Book Image

Learning Pentaho Data Integration 8 CE - Third Edition

Book Image

Learning Pentaho Data Integration 8 CE - Third Edition

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 (23 chapters)
Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface

Chapter 9. Transforming the Dataset

There are occasions when your dataset does not have the structure you like or the structure you need. The solution is not always about changing or adding fields or about filtering rows. The solution has to do with looking around (rows preceding or succeeding the current one) or altering the whole dataset. This chapter explains techniques to implement this behavior and transform the dataset as a whole, for example, aggregating data or normalizing pivoted tables.

The topics covered will be as follows:

  • Sorting data
  • Working on groups of rows
  • Converting rows to columns called denormalizing
  • Converting columns to rows called normalizing