement backup, restore, and recovery of Azure SQL databases Create shards and elastic pools to scale Azure SQL databases Automate common management tasks with PowerShell Implement over 40 practical activities and exercises across 24 topics to reinforce your learning Book Description As the cloud version of SQL Server, Azure SQL Database differs in key ways when it comes to management, maintenance, and administration. It’s important to know how to administer SQL Database to fully benefit from all of the features and functionality that it provides. This book addresses important aspects of an Azure SQL Database instance such as migration, backup restorations, pricing policies, security, scalability, monitoring, performance optimization, high availability, and disaster recovery. It is a complete guide for database administrators, and ideal for those who are planning to migrate from on premise SQL Server database to an Azure SQL Server database. What you will learn Learn how to provision a new database or migrate an existing on-premise solution Understand how to backup, restore, secure, and scale your own Azure SQL Database Optimize the performance by monitoring and tuning your cloud-based SQL instance Implement high availability and disaster recovery procedures with SQL Database Develop a roadmap for your own scalable cloud solution with Azure SQL Database Who this book is for This book is ideal for database administrators, database developers, or application developers who are interested in developing or migrating existing applications with Azure SQL Database. Prior experience of working with an on-premise SQL Server deployment and brief knowledge of PowerShell and C# are recommended prerequisites. |
azure data factory cost optimization: The Azure Cloud Native Architecture Mapbook Stephane Eyskens, Ed Price, 2021-02-17 Improve your Azure architecture practice and set out on a cloud and cloud-native journey with this Azure cloud native architecture guide Key FeaturesDiscover the key drivers of successful Azure architectureImplement architecture maps as a compass to tackle any challengeUnderstand architecture maps in detail with the help of practical use casesBook Description Azure offers a wide range of services that enable a million ways to architect your solutions. Complete with original maps and expert analysis, this book will help you to explore Azure and choose the best solutions for your unique requirements. Starting with the key aspects of architecture, this book shows you how to map different architectural perspectives and covers a variety of use cases for each architectural discipline. You'll get acquainted with the basic cloud vocabulary and learn which strategic aspects to consider for a successful cloud journey. As you advance through the chapters, you'll understand technical considerations from the perspective of a solutions architect. You'll then explore infrastructure aspects, such as network, disaster recovery, and high availability, and leverage Infrastructure as Code (IaC) through ARM templates, Bicep, and Terraform. The book also guides you through cloud design patterns, distributed architecture, and ecosystem solutions, such as Dapr, from an application architect's perspective. You'll work with both traditional (ETL and OLAP) and modern data practices (big data and advanced analytics) in the cloud and finally get to grips with cloud native security. By the end of this book, you'll have picked up best practices and more rounded knowledge of the different architectural perspectives. What you will learnGain overarching architectural knowledge of the Microsoft Azure cloud platformExplore the possibilities of building a full Azure solution by considering different architectural perspectivesImplement best practices for architecting and deploying Azure infrastructureReview different patterns for building a distributed application with ecosystem frameworks and solutionsGet to grips with cloud-native concepts using containerized workloadsWork with AKS (Azure Kubernetes Service) and use it with service mesh technologies to design a microservices hosting platformWho this book is for This book is for aspiring Azure Architects or anyone who specializes in security, infrastructure, data, and application architecture. If you are a developer or infrastructure engineer looking to enhance your Azure knowledge, you'll find this book useful. |
azure data factory cost optimization: Google Cloud Digital Leader Certification Guide Bruno Beraldo Rodrigues, 2024-03-15 Gain the expertise needed for the Google Cloud Digital Leader certification with the help of industry insights, effective testing strategies, and exam questions designed to help you make informed tech decisions aligned with business goals Key Features Learn about data management, AI, monetization, security, and the significance of infrastructure modernization Build a solid foundation in Google Cloud, covering all technical essentials necessary for a Google Cloud Digital Leader Test your knowledge of cloud and digital transformation through realistic exam questions Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionTo thrive in today's world, leaders and technologists must understand how technology shapes businesses. As organizations shift from self-hosted to cloud-native solutions, embracing serverless systems, strategizing data