Reader small image

You're reading from  Hands-On Data Warehousing with Azure Data Factory

Product typeBook
Published inMay 2018
PublisherPackt
ISBN-139781789137620
Edition1st Edition
Tools
Concepts
Right arrow
Authors (3):
Christian Cote
Christian Cote
author image
Christian Cote

Christian Cote is an IT professional with more than 15 years of experience working in a data warehouse, Big Data, and business intelligence projects. Christian developed expertise in data warehousing and data lakes over the years and designed many ETL/BI processes using a range of tools on multiple platforms. He's been presenting at several conferences and code camps. He currently co-leads the SQL Server PASS chapter. He is also a Microsoft Data Platform Most Valuable Professional (MVP).
Read more about Christian Cote

Michelle Gutzait
Michelle Gutzait
author image
Michelle Gutzait

Michelle Gutzait has been in IT for 30 years as a developer, business analyst, and database
Read more about Michelle Gutzait

Giuseppe Ciaburro
Giuseppe Ciaburro
author image
Giuseppe Ciaburro

Giuseppe Ciaburro holds a PhD and two master's degrees. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli". He has over 25 years of work experience in programming, first in the field of combustion and then in acoustics and noise control. His core programming knowledge is in MATLAB, Python and R. As an expert in AI applications to acoustics and noise control problems, Giuseppe has wide experience in researching and teaching. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He was recently included in the world's top 2% scientists list by Stanford University (2022).
Read more about Giuseppe Ciaburro

View More author details
Right arrow

Leveraging our package in ADF V2


So far, we haven't done anything new, in the sense that everything we did was on-premises. This part of the book will focus on cloud leveraging of SSIS packages.

Before ADF V2, the only way to achieve orchestration with SSIS was to schedule our SSIS load on an on-premises (or an Azure) virtual machine, and then schedule an ADF V1.0 pipeline every n amount of minutes. If the data was not available at a specific time, the next ADF run would take it. Or, we had to tell ADF to wait for it before processing the rest of its pipeline.

Also, with the advent of SSIS 2017, the scaling out of package execution had to be done on-premises. There are a couple of issues with it:

  • Who is responsible for the data warehouse data different usage? The developers that create and maintain the packages are not necessarily aware of the cloud implications of their processes. The data might be used in systems other than the ones they had in their specifications, when they first developed...
lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
Hands-On Data Warehousing with Azure Data Factory
Published in: May 2018Publisher: PacktISBN-13: 9781789137620

Authors (3)

author image
Christian Cote

Christian Cote is an IT professional with more than 15 years of experience working in a data warehouse, Big Data, and business intelligence projects. Christian developed expertise in data warehousing and data lakes over the years and designed many ETL/BI processes using a range of tools on multiple platforms. He's been presenting at several conferences and code camps. He currently co-leads the SQL Server PASS chapter. He is also a Microsoft Data Platform Most Valuable Professional (MVP).
Read more about Christian Cote

author image
Michelle Gutzait

Michelle Gutzait has been in IT for 30 years as a developer, business analyst, and database
Read more about Michelle Gutzait

author image
Giuseppe Ciaburro

Giuseppe Ciaburro holds a PhD and two master's degrees. He works at the Built Environment Control Laboratory - Università degli Studi della Campania "Luigi Vanvitelli". He has over 25 years of work experience in programming, first in the field of combustion and then in acoustics and noise control. His core programming knowledge is in MATLAB, Python and R. As an expert in AI applications to acoustics and noise control problems, Giuseppe has wide experience in researching and teaching. He has several publications to his credit: monographs, scientific journals, and thematic conferences. He was recently included in the world's top 2% scientists list by Stanford University (2022).
Read more about Giuseppe Ciaburro