Mastering Azure Analytics
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Mastering Azure Analytics
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Author : Zoiner Tejada
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-04-06
Mastering Azure Analytics written by Zoiner Tejada and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-06 with Computers categories.
Helps users understand the breadth of Azure services by organizing them into a reference framework they can use when crafting their own big-data analytics solution.
Mastering Azure Synapse Analytics
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Author : Debananda Ghosh
language : en
Publisher: BPB Publications
Release Date : 2023-04-15
Mastering Azure Synapse Analytics written by Debananda Ghosh and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-15 with Computers categories.
A practical guide that will help you transform your data into actionable insights with Azure Synapse Analytics KEY FEATURES ● Explore the different features in the Azure Synapse Analytics workspace. ● Learn how to integrate Power BI and Data Governance capabilities with Azure Synapse Analytics. ● Accelerate your analytics journey with the no-code/low-code capabilities of Azure Synapse. DESCRIPTION Cloud analytics is a crucial aspect of any digital transformation initiative, and the capabilities of the Azure Synapse analytics platform can simplify and streamline this process. By mastering Azure Synapse Analytics, analytics developers across organizations can boost their productivity by utilizing low-code, no-code, and traditional code-based analytics frameworks. This book starts with a comprehensive introduction to Azure Synapse Analytics and its limitless cloud-scale analytics capabilities. You will then learn how to explore and work with data warehousing features in Azure Synapse. Moving on, the book will guide you on how to effectively use Synapse Spark for data engineering and data science. It will help you learn how to gain insights from your data through Observational analytics using Synapse Data Explorer. You will also discover the seamless data integration capabilities of Synapse Pipeline, and delve into the benefits of Synapse Analytics' low-code and no-code pipeline development features. Lastly the book will show you how to create network topology and implement industry-specific architecture patterns in Azure Synapse Analytics. By the end of the book, you will be able to process and analyze vast amounts of data in real-time to gain insights quickly and make informed decisions. WHAT YOU WILL LEARN ● Leverage Synapse Spark for machine learning tasks. ● Use Synapse Data Explorer for telemetry analysis. ● Take advantage of Synapse's common data model-based database templates. ● Query data using T-SQL, KQL, and Spark SQL within Synapse. ● Integrate Microsoft Purview with Synapse for enhanced data governance. WHO THIS BOOK IS FOR This book is designed for Cloud data engineers with prior experience in Azure cloud computing, as well as Chief Data Officers (CDOs) and Data professionals, who want to use this unified platform for data ingestion, data warehousing, and big data analytics. TABLE OF CONTENTS 1. Cloud Analytics Concept 2. Introduction to Azure Synapse Analytics 3. Modern Data Warehouse with the Synapse SQL Pool 4. Query as a Service- Synapse Serverless SQL 5. Synapse Spark Pool Capability 6. Synapse Spark and Data Science 7. Learning Synapse Data Explorer 8. Synapse Data Integration 9. Synapse Link for HTAP 10. Azure Synapse -Unified Analytics Service 11. Synapse Workspace Ecosystem Integration 12. Azure Synapse Network Topology 13. Industry Cloud Analytics
Mastering Azure Synapse Analytics Guide To Modern Data Integration
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Author : Sultan Yerbulatov
language : en
Publisher: Litres
Release Date : 2024-06-26
Mastering Azure Synapse Analytics Guide To Modern Data Integration written by Sultan Yerbulatov and has been published by Litres this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-26 with Computers categories.
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.
Mastering Azure Analytics 1st Edition
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Author : Zoiner Tejada
language : en
Publisher:
Release Date : 2017
Mastering Azure Analytics 1st Edition written by Zoiner Tejada and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Mastering Identity And Access Management With Microsoft Azure
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Author : Jochen Nickel
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-09-30
Mastering Identity And Access Management With Microsoft Azure written by Jochen Nickel 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 2016-09-30 with Computers categories.