use, and defining monetization becomes imperative. The Google Cloud Digital Leader Certification Guide lays a solid foundation of industry knowledge, focused on the Google Cloud platform and the innovative ways in which customers leverage its technologies. The book starts by helping you grasp the essence of digital transformation within the Google Cloud context. You’ll then cover core components of the platform, such as infrastructure and application modernization, data innovation, and best practices for environment management and security. With a series of practice exam questions included, this book ensures that you build comprehensive knowledge and prepare to certify as a Google Cloud Digital Leader. Going beyond the exam essentials, you’ll also explore how companies are modernizing infrastructure, data ecosystems, and teams in order to capitalize on new market opportunities through platform expertise, best practices, and real-world scenarios. By the end of this book, you'll have learned everything you need to pass the Google Cloud Digital Leader certification exam and have a reference guide for future requirements.What you will learn Leverage Google Cloud’s AI and ML solutions to create business value Identify Google Cloud solutions for data management and smart analytics Acquire the skills necessary to modernize infrastructure and applications on GCP Understand the value of APIs and their applications in cloud environments Master financial governance and implement best practices for cost management Understand the cloud security approach and benefits of Google Cloud security Find out how IT operations must adapt to thrive in the cloud Who this book is for This Google Cloud fundamentals book is suitable for individuals with both technical and non-technical backgrounds looking for a starting point to pursue more advanced Google Cloud certifications. No prior experience is required to get started with this book; only a keen interest in learning and exploring cloud concepts, with a focus on Google Cloud. |
azure data factory cost optimization: Azure Databricks Cookbook Phani Raj, Vinod Jaiswal, 2021-09-17 Get to grips with building and productionizing end-to-end big data solutions in Azure and learn best practices for working with large datasets Key FeaturesIntegrate with Azure Synapse Analytics, Cosmos DB, and Azure HDInsight Kafka Cluster to scale and analyze your projects and build pipelinesUse Databricks SQL to run ad hoc queries on your data lake and create dashboardsProductionize a solution using CI/CD for deploying notebooks and Azure Databricks Service to various environmentsBook Description Azure Databricks is a unified collaborative platform for performing scalable analytics in an interactive environment. The Azure Databricks Cookbook provides recipes to get hands-on with the analytics process, including ingesting data from various batch and streaming sources and building a modern data warehouse. The book starts by teaching you how to create an Azure Databricks instance within the Azure portal, Azure CLI, and ARM templates. You'll work through clusters in Databricks and explore recipes for ingesting data from sources, including files, databases, and streaming sources such as Apache Kafka and EventHub. The book will help you explore all the features supported by Azure Databricks for building powerful end-to-end data pipelines. You'll also find out how to build a modern data warehouse by using Delta tables and Azure Synapse Analytics. Later, you'll learn how to write ad hoc queries and extract meaningful insights from the data lake by creating visualizations and dashboards with Databricks SQL. Finally, you'll deploy and productionize a data pipeline as well as deploy notebooks and Azure Databricks service using continuous integration and continuous delivery (CI/CD). By the end of this Azure book, you'll be able to use Azure Databricks to streamline different processes involved in building data-driven apps. What you will learnRead and write data from and to various Azure resources and file formatsBuild a modern data warehouse with Delta Tables and Azure Synapse AnalyticsExplore jobs, stages, and tasks and see how Spark lazy evaluation worksHandle concurrent transactions and learn performance optimization in Delta tablesLearn Databricks SQL and create real-time dashboards in Databricks SQLIntegrate Azure DevOps for version control, deploying, and productionizing solutions with CI/CD pipelinesDiscover how to use RBAC and ACLs to restrict data accessBuild end-to-end data processing pipeline for near real-time data analyticsWho this book is for This recipe-based book is for data scientists, data engineers, big data professionals, and machine learning engineers who want to perform data analytics on their applications. Prior experience of working with Apache Spark and Azure is necessary to get the most out of this book. |
