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Condizione: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

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Paperback. Condizione: New. Second Edition. This book is your guide to the modern market of data analytics platforms and the benefits of using Snowflake, the data warehouse built for the cloud. As organizations increasingly rely on modern cloud data platforms, the core of any analytics framework-the data warehouse-is more important than ever. This updated 2nd edition ensures you are ready to make the most of the industry's leading data warehouse.This book will onboard you to Snowflake and present best practices for deploying and using the Snowflake data warehouse. The book also covers modern analytics architecture, integration with leading analytics software such as Matillion ETL, Tableau, and Databricks, and migration scenarios for on-premises legacy data warehouses.This new edition includes expanded coverage of SnowPark for developing complex data applications, an introduction to managing large datasets with Apache Iceberg tables, and instructions for creating interactive data applications using Streamlit, ensuring readers are equipped with the latest advancements in Snowflake's capabilities. What You Will LearnMaster key functionalities of SnowflakeSet up security and access with clusterBulk load data into Snowflake using the COPY commandMigrate from a legacy data warehouse to SnowflakeIntegrate the Snowflake data platform with modern business intelligence (BI) and data integration toolsManage large datasets with Apache Iceberg TablesImplement continuous data loading with Snowpipe and Dynamic Tables Who This Book Is ForData professionals, business analysts, IT administrators, and existing or potential Snowflake users.…

Paperback. Condizione: Good. 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 forThis 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.…

Condizione: very_good. Book is in very good condition and may include minimal underlining highlighting. The book can also include "From the library of" labels. May not contain miscellaneous items toys, dvds, etc. . We offer 100% money back guarantee and 24 7 customer service.

Paperback. Condizione: Good. 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 forThis 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.…

Condizione: good. Paperback Book.

paperback. Condizione: Very Good. Cover and edges may have some wear.

Paperback. Condizione: New. Second Edition. This book is your guide to the modern market of data analytics platforms and the benefits of using Snowflake, the data warehouse built for the cloud. As organizations increasingly rely on modern cloud data platforms, the core of any analytics framework-the data warehouse-is more important than ever. This updated 2nd edition ensures you are ready to make the most of the industry's leading data warehouse.This book will onboard you to Snowflake and present best practices for deploying and using the Snowflake data warehouse. The book also covers modern analytics architecture, integration with leading analytics software such as Matillion ETL, Tableau, and Databricks, and migration scenarios for on-premises legacy data warehouses.This new edition includes expanded coverage of SnowPark for developing complex data applications, an introduction to managing large datasets with Apache Iceberg tables, and instructions for creating interactive data applications using Streamlit, ensuring readers are equipped with the latest advancements in Snowflake's capabilities. What You Will LearnMaster key functionalities of SnowflakeSet up security and access with clusterBulk load data into Snowflake using the COPY commandMigrate from a legacy data warehouse to SnowflakeIntegrate the Snowflake data platform with modern business intelligence (BI) and data integration toolsManage large datasets with Apache Iceberg TablesImplement continuous data loading with Snowpipe and Dynamic Tables Who This Book Is ForData professionals, business analysts, IT administrators, and existing or potential Snowflake users.…

Paperback or Softback. Condizione: New. Data Engineering with Azure Databricks: Design, build, and optimize scalable data pipelines and analytics solutions with Azure Databricks. Book.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Paperback or Softback. Condizione: New. Azure Data Factory Cookbook - Second Edition: A data engineer's guide to building and managing ETL and ELT pipelines with data integration. Book.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Paperback. Condizione: New. Master end-to-end data engineering on Azure Databricks. From data ingestion and Delta Lake to CI/CD and real-time streaming, build secure, scalable, and performant data solutions with Spark, Unity Catalog, and ML tools.Key FeaturesBuild scalable data pipelines using Apache Spark and Delta LakeAutomate workflows and manage data governance with Unity CatalogLearn real-time processing and structured streaming with practical use casesImplement CI/CD, DevOps, and security for production-ready data solutionsExplore Databricks-native ML, AutoML, and Generative AI integrationBook Description"Data Engineering with Azure Databricks" is your essential guide to building scalable, secure, and high-performing data pipelines using the powerful Databricks platform on Azure. Designed for data engineers, architects, and developers, this book demystifies the complexities of Spark-based workloads, Delta Lake, Unity Catalog, and real-time data processing.Beginning with the foundational role of Azure Databricks in modern data engineering, you'll explore how to set up robust environments, manage data ingestion with Auto Loader, optimize Spark performance, and orchestrate complex workflows using tools like Azure Data Factory and Airflow.The book offers deep dives into structured streaming, Delta Live Tables, and Delta Lake's ACID features for data reliability and schema evolution. You'll also learn how to manage security, compliance, and access controls using Unity Catalog, and gain insights into managing CI/CD pipelines with Azure DevOps and Terraform.With a special focus on machine learning and generative AI, the final chapters guide you in automating model workflows, leveraging MLflow, and fine-tuning large language models on Databricks. Whether you're building a modern data lakehouse or operationalizing analytics at scale, this book provides the tools and insights you need.What you will learnSet up a full-featured Azure Databricks environmentImplement batch and streaming ingestion using Auto LoaderOptimize Spark jobs with partitioning and cachingBuild real-time pipelines with structured streaming and DLTManage data governance using Unity CatalogOrchestrate production workflows with jobs and ADFApply CI/CD best practices with Azure DevOps and GitSecure data with RBAC, encryption, and compliance standardsUse MLflow and Feature Store for ML pipelinesBuild generative AI applications in DatabricksWho this book is forThis book is for data engineers, solution architects, cloud professionals, and software engineers seeking to build robust and scalable data pipelines using Azure Databricks. Whether you're migrating legacy systems, implementing a modern lakehouse architecture, or optimizing data workflows for performance, this guide will help you leverage the full power of Databricks on Azure. A basic understanding of Python, Spark, and cloud infrastructure is recommended.…