Start empowering users and protecting corporate data, while managing Identities and Access with Microsoft Azure in different environments About This Book Deep dive into the Microsoft Identity and Access Management as a Service (IDaaS) solution Design, implement and manage simple and complex hybrid identity and access management environments Learn to apply solution architectures directly to your business needs and understand how to identify and manage business drivers during transitions Who This Book Is For This book is for business decision makers, IT consultants, and system and security engineers who wish to plan, design, and implement Identity and Access Management solutions with Microsoft Azure. What You Will Learn Apply technical descriptions and solution architectures directly to your business needs and deployments Identify and manage business drivers and architecture changes to transition between different scenarios Understand and configure all relevant Identity and Access Management key features and concepts Implement simple and complex directory integration, authentication, and authorization scenarios Get to know about modern identity management, authentication, and authorization protocols and standards Implement and configure a modern information protection solution Integrate and configure future improvements in authentication and authorization functionality of Windows 10 and Windows Server 2016 In Detail Microsoft Azure and its Identity and Access Management is at the heart of Microsoft's Software as a Service, including Office 365, Dynamics CRM, and Enterprise Mobility Management. It is an essential tool to master in order to effectively work with the Microsoft Cloud. Through practical, project based learning this book will impart that mastery. Beginning with the basics of features and licenses, this book quickly moves on to the user and group lifecycle required to design roles and administrative units for role-based access control (RBAC). Learn to design Azure AD to be an identity provider and provide flexible and secure access to SaaS applications. Get to grips with how to configure and manage users, groups, roles, and administrative units to provide a user- and group-based application and self-service access including the audit functionality. Next find out how to take advantage of managing common identities with the Microsoft Identity Manager 2016 and build cloud identities with the Azure AD Connect utility. Construct blueprints with different authentication scenarios including multi-factor authentication. Discover how to configure and manage the identity synchronization and federation environment along with multi -factor authentication, conditional access, and information protection scenarios to apply the required security functionality. Finally, get recommendations for planning and implementing a future-oriented and sustainable identity and access management strategy. Style and approach A practical, project-based learning experience explained through hands-on examples.
Microsoft Azure Machine Learning
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Author : Sumit Mund
language : en
Publisher:
Release Date : 2015-06-16
Microsoft Azure Machine Learning written by Sumit Mund and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-16 with Computers categories.
The book is intended for those who want to learn how to use Azure Machine Learning. Perhaps you already know a bit about Machine Learning, but have never used ML Studio in Azure; or perhaps you are an absolute newbie. In either case, this book will get you up-and-running quickly.
Mastering Azure Machine Learning
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Author : Christoph Körner
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-04-30
Mastering Azure Machine Learning written by Christoph Körner 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 2020-04-30 with Computers categories.
Master expert techniques for building automated and highly scalable end-to-end machine learning models and pipelines in Azure using TensorFlow, Spark, and Kubernetes Key FeaturesMake sense of data on the cloud by implementing advanced analyticsTrain and optimize advanced deep learning models efficiently on Spark using Azure DatabricksDeploy machine learning models for batch and real-time scoring with Azure Kubernetes Service (AKS)Book Description The increase being seen in data volume today requires distributed systems, powerful algorithms, and scalable cloud infrastructure to compute insights and train and deploy machine learning (ML) models. This book will help you improve your knowledge of building ML models using Azure and end-to-end ML pipelines on the cloud. The book starts with an overview of an end-to-end ML project and a guide on how to choose the right Azure service for different ML tasks. It then focuses on Azure Machine Learning and takes you through the process of data experimentation, data preparation, and feature engineering using Azure Machine Learning and Python. You'll learn advanced feature extraction techniques using natural language processing (NLP), classical ML techniques, and the secrets of both a great recommendation engine and a performant computer vision model using deep learning methods. You'll also explore how to train, optimize, and tune models using Azure Automated Machine Learning and HyperDrive, and perform distributed training on Azure. Then, you'll learn different deployment and monitoring techniques using Azure Kubernetes Services with Azure Machine Learning, along with the basics of MLOps—DevOps for ML to automate your ML process as CI/CD pipeline. By the end of this book, you'll have mastered Azure Machine Learning and be able to confidently design, build and operate scalable ML pipelines in Azure. What you will learnSetup your Azure Machine Learning workspace for data experimentation and visualizationPerform ETL, data preparation, and feature extraction using Azure best practicesImplement advanced feature extraction using NLP and word embeddingsTrain gradient boosted tree-ensembles, recommendation engines and deep neural networks on Azure Machine LearningUse hyperparameter tuning and Azure Automated Machine Learning to optimize your ML modelsEmploy distributed ML on GPU clusters using Horovod in Azure Machine LearningDeploy, operate and manage your ML models at scaleAutomated your end-to-end ML process as CI/CD pipelines for MLOpsWho this book is for This machine learning book is for data professionals, data analysts, data engineers, data scientists, or machine learning developers who want to master scalable cloud-based machine learning architectures in Azure. This book will help you use advanced Azure services to build intelligent machine learning applications. A basic understanding of Python and working knowledge of machine learning are mandatory.
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
Mastering Azure For Predictive Analytics And Machine Learning
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Author : KRISHNA KISHOR TIRUPATI SATISH VADLAMANI SHALU JAIN A RENUKA
language : en
Publisher: DeepMisti Publication
Release Date : 2024-10-09
Mastering Azure For Predictive Analytics And Machine Learning written by KRISHNA KISHOR TIRUPATI SATISH VADLAMANI SHALU JAIN A RENUKA and has been published by DeepMisti Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-09 with Computers categories.
In Today's Data-Driven World, The Ability To Harness The Power Of Predictive Analytics And Machine Learning Has Become A Pivotal Force In Shaping Innovation Across Industries. This Book, Mastering Azure For Predictive Analytics And Machine Learning, Aims To Bridge The Gap Between Cloud Technology And The Analytical Tools Needed To Drive Insights From Complex Data. Our Objective Is To Provide Readers With The Foundational Knowledge And Advanced Techniques Necessary To Leverage Microsoft Azure For Predictive Modeling And Machine Learning Applications. The Structure Of This Book Offers A Comprehensive Exploration Of The Tools, Methodologies, And Best Practices That Define Modern Analytics And Machine Learning In The Cloud. From Setting Up Your Azure Environment To Deploying Machine Learning Models, We Cover Each Stage With Practical Examples And Detailed Guidance. The Content Is Designed For A Broad Audience, Including Students, Data Scientists, It Professionals, And Business Leaders Who Seek To Use Azure’s Capabilities To Make Data-Informed Decisions. Drawing From The Latest Industry Research And Real-World Use Cases, This Book Not Only Provides Theoretical Knowledge But Also Equips Readers With Hands-On Skills They Can Apply In Real-Time Data Projects. Each Chapter Balances Depth With Accessibility, Covering Topics Like Data Preparation, Model Building, And Cloud-Based Deployment, While Also Touching On Critical Issues Such As Scalability, Security, And Automation. Additionally, We Highlight Best Practices For Managing Azure’s Infrastructure And Optimizing Machine Learning Workflows Within The Platform. The Inspiration For This Book Comes From The Recognition Of The Growing Role That Cloud Platforms Like Azure Play In Transforming How Organizations Use Data To Innovate And Compete. We Are Immensely Thankful To Chancellor Shri Shiv Kumar Gupta Of Maharaja Agrasen Himalayan Garhwal University For His Support And Commitment To Academic And Technological Excellence, Which Has Been Instrumental In Making This Book A Reality. We Hope That Mastering Azure For Predictive Analytics And Machine Learning Will Be A Valuable Resource For Anyone Looking To Deepen Their Understanding Of How Cloud Computing And Machine Learning Can Converge To Unlock The Full Potential Of Predictive Analytics. The Knowledge Contained In These Pages Is Intended To Empower Readers To Lead Transformative Data Projects With Confidence. Thank You For Embarking On This Journey With Us. Authors
Microsoft Azure Essentials Azure Machine Learning
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Author : Jeff Barnes
language : en
Publisher: Microsoft Press
Release Date : 2015-04-25
Microsoft Azure Essentials Azure Machine Learning written by Jeff Barnes and has been published by Microsoft Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-25 with Computers categories.
Microsoft Azure Essentials from Microsoft Press is a series of free ebooks designed to help you advance your technical skills with Microsoft Azure. This third ebook in the series introduces Microsoft Azure Machine Learning, a service that a developer can use to build predictive analytics models (using training datasets from a variety of data sources) and then easily deploy those models for consumption as cloud web services. The ebook presents an overview of modern data science theory and principles, the associated workflow, and then covers some of the more common machine learning algorithms in use today. It builds a variety of predictive analytics models using real world data, evaluates several different machine learning algorithms and modeling strategies, and then deploys the finished models as machine learning web services on Azure within a matter of minutes. The ebook also expands on a working Azure Machine Learning predictive model example to explore the types of client and server applications you can create to consume Azure Machine Learning web services. Watch Microsoft Press’s blog and Twitter (@MicrosoftPress) to learn about other free ebooks in the Microsoft Azure Essentials series.