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"Whether you are brand new to data mining or working on your tenth predictive analytics project, Commercial data mining will be there for you as an accessible reference outlining the entire process and related themes. In this book, you'll learn that your organization does not need a huge volume of data or a Fortune 500 budget to generate business using existing information assets. Expert author David Nettleton guides you through the process from beginning to end and covers everything from business objectives to data sources, and selection to analysis and predictive modeling.Commercial data mining includes case studies and practical examples from Nettleton's more than 20 years of commercial experience. Real-world cases covering customer loyalty, cross-selling, and audience prediction in industries including insurance, banking, and media illustrate the concepts and techniques explained throughout the book."

"Whether you are brand new to data mining or working on your tenth predictive analytics project, Commercial Data Mining will be there for you as an accessible reference outlining the entire process and related themes. In this book, you'll learn that your organization does not need a huge volume of data or a Fortune 500 budget to generate business using existing information assets. Expert author David Nettleton guides you through the process from beginning to end and covers everything from business objectives to data sources, and selection to analysis and predictive modeling."

"This textbook presents a practical approach to predictive analytics for classroom learning. It focuses on using analytics to solve business problems and compares several different modeling techniques, all explained from examples using the SAS Enterprise Miner software. The authors demystify complex algorithms to show how they can be utilized and explained within the context of enhancing business opportunities. Each chapter includes an opening vignette that provides real-life example of how business analytics have been used in various aspects of organizations to solve issue or improve their results. A running case provides an example of a how to build and analyze a complex analytics model and utilize it to predict future outcomes."

"E-commerce dan big data merupakan bukti dari kemajuan teknologi yang sangat pesat. Big data berperan cukup penting dalam perusahaan e-commerce untuk menangani perkembangan semua data, mengolah setiap data tersebut dan menjadi competitive advantage bagi perusahaan. Perusahaan XYZ.com mengalami kesulitan dalam menganalisis stok dan tren dari produk yang dijual. Jika hal ini tidak ditanggulangi, maka perusahaan XYZ.com akan kehilangan opportunity gain. Untuk menentukan tren dan stok produk secara cepat dengan akurat, dibutuhkan big data predictive analysis. Penelitian ini mengolah data transaksi menjadi data yang dapat dianalisis untuk menentukan tren dan prediksi tren produk berdasarkan kategorinya dengan menggunakan big data predictive analysis. Hasil dari penelitian ini akan memberikan informasi kepada pihak manajemen kategori apa yang berpotensi menjadi tren dan jumlah minimal stok yang harus disediakan dari kategori produk tersebut.

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E commerce and big data are evidence of rapid technological advances. Big data plays an important role in e commerce companies to handle and analyze all data changes, and become a competitive advantage for the company. XYZ.com experience a difficulty in analyzing stocks and commerce product trend. If this issue not addressed, XYZ.com company will lose an opportunity gain. To determine trends and stock accurately, XYZ.com can use big data predictive analysis. This study processes transaction data into data that can be analyzed to determine trends and predictions of product trends based on its categories using big data predictive analysis. The results of this study give massive informations to management about what categories will potential become trends and minimum stock required to be provided."

"Data are the prominent elements in scientific researches and approaches. Data Science methodology is used to select and to prepare enormous numbers of data for further processing and analysing. Big Data technology collects vast amount of data from many sources in order to exploit the information and to visualise trend or to discover a certain phenomenon in the past, present, or in the future at high speed processing capability. Predictive analytics provides in-depth analytical insights and the emerging of machine learning brings the data analytics to a higher level by processing raw data with artificial intelligence technology. Predictive analytics and machine learning produce visual reports for decision makers and stake-holders. Regarding cyberspace security, big data promises the opportunities in order to prevent and to detect any advanced cyber-attacks by using internal and external security data."

"This book is a comprehensive introduction to the methods and algorithms and approaches of modern data analytics. It covers data preprocessing, visualization, correlation, regression, forecasting, classification, and clustering. It provides a sound mathematical basis, discusses advantages and drawbacks of different approaches, and enables the reader to design and implement data analytics solutions for real-world applications. Much of the content is based on the results of industrial research and development projects at Siemens."

"Learn the basics of Predictive analysis and data mining through an easy to understand conceptual framework and immediately practice the concepts learned using the open source RapidMiner tool. Whether you are brand new to Data Mining or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Mining has become an essential tool for any enterprise that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, business intelligence and data warehousing professionals and for anyone who wants to learn Data Mining.You’ll be able to :1. Gain the necessary knowledge of different data mining techniques, so that you can select the right technique for a given data problem and create a general purpose analytics process.2. Get up and running fast with more than two dozen commonly used powerful algorithms for predictive analytics using practical use cases.3. Implement a simple step-by-step process for predicting an outcome or discovering hidden relationships from the data using RapidMiner, an open source GUI based data mining tool."