azure data factory cost optimization: Professional Azure SQL Managed Database Administration Ahmad Osama, Shashikant Shakya, 2021-03-08 Master data management by effectively utilizing the features of Azure SQL database. Key FeaturesLearn to automate common management tasks with PowerShell.Understand different methods to generate elastic pools and shards to scale Azure SQL databases.Learn to develop a scalable cloud solution through over 40 practical activities and exercises.Book Description Despite being the cloud version of SQL Server, Azure SQL Database and Azure SQL Managed Instance stands out in various aspects when it comes to management, maintenance, and administration. Updated with the latest Azure features, Professional Azure SQL Managed Database Administration continues to be a comprehensive guide for becoming proficient in data management. The book begins by introducing you to the Azure SQL managed databases (Azure SQL Database and Azure SQL Managed Instance), explaining their architecture, and how they differ from an on-premises SQL server. You will then learn how to perform common tasks, such as migrating, backing up, and restoring a SQL Server database to an Azure database. As you progress, you will study how you can save costs and manage and scale multiple SQL databases using elastic pools. You will also implement a disaster recovery solution using standard and active geo-replication. Finally, you will explore the monitoring and tuning of databases, the key features of databases, and the phenomenon of app modernization. By the end of this book, you will have mastered the key aspects of an Azure SQL database and Azure SQL managed instance, including migration, backup restorations, performance optimization, high availability, and disaster recovery. What you will learnUnderstanding Azure SQL database configuration and pricing optionsProvisioning a new SQL database or migrating an existing on-premises SQL Server database to an Azure SQL databaseBacking up and restoring an Azure SQL databaseSecuring and scaling an Azure SQL databaseMonitoring and tuning an Azure SQL databaseImplementing high availability and disaster recovery with an Azure SQL databaseManaging, maintaining, and securing managed instancesWho this book is for This book is designed to benefit database administrators, database developers, or application developers who are interested in developing new applications or migrating existing ones with Azure SQL database. Prior experience of working with an on-premise SQL Server or Azure SQL database along with a basic understanding of PowerShell scripts and C# code is necessary to grasp the concepts covered in this book. |
azure data factory cost optimization: AWS Certified Big Data – Specialty (BDS-C01) Cybellium, Welcome to the forefront of knowledge with Cybellium, your trusted partner in mastering the cutting-edge fields of IT, Artificial Intelligence, Cyber Security, Business, Economics and Science. Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com |
azure data factory cost optimization: Distributed Data Systems with Azure Databricks Alan Bernardo Palacio, 2021-05-25 Quickly build and deploy massive data pipelines and improve productivity using Azure Databricks Key FeaturesGet to grips with the distributed training and deployment of machine learning and deep learning modelsLearn how ETLs are integrated with Azure Data Factory and Delta LakeExplore deep learning and machine learning models in a distributed computing infrastructureBook Description Microsoft Azure Databricks helps you to harness the power of distributed computing and apply it to create robust data pipelines, along with training and deploying machine learning and deep learning models. Databricks' advanced features enable developers to process, transform, and explore data. Distributed Data Systems with Azure Databricks will help you to put your knowledge of Databricks to work to create big data pipelines. The book provides a hands-on approach to implementing Azure Databricks and its associated methodologies that will make you productive in no time. Complete with detailed explanations of essential concepts, practical examples, and self-assessment questions, you’ll begin with a quick introduction to Databricks core functionalities, before performing distributed model training and inference using TensorFlow and Spark MLlib. As you advance, you’ll explore MLflow Model Serving on Azure Databricks and implement distributed training pipelines using HorovodRunner in Databricks. Finally, you’ll discover how to transform, use, and obtain insights from massive amounts of data to train predictive models and create entire fully working data pipelines. By the end of this MS Azure book, you’ll have gained a solid understanding of how to work with Databricks to create and manage an entire big data pipeline. What you will learnCreate ETLs for big data in Azure DatabricksTrain, manage, and deploy machine learning and deep learning modelsIntegrate Databricks with Azure Data Factory for extract, transform, load (ETL) pipeline creationDiscover how to use Horovod for distributed deep learningFind out how to use Delta Engine to query and process data from Delta LakeUnderstand how to use Data Factory in combination with DatabricksUse Structured Streaming in a production-like environmentWho this book is for This book is for software engineers, machine learning engineers, data scientists, and data engineers who are new to Azure Databricks and want to build high-quality data pipelines without worrying about infrastructure. Knowledge of Azure Databricks basics is required to learn the concepts covered in this book more effectively. A basic understanding of machine learning concepts and beginner-level Python programming knowledge is also recommended. |
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