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

Validating data


It's a fact that data from the real world has errors. In Chapter 2, Getting Started with Transformations, we saw that errors in data can cause a Transformation to crash, and we learned to deal with them. There are other kinds of issues that don't cause the Transformation to abort but don't respect business rules. This section is about detecting these kinds of issues and reporting them.

Validating data with PDI

Validating data is about ensuring that incoming data contains expected values. There are several kinds of constraints that we may need to impose on our data. The following are just some examples:

  • A field must contain only digits
  • A date field must be formatted as MM-dd-yyyyy
  • A field must be either YES or NO
  • The value of a field must exist in a reference table

If a field doesn't respect theses rules or constraints, we have to proceed somehow. Some options are as follows:

  • Reporting the error to the log
  • Inserting the inconsistency into a dedicated table
  • Writing the line with the...