Coverart for item
The Resource Understanding Azure Data Factory : Operationalizing Big Data and Advanced Analytics Solutions, Sudhir Rawat, Abhishek Narain, (electronic book)

Understanding Azure Data Factory : Operationalizing Big Data and Advanced Analytics Solutions, Sudhir Rawat, Abhishek Narain, (electronic book)

Label
Understanding Azure Data Factory : Operationalizing Big Data and Advanced Analytics Solutions
Title
Understanding Azure Data Factory
Title remainder
Operationalizing Big Data and Advanced Analytics Solutions
Statement of responsibility
Sudhir Rawat, Abhishek Narain
Creator
Contributor
Subject
Language
eng
Cataloging source
EBLCP
http://library.link/vocab/creatorName
Rawat, Sudhir
Dewey number
005.7
Index
no index present
LC call number
QA76.9.B45
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
Narain, Abhishek
http://library.link/vocab/subjectName
Big data
Label
Understanding Azure Data Factory : Operationalizing Big Data and Advanced Analytics Solutions, Sudhir Rawat, Abhishek Narain, (electronic book)
Instantiates
Publication
Note
  • Description based upon print version of record
  • Advanced Security with Managed Service Identity
Antecedent source
file reproduced from an electronic resource
Contents
  • 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)
  • 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
  • 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
  • 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
  • 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
Dimensions
unknown
Extent
1 online resource (376 p.)
File format
one file format
Form of item
online
Isbn
9781484241226
Level of compression
unknown
Quality assurance targets
unknown
Reformatting quality
unknown
Specific material designation
remote
System control number
  • on1080434080
  • (OCoLC)1080434080
Label
Understanding Azure Data Factory : Operationalizing Big Data and Advanced Analytics Solutions, Sudhir Rawat, Abhishek Narain, (electronic book)
Publication
Note
  • Description based upon print version of record
  • Advanced Security with Managed Service Identity
Antecedent source
file reproduced from an electronic resource
Contents
  • 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)
  • 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
  • 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
  • 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
  • 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
Dimensions
unknown
Extent
1 online resource (376 p.)
File format
one file format
Form of item
online
Isbn
9781484241226
Level of compression
unknown
Quality assurance targets
unknown
Reformatting quality
unknown
Specific material designation
remote
System control number
  • on1080434080
  • (OCoLC)1080434080

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