Condizione: New.

Paperback. Condizione: New. Master end-to-end data engineering on Azure Databricks. From data ingestion and Delta Lake to CI/CD and real-time streaming, build secure, scalable, and performant data solutions with Spark, Unity Catalog, and ML tools.Key FeaturesBuild scalable data pipelines using Apache Spark and Delta LakeAutomate workflows and manage data governance with Unity CatalogLearn real-time processing and structured streaming with practical use casesImplement CI/CD, DevOps, and security for production-ready data solutionsExplore Databricks-native ML, AutoML, and Generative AI integrationBook Description"Data Engineering with Azure Databricks" is your essential guide to building scalable, secure, and high-performing data pipelines using the powerful Databricks platform on Azure. Designed for data engineers, architects, and developers, this book demystifies the complexities of Spark-based workloads, Delta Lake, Unity Catalog, and real-time data processing.Beginning with the foundational role of Azure Databricks in modern data engineering, you'll explore how to set up robust environments, manage data ingestion with Auto Loader, optimize Spark performance, and orchestrate complex workflows using tools like Azure Data Factory and Airflow.The book offers deep dives into structured streaming, Delta Live Tables, and Delta Lake's ACID features for data reliability and schema evolution. You'll also learn how to manage security, compliance, and access controls using Unity Catalog, and gain insights into managing CI/CD pipelines with Azure DevOps and Terraform.With a special focus on machine learning and generative AI, the final chapters guide you in automating model workflows, leveraging MLflow, and fine-tuning large language models on Databricks. Whether you're building a modern data lakehouse or operationalizing analytics at scale, this book provides the tools and insights you need.What you will learnSet up a full-featured Azure Databricks environmentImplement batch and streaming ingestion using Auto LoaderOptimize Spark jobs with partitioning and cachingBuild real-time pipelines with structured streaming and DLTManage data governance using Unity CatalogOrchestrate production workflows with jobs and ADFApply CI/CD best practices with Azure DevOps and GitSecure data with RBAC, encryption, and compliance standardsUse MLflow and Feature Store for ML pipelinesBuild generative AI applications in DatabricksWho this book is forThis book is for data engineers, solution architects, cloud professionals, and software engineers seeking to build robust and scalable data pipelines using Azure Databricks. Whether you're migrating legacy systems, implementing a modern lakehouse architecture, or optimizing data workflows for performance, this guide will help you leverage the full power of Databricks on Azure. A basic understanding of Python, Spark, and cloud infrastructure is recommended.…

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New. pp. 382.

Condizione: New.

Paperback. Condizione: New. Data Engineers guide to solve real-world problems encountered while building and transforming data pipelines using Azure's data integration toolKey FeaturesSolve real-world data problems and create data-driven workflows with ease using Azure Data FactoryBuild an ADF pipeline that operates on pre-built ML model and Azure AIGet up and running with Fabric Data Explorer and extend ADF with Logic Apps and Azure functionsBook 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 learnBuild and Manage data pipelines with ease using the latest version of ADFConfigure, load data, and operate data flows with Azure SynapseGet up and running with Fabric Data FactoryWorking with Azure Data Factory and Azure PurviewCreate big data pipelines using Databricks and Delta tablesIntegrate ADF with commonly used Azure services such as Azure ML, Azure Logic Apps, and Azure FunctionsLearn industry-grade best practices for using Azure Data FactoryWho this book is forThis 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.…

Condizione: New. In English.

Condizione: As New. Unread book in perfect condition.

Condizione: New.