Over 50 recipes to learn how to use Pentaho Analytics and MongoDB to create powerful analysis and reporting solutions About This Book Create reports and stunning dashboards with MongoDB data Accelerate data access and maximize productivity with unique features of Pentaho for MongoDB A step-by-step recipe-based guide for making full use of Pentaho suite tools with MongoDB Who This Book Is For This book is intended for data architects and developers with a basic level of knowledge of MongoDB. Familiarity with Pentaho is not expected. What You Will Learn Extract, load, and transform data from MongoDB collections to other datasources Design Pentaho Reports using different types of connections for MongoDB Create a OLAP mondrian schema for MongoDB Explore your MongoDB data using Pentaho Analyzer Utilize the drag and drop web interface to create dashboards Use Kettle Thin JDBC with MongoDB for analysis Integrate advanced dashboards with MondoDB using different types of connections Publish and run a report on Pentaho BI server using a web interface In Detail 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. Style and approach A comprehensive, recipe-based guide to take complete advantage of the Pentaho Analytics for MongoDB.

Over 60 practical recipes on data exploration and analysis About This Book Clean dirty data, extract accurate information, and explore the relationships between variables Forecast the output of an electric plant and the water flow of American rivers using pandas, NumPy, Statsmodels, and scikit-learn Find and extract the most important features from your dataset using the most efficient Python libraries Who This Book Is For If you are a beginner or intermediate-level professional who is looking to solve your day-to-day, analytical problems with Python, this book is for you. Even with no prior programming and data analytics experience, you will be able to finish each recipe and learn while doing so. What You Will Learn Read, clean, transform, and store your data usng Pandas and OpenRefine Understand your data and explore the relationships between variables using Pandas and D3.js Explore a variety of techniques to classify and cluster outbound marketing campaign calls data of a bank using Pandas, mlpy, NumPy, and Statsmodels Reduce the dimensionality of your dataset and extract the most important features with pandas, NumPy, and mlpy Predict the output of a power plant with regression models and forecast water flow of American rivers with time series methods using pandas, NumPy, Statsmodels, and scikit-learn Explore social interactions and identify fraudulent activities with graph theory concepts using NetworkX and Gephi Scrape Internet web pages using urlib and BeautifulSoup and get to know natural language processing techniques to classify movies ratings using NLTK Study simulation techniques in an example of a gas station with agent-based modeling In Detail Data analysis is the process of systematically applying statistical and logical techniques to describe and illustrate, condense and recap, and evaluate data. Its importance has been most visible in the sector of information and communication technologies. It is an employee asset in almost all economy sectors. This book provides a rich set of independent recipes that dive into the world of data analytics and modeling using a variety of approaches, tools, and algorithms. You will learn the basics of data handling and modeling, and will build your skills gradually toward more advanced topics such as simulations, raw text processing, social interactions analysis, and more. First, you will learn some easy-to-follow practical techniques on how to read, write, clean, reformat, explore, and understand your data—arguably the most time-consuming (and the most important) tasks for any data scientist. In the second section, different independent recipes delve into intermediate topics such as classification, clustering, predicting, and more. With the help of these easy-to-follow recipes, you will also learn techniques that can easily be expanded to solve other real-life problems such as building recommendation engines or predictive models. In the third section, you will explore more advanced topics: from the field of graph theory through natural language processing, discrete choice modeling to simulations. You will also get to expand your knowledge on identifying fraud origin with the help of a graph, scrape Internet websites, and classify movies based on their reviews. By the end of this book, you will be able to efficiently use the vast array of tools that the Python environment has to offer. Style and approach This hands-on recipe guide is divided into three sections that tackle and overcome real-world data modeling problems faced by data analysts/scientist in their everyday work. Each independent recipe is written in an easy-to-follow and step-by-step fashion.

This is an easy-to-follow guide on the key integration points between Pentaho and MongoDB. This book employs a practical approach designed to have Pentaho configured to talk to MongoDB early on so that you see rapid results. This book is intended for business analysts, data architects, and developers new to either Pentaho or MongoDB who want to be able to deliver a complete solution for storing, processing, and visualizing data. It's assumed that you will already have experience defining data requirements needed to support business processes and exposure to database modeling, SQL query, and rep.

