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SQL Server data automation through f...

Leonard, Andy.

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SQL Server data automation through frameworks = building metadata-driven frameworks with T-SQL, SSIS, and Azure Data Factory /

Record Type:	Electronic resources : Monograph/item
Title/Author:	SQL Server data automation through frameworks/ by Andy Leonard, Kent Bradshaw.
Reminder of title:	building metadata-driven frameworks with T-SQL, SSIS, and Azure Data Factory /
Author:	Leonard, Andy.
other author:	Bradshaw, Kent.
Published:	Berkeley, CA :Apress : : 2020.,
Description:	xx, 391 p. :ill., digital ;24 cm.
[NT 15003449]:	Part I: Stored Procedure-Based Database Frameworks -- 1. Stored Procedures 101 -- 2. Automation with Stored Procedures -- 3. Stored Procedure Orchestrators -- 4. A Stored Procedure-Base Metadata-Driven Framework -- Part II: SSIS Frameworks -- 5. A Simple Custom File-Based SSIS Framework -- 6. Framework Execution Engine -- 7. Framework Logging -- 8. Azure-SSIS Integration Runtime -- 9. Deploy A Simple Custom File-Based Azure-SSIS Framework -- 10. Framework Logging in ADF -- 11. Fault Tolerance in the ADF Framework.
Contained By:	Springer Nature eBook
Subject:	Client/server computing. -
Online resource:	https://doi.org/10.1007/978-1-4842-6213-9
ISBN:	9781484262139

SQL Server data automation through frameworks = building metadata-driven frameworks with T-SQL, SSIS, and Azure Data Factory /
Leonard, Andy.

SQL Server data automation through frameworksbuilding metadata-driven frameworks with T-SQL, SSIS, and Azure Data Factory /[electronic resource] :by Andy Leonard, Kent Bradshaw. - Berkeley, CA :Apress :2020. - xx, 391 p. :ill., digital ;24 cm.

Part I: Stored Procedure-Based Database Frameworks -- 1. Stored Procedures 101 -- 2. Automation with Stored Procedures -- 3. Stored Procedure Orchestrators -- 4. A Stored Procedure-Base Metadata-Driven Framework -- Part II: SSIS Frameworks -- 5. A Simple Custom File-Based SSIS Framework -- 6. Framework Execution Engine -- 7. Framework Logging -- 8. Azure-SSIS Integration Runtime -- 9. Deploy A Simple Custom File-Based Azure-SSIS Framework -- 10. Framework Logging in ADF -- 11. Fault Tolerance in the ADF Framework.

Learn to automate SQL Server operations using frameworks built from metadata-driven stored procedures and SQL Server Integration Services (SSIS) Bring all the power of Transact-SQL (T-SQL) and Microsoft .NET to bear on your repetitive data, data integration, and ETL processes. Do this for no added cost over what you've already spent on licensing SQL Server. The tools and methods from this book may be applied to on-premises and Azure SQL Server instances. The SSIS framework from this book works in Azure Data Factory (ADF) and provides DevOps personnel the ability to execute child packages outside a project-functionality not natively available in SSIS. Frameworks not only reduce the time required to deliver enterprise functionality, but can also accelerate troubleshooting and problem resolution. You'll learn in this book how frameworks also improve code quality by using metadata to drive processes. Much of the work performed by data professionals can be classified as "drudge work"-tasks that are repetitive and template-based. The frameworks-based approach shown in this book helps you to avoid that drudgery by turning repetitive tasks into "one and done" operations. Frameworks as described in this book also support enterprise DevOps with built-in logging functionality. You will: Create a stored procedure framework to automate SQL process execution Base your framework on a working system of stored procedures and execution logging Create an SSIS framework to reduce the complexity of executing multiple SSIS packages Deploy stored procedure and SSIS frameworks to Azure Data Factory environments in the cloud.

ISBN: 9781484262139

Standard No.: 10.1007/978-1-4842-6213-9doiSubjects--Uniform Titles:

SQL server.
Subjects--Topical Terms:

532546
Client/server computing.

LC Class. No.: QA76.9.D3 / L46 2020

Dewey Class. No.: 005.7585

SQL Server data automation through frameworks = building metadata-driven frameworks with T-SQL, SSIS, and Azure Data Factory /
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