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.

Related Content you might be interested in

Current Title:

Small book image
Hands-On Data Warehousing with Azure Data Factory
Christian Cote | Michelle Gutzait | Giuseppe Ciaburro
May, 2018 | 284 pages
Small book image
ETL with Azure Cookbook
Christian Cote | Matija Lah | Madina Saitakhmetova
Sep, 2020 | 446 pages
Small book image
Azure Data Factory Cookbook
Dmitry Anoshin | Dmitry Foshin | Roman Storchak | Xenia Ireton
Dec, 2020 | 382 pages
Small book image
SQL Server 2017 Integration Services Cookbook
Christian Cote | David Peter Hansen | Dejan Sarka | Matija Lah | Samuel Lester | Christo Olivier
Jun, 2017 | 558 pages
Table of Contents (12 chapters)
Title Page
Title Page
Packt Upsell
Packt Upsell
Contributors
Contributors
Preface
Preface
Free Chapter
1
The Modern Data Warehouse
The Modern Data Warehouse
The need for a data warehouse
The modern data warehouse
What's new in V2.0?
Summary
2
Getting Started with Our First Data Factory
Getting Started with Our First Data Factory
Resource group
Azure Data Factory
Azure Blob storage
Types of blobs
SQL Azure database
Summary
3
SSIS Lift and Shift
SSIS Lift and Shift
SSIS in ADF
Leveraging our package in ADF V2
Summary
4
Azure Data Lake
Azure Data Lake
Creating and configuring Data Lake Store
Creating a Data Lake Analytics resource
Using the data factory to manipulate data in the Data Lake
Run U-SQL from a job in the Data Lake Analytics
Summary
5
Machine Learning on the Cloud
Machine Learning on the Cloud
Machine learning overview
Machine learning tasks
Azure Machine Learning Studio
Breast cancer detection
Summary
6
Introduction to Azure Databricks
Introduction to Azure Databricks
Azure Databricks setup
Prepare the data to ingest
Copy data from SQL Server to sales-data
Databricks notebook
Calling Databricks notebook execution in ADF
Summary
7
Reporting on the Modern Data Warehouse
Reporting on the Modern Data Warehouse
Different types of BI
Power BI consumption
Creating our Power BI reports
Incorporating Spark data
Summary
Index
Index

Chapter 7. Reporting on the Modern Data Warehouse

There are a lot of tools available these days when it comes to reporting. In this book, we'll use Power BI for several reasons:

  • It has a free version. We'll talk about the different versions later in this chapter.
  • It can connect to a wide variety of data sources.
  • There are many transformations and merges that can be applied to the data sources from it.
  • It is easy to use and has a lot of visualizations available.

Power BI is not that new in the reporting world; it has been around for almost 5 years now. It has evolved since then and continues to evolve. Microsoft releases an update to Power BI monthly.

From a modern data warehouse perspective, we need a reporting tool that is flexible enough to accommodate a wide variety of users, from beginners or casual users to power users. As we will see later in this chapter, Power BI can address all of these mentioned users and can also connect to many data sources, be it on the cloud or on-premise.

The next...

Previous Section
End of Section 1
Next Section