Inne
Miguel Angel Garcia, Barry Harmsen
Business Intelligence technologies are a must-have in every business to make informed decisions and keep up-to speed with the ever-evolving markets. QlikView's disruptive technology makes it a key player and leader in the industry; with its flexibility and powerful analytics environment, building QlikView apps can be mastered by both, business users as well as developers.This book will help you learn QlikView Development from a basic to a practitioner level using a step-by-step approach in a practical environment, and apply proven best practices on each topic.Throughout the book, we will build a QlikView app based on real data about Airline Operations that will help HighCloud Airlines make informed business decisions and analysis-guided strategies. HighCloud Airlines executives are evaluating if entering the US market is a good strategy and, if so, which line of business should they focus their investments on; they need QlikView to make the best decision.The application will be evolving chapter by chapter, along with your skills, going from a simple proof of concept to creating a Data Model, adding a custom style, building a Dashboard and handling and manipulating the source data via script. We will meet the HighCloud Airlines requirement by using many different data visualization objects and time-saving techniques.The whole application uses real data taken from the Bureau of Transportations statistics of the US and encompasses the operations of Airlines both domestic and international. With three years worth of data, you will help HighCloud Airlines discover where people travel the most, which are the Carriers with the most market share, what is the average load factor per airline, which aircraft is the most used to perform flights, which are the busiest airports, and a whole universe of new insights.
Chandraish Sinha
This guide demonstrates just how easy it is to get started with QlikView and create your own BI application. Featuring an introduction to its core features before exploring how to load data and model it, you’ll soon become more confident that you can take full advantage of QlikView’s capabilities.. You will also learn how to use QVD files with QlikView – and how they offer a simpler way of handling data.After digging deeper into data handling, as you learn how to use mapping tables and create a master calendar, you’ll then find out how to get the most from QlikView’s visualization features – vital if you are to use your data insights effectively. From accessible and user friendly dashboards to strategies and best practices for subjecting data to further analysis, you can be confident that you’ll be prepared to get the most out of your data with QlikView.With details on how to finally secure your application and deploy it for a successful integration in your organization, QlikView Essentials underlines exactly why QlikView is becoming more and more popular for businesses that understand the value of data.
Qlikview Unlocked. Unlock more than 50 amazing tips and tricks to enhance your QlikView skills
Roger Stone, Andrew Dove
QlikView Unlocked will provide you with new insights to get the very best from QlikView. This book will help you to develop skills to work with data efficiently. We will cover all the secrets of unleashing the full power of QlikView, which will enable you to make better use of the tool and create better results for future projects. In the course of this book, we will walk you through techniques and best practices that will enable you to be more productive. You will gain quick insights into the tool with the help of short steps called ”keys,” which will help you discover new features of QlikView. Moving on you will learn new techniques for data visualization, scripting, data modeling, and more. This book will then cover best practices to help you establish an efficient system with improved performance. We will also teach you some tricks that will help you speed up development processes, monitor data with dashboards, and so on.By the end of this book, you will have gained beneficial tips, tricks, and techniques to enhance the overall experience of working with QlikView.
R: Data Analysis and Visualization. Master the art of building analytical models using R
Tony Fischetti, Brett Lantz, Hrishi V. Mittal,...
The R learning path created for you has five connected modules, which are a mini-course in their own right. As you complete each one, you'll have gained key skills and be ready for the material in the next module!This course begins by looking at the Data Analysis with R module. This will help you navigate the R environment. You'll gain a thorough understanding of statistical reasoning and sampling. Finally, you'll be able to put best practices into effect to make your job easier and facilitate reproducibility.The second place to explore is R Graphs, which will help you leverage powerful default R graphics and utilize advanced graphics systems such as lattice and ggplot2, the grammar of graphics. You'll learn how to produce, customize, and publish advanced visualizations using this popular and powerful framework.With the third module, Learning Data Mining with R, you will learn how to manipulate data with R using code snippets and be introduced to mining frequent patterns, association, and correlations while working with R programs.The Mastering R for Quantitative Finance module pragmatically introduces both the quantitative finance concepts and their modeling in R, enabling you to build a tailor-made trading system on your own. By the end of the module, you will be well-versed with various financial techniques using R and will be able to place good bets while making financial decisions.Finally, we'll look at the Machine Learning with R module. With this module, you'll discover all the analytical tools you need to gain insights from complex data and learn how to choose the correct algorithm for your specific needs. You'll also learn to apply machine learning methods to deal with common tasks, including classification, prediction, forecasting, and so on.
