Book Image

Pentaho Analytics for MongoDB Cookbook

By : Joel Latino, Harris Ward, Joel André Latino, Harris Ward
Book Image

Pentaho Analytics for MongoDB Cookbook

By: Joel Latino, Harris Ward, Joel André Latino, Harris Ward

Overview of this book

MongoDB is an open source, schemaless NoSQL database system. Pentaho as a famous open source Analysis tool provides high performance, high availability, and easy scalability for large sets of data. The variant features in Pentaho for MongoDB are designed to empower organizations to be more agile and scalable and also enables applications to have better flexibility, faster performance, and lower costs. Whether you are brand new to online learning or a seasoned expert, this book will provide you with the skills you need to create turnkey analytic solutions that deliver insight and drive value for your organization. The book will begin by taking you through Pentaho Data Integration and how it works with MongoDB. You will then be taken through the Kettle Thin JDBC Driver for enabling a Java application to interact with a database. This will be followed by exploration of a MongoDB collection using Pentaho Instant view and creating reports with MongoDB as a datasource using Pentaho Report Designer. The book will then teach you how to explore and visualize your data in Pentaho BI Server using Pentaho Analyzer. You will then learn how to create advanced dashboards with your data. The book concludes by highlighting contributions of the Pentaho Community.
Table of Contents (15 chapters)
Pentaho Analytics for MongoDB Cookbook
About the Authors
About the Reviewers


Migrating data from an RDBMS to a NoSQL database, such as MongoDB, isn't an easy task, especially when your RBDMS has a lot of tables. It can be a time consuming issue, and in most cases, using a manual process is like developing a bespoke solution.

Pentaho Data Integration (or PDI, also known as Kettle) is an Extract, Transform, and Load (ETL) tool that can be used as a solution for this problem. PDI provides a graphical drag-and-drop development environment called Spoon. Primarily, PDI is used to create data warehouses. However, it can also be used for other scenarios, such as migrating data between two databases, exporting data to files with different formats (flat, CSV, JSON, XML, and so on), loading data into databases from many different types of source data, data cleaning, integrating applications, and so on.

The following recipes will focus on the main operations that you need to know to work with PDI and MongoDB.