Pentaho Data Integration Cookbook Second Edition is written in a cookbook format, presenting examples in the style of recipes.This allows you to go directly to your topic of interest, or follow topics throughout a chapter to gain a thorough in-depth knowledge.Pentaho Data Integration Cookbook Second Edition is designed for developers who are familiar with the basics of Kettle but who wish to move up to the next level.It is also aimed at advanced users that want to learn how to use the new features of PDI as well as and best practices for working with Kettle.

Acquire finesse with CTools features and build rich and custom analytics solutions using Pentaho About This Book Learn everything you need to know to make the most of CTools Create interactive and remarkable dashboards using the CTools Understand how to use and create data visualizations that can make the difference The author of our book works for Pentaho as a Senior Consultant Acts as a follow-up to Packt's previously published products on Pentaho such as Pentaho Business Analytics Cookbook, Pentaho Analytics for MongoDB, Pentaho Data Integration Cookbook - Second Edition, and Pentaho Reporting [Video] Our book is based on the latest version of Pentaho, that is, 6.0 Who This Book Is For If you are a CTools developer and would like to expand your knowledge and create attractive dashboards and frameworks, this book is the go-to-guide for you. A basic knowledge of JavaScript and Cascading Style Sheets (CSS) is highly recommended. What You Will Learn Install Community Tools on Pentaho; and understand the necessary concepts and considerations when creating an exciting dashboard design Get data from many different Pentaho datasources and deliver it in different formats (CSV, XLS, XML, or JSON) Use the Community Data Access (CDA) as the data abstraction layer and understand the concepts in the Community Dashboard Framework (CDF) Create a Community Dashboard Editor (CDE) dashboard and make the most of the main components Create and make use of widgets and use duplicate components to have data-driven sections on the dashboard Customize and create interaction between all components, including charts, using the Community Charts Components Create and embed dashboards in a better and new way Create plugins and make use of parameters inside Pentaho without writing code In Detail Pentaho and CTools are two of the fastest and most rapidly growing tools for practical solutions not found in any other tool available on the market. Using Pentaho allows you to build a complete analytics solution, and CTools brings an advanced flexibility to customizing them in a remarkable way. CTools provides its users with the ability to utilize Web technologies and data visualization concepts, and make the most of best practices to create a huge visual impact. The book starts with the basics of the framework and how to get data to your dashboards. We'll take you all the way through to create your custom and advanced dashboards that will create an effective visual impact and provide the best user experience. You will be given deep insights into the lifecycle of dashboards and the working of various components. Further, you will create a custom dashboard using the Community Dashboards Editor and use datasources to load data on the components. You will also create custom content using Query, the Freeform Addins Popup, and text components. Next, you will make use of widgets to create similar sections and duplicate components to reproduce other components on a dashboard. You will then learn to build a plugin without writing Java code, use Sparkl as a CPK plugin manager, and understand the application of deployment and version control to dashboard development. Finally, you will learn tips and tricks that can be very useful while embedding dashboards into other applications. This guide is an invaluable tutorial if you are planning to use custom and advanced dashboards among the solutions that you are building with Pentaho. Style and approach This book is a pragmatic, easy-to-follow guide that provides theoretical concepts, ideas, and tricks to better understand the necessary theoretical concepts. It also provides you with a set of highly intriguing samples of dashboards with customized code within them that can be utilized for future projects.

A complete guide to Pentaho Kettle, the Pentaho Data lntegration toolset for ETL This practical book is a complete guide to installing, configuring, and managing Pentaho Kettle. If you’re a database administrator or developer, you’ll first get up to speed on Kettle basics and how to apply Kettle to create ETL solutions—before progressing to specialized concepts such as clustering, extensibility, and data vault models. Learn how to design and build every phase of an ETL solution. Shows developers and database administrators how to use the open-source Pentaho Kettle for enterprise-level ETL processes (Extracting, Transforming, and Loading data) Assumes no prior knowledge of Kettle or ETL, and brings beginners thoroughly up to speed at their own pace Explains how to get Kettle solutions up and running, then follows the 34 ETL subsystems model, as created by the Kimball Group, to explore the entire ETL lifecycle, including all aspects of data warehousing with Kettle Goes beyond routine tasks to explore how to extend Kettle and scale Kettle solutions using a distributed “cloud” Get the most out of Pentaho Kettle and your data warehousing with this detailed guide—from simple single table data migration to complex multisystem clustered data integration tasks.