Prabhanjan Narayanachar Tattar, Yu-Wei, Chiu (David Chiu)
This cookbook offers a range of data analysis samples in simple and straightforward R code, providing step-by-step resources and time-saving methods to help you solve data problems efficiently.The first section deals with how to create R functions to avoid the unnecessary duplication of code. You will learn how to prepare, process, and perform sophisticated ETL for heterogeneous data sources with R packages. An example of data manipulation is provided, illustrating how to use the “dplyr” and “data.table” packages to efficiently process larger data structures. We also focus on “ggplot2” and show you how to create advanced figures for data exploration.In addition, you will learn how to build an interactive report using the “ggvis” package. Later chapters offer insight into time series analysis on financial data, while there is detailed information on the hot topic of machine learning, including data classification, regression, clustering, association rule mining, and dimension reduction.By the end of this book, you will understand how to resolve issues and will be able to comfortably offer solutions to problems encountered while performing data analysis.
Raghav Bali
Data science and machine learning are some of the top buzzwords in the technical world today. From retail stores to Fortune 500 companies, everyone is working hard to making machine learning give them data-driven insights to grow their business. With powerful data manipulation features, machine learning packages, and an active developer community, R empowers users to build sophisticated machine learning systems to solve real-world data problems.This book takes you on a data-driven journey that starts with the very basics of R and machine learning and gradually builds upon the concepts to work on projects that tackle real-world problems.You’ll begin by getting an understanding of the core concepts and definitions required to appreciate machine learning algorithms and concepts. Building upon the basics, you will then work on three different projects to apply the concepts of machine learning, following current trends and cover major algorithms as well as popular R packages in detail. These projects have been neatly divided into six different chapters covering the worlds of e-commerce, finance, and social-media, which are at the very core of this data-driven revolution. Each of the projects will help you to understand, explore, visualize, and derive insights depending upon the domain and algorithms.Through this book, you will learn to apply the concepts of machine learning to deal with data-related problems and solve them using the powerful yet simple language, R.
R: Mining spatial, text, web, and social media data. Create and customize data mining algorithms
Richard Heimann, Nathan H. Danneman, Pradeepta Mishra,...
Data mining is the first step to understanding data and making sense of heaps of data. Properly mined data forms the basis of all data analysis and computing performed on it. This learning path will take you from the very basics of data mining to advanced data mining techniques, and will end up with a specialized branch of data mining—social media mining.You will learn how to manipulate data with R using code snippets and how to mine frequent patterns, association, and correlation while working with R programs. You will discover how to write code for various predication models, stream data, and time-series data. You will also be introduced to solutions written in R based on R Hadoop projects. Now that you are comfortable with data mining with R, you will move on to implementing your knowledge with the help of end-to-end data mining projects. You will learn how to apply different mining concepts to various statistical and data applications in a wide range of fields. At this stage, you will be able to complete complex data mining cases and handle any issues you might encounter during projects.After this, you will gain hands-on experience of generating insights from social media data. You will get detailed instructions on how to obtain, process, and analyze a variety of socially-generated data while providing a theoretical background to accurately interpret your findings. You will be shown R code and examples of data that can be used as a springboard as you get the chance to undertake your own analyses of business, social, or political data.This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:? Learning Data Mining with R by Bater Makhabel ? R Data Mining Blueprints by Pradeepta Mishra? Social Media Mining with R by Nathan Danneman and Richard Heimann
Bruce M. Van Horn II
As a software developer, you need to learn new languages and simultaneously get familiarized with the programming paradigms and methods of leveraging patterns, as both a communications tool and an advantage when designing well-written, easy-to-maintain code. Design patterns, being a collection of best practices, provide the necessary wisdom to help you overcome common sets of challenges in object-oriented design and programming.This practical guide to design patterns helps C# developers put their programming knowledge to work. The book takes a hands-on approach to introducing patterns and anti-patterns, elaborating on 14 patterns along with their real-world implementations. Throughout the book, you'll understand the implementation of each pattern, as well as find out how to successfully implement those patterns in C# code within the context of a real-world project.By the end of this design patterns book, you’ll be able to recognize situations that tempt you to reinvent the wheel, and quickly avoid the time and cost associated with solving common and well-understood problems with battle-tested design patterns.