Book Image

Pentaho 3.2 Data Integration: Beginner's Guide

Book Image

Pentaho 3.2 Data Integration: Beginner's Guide

Overview of this book

Pentaho Data Integration (a.k.a. Kettle) is a full-featured open source ETL (Extract, Transform, and Load) solution. Although PDI is a feature-rich tool, effectively capturing, manipulating, cleansing, transferring, and loading data can get complicated.This book is full of practical examples that will help you to take advantage of Pentaho Data Integration's graphical, drag-and-drop design environment. You will quickly get started with Pentaho Data Integration by following the step-by-step guidance in this book. The useful tips in this book will encourage you to exploit powerful features of Pentaho Data Integration and perform ETL operations with ease.Starting with the installation of the PDI software, this book will teach you all the key PDI concepts. Each chapter introduces new features, allowing you to gradually get involved with the tool. First, you will learn to work with plain files, and to do all kinds of data manipulation. Then, the book gives you a primer on databases and teaches you how to work with databases inside PDI. Not only that, you'll be given an introduction to data warehouse concepts and you will learn to load data in a data warehouse. After that, you will learn to implement simple and complex processes.Once you've learned all the basics, you will build a simple datamart that will serve to reinforce all the concepts learned through the book.
Table of Contents (27 chapters)
Pentaho 3.2 Data Integration Beginner's Guide
Credits
Foreword
The Kettle Project
About the Author
About the Reviewers
Preface
Index

Exploring the sales datamart


In Chapter 9, you were introduced to star schemas. In short, a star schema consists of a central table known as the fact table, surrounded by dimension tables. While the fact has indicators of your business such as sales in dollars, the dimensions have descriptive information for the attributes of your business such as time, customers, and products.

A star that addresses a specific department's needs or that is built for use by a particular group of users is called a datamart. You can have datamarts focused on customer relationship management, inventory, human resources management, budget, and more. In this chapter, you will load a datamart focused on sales.

Sometimes the term datamart is confused with datawarehouse. However, datamarts and datawarehouses are not the same.

Note

The main difference between datamarts and datawarehouses is that datawarehouses address the needs of the whole organization, whereas a datamarts addresses the needs of a particular department...