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

Product typeBook
Published inMay 2018
PublisherPackt
ISBN-139781789137620
Edition1st Edition
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Authors (3):
Christian Cote
Christian Cote
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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

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The need for a data warehouse


A data warehouse is a repository of enterprise data used for reporting and analysis. There have been three waves of data warehouses so far, which we will cover in the upcoming subsections.

Driven by IT

This is the first wave of business intelligence (BI). IT needed to separate operational data and databases from its origin for the following reasons:

  • Keep data changes history. Some operational applications purge the data after a while.
  • When users wanted to report on the application's data, they were often affecting the performance of the system. IT replicated the operational data to another server to avoid any performance impact on applications.
  • Things got more complex when users wanted to do analysis and reports on databases from multiple enterprise's applications. IT had to replicate all the needed systems and make them speak together. This implied that new structures had to be built and new patterns emerged from there: star schemas, decision support systems (DSS), OLAP cubes, and so on.

Self-service BI

Analysts and users always need data warehouses to evolve at a faster pace. This is the second wave of BI and it happened when major BI players such as Microsoft and Click came with tools that enabled users to merge some data with or without data warehouses. In many enterprises, this is used as a temporary source of analytics or proof of concept. On the other hand, not every data could fit at that time in data warehouses. Many ad hoc reports were, and are still, using self-service BI tools. Here is a short list of such tools:

  • Microsoft Power Pivot
  • Microsoft Power BI
  • Click

Cloud-based BI – big data and artificial intelligence

This is the third wave of BI. The cloud capabilities enable enterprises to do more accurate analysis. Big data technologies allows users to base their analysis on much bigger data volumes. This helps them deriving patterns form the data and have technologies that incorporate and modify these patterns. This leads to artificial intelligence or AI.

Technologies used in big data are not that new. They were used by many search engines in the early 21st century such as Yahoo! and Google. They have also been used quite a lot in research faculties in different enterprises. The third wave of BI broaden the usage of these technologies. Vendors such as Microsoft, Amazon, or Google make it available to almost everyone with their cloud offer.]

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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