Book Image

Learning Pentaho Data Integration 8 CE - Third Edition

By : Carina Roldán
Book Image

Learning Pentaho Data Integration 8 CE - Third Edition

By: Carina Roldán

Overview of this book

Pentaho Data Integration(PDI) is an intuitive and graphical environment packed with drag-and-drop design and powerful Extract-Tranform-Load (ETL) capabilities. This book shows and explains the new interactive features of Spoon, the revamped look and feel, and the newest features of the tool including transformations and jobs Executors and the invaluable Metadata Injection capability. We begin with the installation of PDI software and then move on to cover all the key PDI concepts. Each of the chapter introduces new features, enabling you to gradually get practicing with the tool. First, you will learn to do all kind of data manipulation and work with simple plain files. Then, the book teaches you how you can work with relational databases inside PDI. Moreover, you will be given a primer on data warehouse concepts and you will learn how to load data in a data warehouse. During the course of this book, you will be familiarized with its intuitive, graphical and drag-and-drop design environment. By the end of this book, you will learn everything you need to know in order to meet your data manipulation requirements. Besides, your will be given best practices and advises for designing and deploying your projects.
Table of Contents (17 chapters)

Normalizing data


Some datasets are nice to view but complicated for further processing. Take a look at the following information about product sales, aggregated by year and product line:

Product sales

Suppose that you want to answer the following questions:

  • Which product line was the best sold?
  • How many cars did you sell (including Classic and Vintage)?
  • Which is the average price per product sold?

The dataset is not prepared to answer these questions, at least in an easy way. In order to simplify the task, you will have to normalize the data first, that is, convert it to a suitable format before proceeding. The next subsection explains how to do that.

Modifying the dataset with a Row Normaliser step

The Row Normaliser step takes a pivoted dataset and normalizes the data. In simple words, it converts columns to rows. In order to explain how to use and configure the step, we will normalize the data shown earlier. Our purpose, in this case, will be to have something like this:

Product sales normalized...