Book Image

Hands-On Data Warehousing with Azure Data Factory

By : Christian Cote, Michelle Gutzait, Giuseppe Ciaburro
Book Image

Hands-On Data Warehousing with Azure Data Factory

By: Christian Cote, Michelle Gutzait, Giuseppe Ciaburro

Overview of this book

ETL is one of the essential techniques in data processing. Given data is everywhere, ETL will always be the vital process to handle data from different sources. Hands-On Data Warehousing with Azure Data Factory starts with the basic concepts of data warehousing and ETL process. You will learn how Azure Data Factory and SSIS can be used to understand the key components of an ETL solution. You will go through different services offered by Azure that can be used by ADF and SSIS, such as Azure Data Lake Analytics, Machine Learning and Databrick’s Spark with the help of practical examples. You will explore how to design and implement ETL hybrid solutions using different integration services with a step-by-step approach. Once you get to grips with all this, you will use Power BI to interact with data coming from different sources in order to reveal valuable insights. By the end of this book, you will not only learn how to build your own ETL solutions but also address the key challenges that are faced while building them.
Table of Contents (12 chapters)

Different types of BI

In this section, we will discuss various types of BI depending on the use cases.

Self-service – personal

This is the type of BI or reports that users will work upon themselves. In this scenario, they use Power BI for desktop to connect to the data sources they want to, whether they are in the data warehouse or anywhere else on the cloud, such as Twitter feeds, data lakes, Spark, and so on.

Most of these sources require that users import data in the Power BI data model to their local machine. If the data source contains a large amount of data, this can consume a lot of resources. But in this mode, data can be altered, in the sense that the source data can be merged or transformed. No live connection is needed to connect to the data as it is imported to Power BI's underlying model. This model is meant to allow users to explore their data and modify it to suit their needs better. They have almost complete control over it.

If the data source is an SQL Server relational database...