operationalizing big data and advanced analytics solutions /
نام نخستين پديدآور
Sudhir Rawat, Abhishek Narain.
وضعیت نشر و پخش و غیره
محل نشرو پخش و غیره
[New York, New York] :
نام ناشر، پخش کننده و غيره
Apress,
تاریخ نشرو بخش و غیره
[2019]
مشخصات ظاهری
نام خاص و کميت اثر
1 online resource (376 pages)
یادداشتهای مربوط به مندرجات
متن يادداشت
Intro; Table of Contents; About the Authors; About the Technical Reviewer; Introduction; Chapter 1: Introduction to Data Analytics; What Is Big Data?; Why Big Data?; Big Data Analytics on Microsoft Azure; What Is Azure Data Factory?; High-Level ADF Concepts; Activity; Pipeline; Datasets; Linked Service; Integration Runtime; When to Use ADF?; Why ADF?; Summary; Chapter 2: Introduction to Azure Data Factory; Azure Data Factory v1 vs. Azure Data Factory v2; Data Integration with Azure Data Factory; Architecture; Concepts; Pipelines; Activities; Execution Activities (Copy and Data Transform)
متن يادداشت
Activity PolicyControl; Activity Dependency; Datasets; Dataset Structure; When to Specify a Dataset Structure?; Linked Services; Linked Service Example; Integration Runtime; Azure IR; Self-Hosted IR; Azure-SSIS IR; Hands-on: Creating a Data Factory Instance Using a User Interface; Prerequisites; Steps; Hands-on: Creating a Data Factory Instance Using PowerShell; Prerequisites; Log In to PowerShell; Create a Data Factory; Summary; Chapter 3: Data Movement; Overview; How Does the Copy Activity Work?; Supported Connectors; Configurations; Supported File and Compression Formats
متن يادداشت
Chapter 7: SecurityOverview; Cloud Scenario; Securing the Data Credentials; Data Encryption in Transit; Data Encryption at Rest; Hybrid Scenario; On-Premise Data Store Credentials; Encryption in Transit; Considerations for Selecting Express Route or VPN; Firewall Configurations and IP Whitelisting for Self-Hosted Integration Runtime Functionality; IP Configurations and Whitelisting in Data Stores; Proxy Server Considerations; Storing Credentials in Azure Key Vault; Prerequisites; Steps; Using the Authoring UI; Reference Secret Stored in Key Vault; Using the Authoring UI
متن يادداشت
Copy Activity PropertiesProperty Details; How to Create a Copy Activity; Schema Capture and Automatic Mapping in Copy Data Tool; Scenario: Creating a Copy Activity Using the Copy Data Tool (Binary Copy); Copy Performance Considerations; Data Integration Units; Parallel Copy; Staged Copy; How Staged Copy Works; Configuration; Staged Copy Billing Impact; Considerations for the Self-Hosted Integration Runtime; Considerations for Serialization and Deserialization; Considerations for Compression; Considerations for Column Mapping; Summary; Chapter 4: Data Transformation: Part 1
متن يادداشت
Data TransformationHDInsight; Hive Activity; Pig Activity; MapReduce Activity; Streaming Activity; Spark Activity; Azure Machine Learning; Azure Data Lake; Chapter 5: Data Transformation: Part 2; Data Warehouse to Modern Data Warehouse; ETL vs. ELT; Azure Databricks; Build and Implement Use Case; Stored Procedure; Custom Activity; Chapter 6: Managing Flow; Why Managing Flow Is Important; Expressions; Functions; Activities; Let's Build the Flow; Build the Source Database; Build Azure Blob Storage as the Destination; Build the Azure Logic App; Build the Azure Data Factory Pipeline; Summary
بدون عنوان
0
بدون عنوان
8
بدون عنوان
8
بدون عنوان
8
بدون عنوان
8
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
Improve your analytics and data platform to solve major challenges, including operationalizing big data and advanced analytics workloads on Azure. You will learn how to monitor complex pipelines, set alerts, and extend your organization's custom monitoring requirements. This book starts with an overview of the Azure Data Factory as a hybrid ETL/ELT orchestration service on Azure. The book then dives into data movement and the connectivity capability of Azure Data Factory. You will learn about the support for hybrid data integration from disparate sources such as on-premise, cloud, or from SaaS applications. Detailed guidance is provided on how to transform data and on control flow. Demonstration of operationalizing the pipelines and ETL with SSIS is included. You will know how to leverage Azure Data Factory to run existing SSIS packages. As you advance through the book, you will wrap up by learning how to create a single pane for end-to-end monitoring, which is a key skill in building advanced analytics and big data pipelines.
یادداشتهای مربوط به سفارشات
منبع سفارش / آدرس اشتراک
Springer Nature
شماره انبار
com.springer.onix.9781484241226
ویراست دیگر از اثر در قالب دیگر رسانه
عنوان
Understanding Azure Data Factory : Operationalizing Big Data and Advanced Analytics Solutions.
شماره استاندارد بين المللي کتاب و موسيقي
9781484241219
عنوان به منزله موضوع
موضوع مستند نشده
Microsoft Azure SQL Database.
موضوع مستند نشده
Microsoft Azure SQL Database.
موضوع (اسم عام یاعبارت اسمی عام)
موضوع مستند نشده
Big data.
موضوع مستند نشده
Quantitative research.
موضوع مستند نشده
Big data.
موضوع مستند نشده
Quantitative research.
مقوله موضوعی
موضوع مستند نشده
COM051380
موضوع مستند نشده
UMP
موضوع مستند نشده
UMP
رده بندی ديویی
شماره
005
.
7
ويراست
23
رده بندی کنگره
شماره رده
QA76
.
9
.
B45
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )