Business Intelligence Techniques

Business Intelligence Techniques PDF Book Detail:
Author: Murugan Anandarajan
Publisher: Springer Science & Business Media
ISBN: 3540247009
Size: 30.35 MB
Format: PDF
Category : Business & Economics
Languages : un
Pages : 268
View: 796

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Book Description: Modern businesses generate huge volumes of accounting data on a daily basis. The recent advancements in information technology have given organizations the ability to capture and store data in an efficient and effective manner. However, there is a widening gap between this data storage and usage of the data. Business intelligence techniques can help an organization obtain and process relevant accounting data quickly and cost efficiently. Such techniques include: query and reporting tools, online analytical processing (OLAP), statistical analysis, text mining, data mining, and visualization. Business Intelligence Techniques is a compilation of chapters written by experts in the various areas. While these chapters stand on their own, taken together they provide a comprehensive overview of how to exploit accounting data in the business environment.

Data Mining For Business Intelligence

Data Mining for Business Intelligence PDF Book Detail:
Author: Galit Shmueli
Publisher: John Wiley & Sons
ISBN: 1118211391
Size: 13.19 MB
Format: PDF
Category : Mathematics
Languages : un
Pages : 428
View: 5564

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Book Description:

Improving E Commerce Web Applications Through Business Intelligence Techniques

Improving E Commerce Web Applications Through Business Intelligence Techniques PDF Book Detail:
Author: Sreedhar, G.
Publisher: IGI Global
ISBN: 1522536477
Size: 25.80 MB
Format: PDF
Category : Business & Economics
Languages : un
Pages : 363
View: 1127

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Book Description: As the Internet becomes increasingly interconnected with modern society, the transition to online business has developed into a prevalent form of commerce. While there exist various advantages and disadvantages to online business, it plays a major role in contemporary business methods. Improving E-Commerce Web Applications Through Business Intelligence Techniques provides emerging research on the core areas of e-commerce web applications. While highlighting the use of data mining, search engine optimization, and online marketing to advance online business, readers will learn how the role of online commerce is becoming more prevalent in modern business. This book is an important resource for vendors, website developers, online customers, and scholars seeking current research on the development and use of e-commerce.

Oracle Business Intelligence With Machine Learning

Oracle Business Intelligence with Machine Learning PDF Book Detail:
Author: Rosendo Abellera
Publisher: Apress
ISBN: 1484232550
Size: 38.93 MB
Format: PDF, ePub, Mobi
Category : Computers
Languages : un
Pages : 199
View: 3061

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Book Description: Use machine learning and Oracle Business Intelligence Enterprise Edition (OBIEE) as a comprehensive BI solution. This book follows a when-to, why-to, and how-to approach to explain the key steps involved in utilizing the artificial intelligence components now available for a successful OBIEE implementation. Oracle Business Intelligence with Machine Learning covers various technologies including using Oracle OBIEE, R Enterprise, Spatial Maps, and machine learning for advanced visualization and analytics. The machine learning material focuses on learning representations of input data suitable for a given prediction problem. This book focuses on the practical aspects of implementing machine learning solutions using the rich Oracle BI ecosystem. The primary objective of this book is to bridge the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to machine learning with OBIEE. What You Will Learn See machine learning in OBIEE Master the fundamentals of machine learning and how it pertains to BI and advanced analytics Gain an introduction to Oracle R Enterprise Discover the practical considerations of implementing machine learning with OBIEE Who This Book Is For Analytics managers, BI architects and developers, and data scientists.

Open Source Intelligence Methods And Tools

Open Source Intelligence Methods and Tools PDF Book Detail:
Author: Nihad A. Hassan
Publisher: Apress
ISBN: 1484232135
Size: 74.26 MB
Format: PDF, Docs
Category : Computers
Languages : un
Pages : 354
View: 5796

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Book Description: Apply Open Source Intelligence (OSINT) techniques, methods, and tools to acquire information from publicly available online sources to support your intelligence analysis. Use the harvested data in different scenarios such as financial, crime, and terrorism investigations as well as performing business competition analysis and acquiring intelligence about individuals and other entities. This book will also improve your skills to acquire information online from both the regular Internet as well as the hidden web through its two sub-layers: the deep web and the dark web. The author includes many OSINT resources that can be used by intelligence agencies as well as by enterprises to monitor trends on a global level, identify risks, and gather competitor intelligence so more effective decisions can be made. You will discover techniques, methods, and tools that are equally used by hackers and penetration testers to gather intelligence about a specific target online. And you will be aware of how OSINT resources can be used in conducting social engineering attacks. Open Source Intelligence Methods and Tools takes a practical approach and lists hundreds of OSINT resources that can be used to gather intelligence from online public sources. The book also covers how to anonymize your digital identity online so you can conduct your searching activities without revealing your identity. What You’ll Learn Identify intelligence needs and leverage a broad range of tools and sources to improve data collection, analysis, and decision making in your organization Use OSINT resources to protect individuals and enterprises by discovering data that is online, exposed, and sensitive and hide the data before it is revealed by outside attackers Gather corporate intelligence about business competitors and predict future market directions Conduct advanced searches to gather intelligence from social media sites such as Facebook and Twitter Understand the different layers that make up the Internet and how to search within the invisible web which contains both the deep and the dark webs Who This Book Is For Penetration testers, digital forensics investigators, intelligence services, military, law enforcement, UN agencies, and for-profit/non-profit enterprises

Fundamentals Of Business Intelligence

Fundamentals of Business Intelligence PDF Book Detail:
Author: Wilfried Grossmann
Publisher: Springer
ISBN: 3662465310
Size: 58.84 MB
Format: PDF, ePub, Docs
Category : Computers
Languages : un
Pages : 348
View: 6172

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Book Description: This book presents a comprehensive and systematic introduction to transforming process-oriented data into information about the underlying business process, which is essential for all kinds of decision-making. To that end, the authors develop step-by-step models and analytical tools for obtaining high-quality data structured in such a way that complex analytical tools can be applied. The main emphasis is on process mining and data mining techniques and the combination of these methods for process-oriented data. After a general introduction to the business intelligence (BI) process and its constituent tasks in chapter 1, chapter 2 discusses different approaches to modeling in BI applications. Chapter 3 is an overview and provides details of data provisioning, including a section on big data. Chapter 4 tackles data description, visualization, and reporting. Chapter 5 introduces data mining techniques for cross-sectional data. Different techniques for the analysis of temporal data are then detailed in Chapter 6. Subsequently, chapter 7 explains techniques for the analysis of process data, followed by the introduction of analysis techniques for multiple BI perspectives in chapter 8. The book closes with a summary and discussion in chapter 9. Throughout the book, (mostly open source) tools are recommended, described and applied; a more detailed survey on tools can be found in the appendix, and a detailed code for the solutions together with instructions on how to install the software used can be found on the accompanying website. Also, all concepts presented are illustrated and selected examples and exercises are provided. The book is suitable for graduate students in computer science, and the dedicated website with examples and solutions makes the book ideal as a textbook for a first course in business intelligence in computer science or business information systems. Additionally, practitioners and industrial developers who are interested in the concepts behind business intelligence will benefit from the clear explanations and many examples.

Business Intelligence In Economic Forecasting Technologies And Techniques

Business Intelligence in Economic Forecasting  Technologies and Techniques PDF Book Detail:
Author: Wang, Jue
Publisher: IGI Global
ISBN: 1615206302
Size: 40.68 MB
Format: PDF, Mobi
Category : Computers
Languages : un
Pages : 406
View: 7076

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Book Description: With the rapid development of economic globalization and information technology, the field of economic forecasting continues its expeditious advancement, providing business and government with applicable technologies. This book discusses various business intelligence techniques including neural networks, support vector machine, genetic programming, clustering analysis, [email protected], fuzzy systems, text mining, and many more. It serves as a valuable reference for professionals and researchers interested in BI technologies and their practical applications in economic forecasting, as well as policy makers in business organizations and governments.

Data Mining For Business Intelligence

Data Mining for Business Intelligence PDF Book Detail:
Author: Galit Shmueli
Publisher: Wiley-Interscience
ISBN:
Size: 72.41 MB
Format: PDF, ePub
Category : Mathematics
Languages : un
Pages : 279
View: 5570

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Book Description: Learn how to develop models for classification, prediction, and customer segmentation with the help of Data Mining for Business Intelligence In today's world, businesses are becoming more capable of accessing their ideal consumers, and an understanding of data mining contributes to this success. Data Mining for Business Intelligence, which was developed from a course taught at the Massachusetts Institute of Technology's Sloan School of Management, and the University of Maryland's Smith School of Business, uses real data and actual cases to illustrate the applicability of data mining intelligence to the development of successful business models. Featuring XLMiner, the Microsoft Office Excel add-in, this book allows readers to follow along and implement algorithms at their own speed, with a minimal learning curve. In addition, students and practitioners of data mining techniques are presented with hands-on, business-oriented applications. An abundant amount of exercises and examples are provided to motivate learning and understanding. Data Mining for Business Intelligence: Provides both a theoretical and practical understanding of the key methods of classification, prediction, reduction, exploration, and affinity analysis Features a business decision-making context for these key methods Illustrates the application and interpretation of these methods using real business cases and data This book helps readers understand the beneficial relationship that can be established between data mining and smart business practices, and is an excellent learning tool for creating valuable strategies and making wiser business decisions.

Data Mining For Business Intelligence

Data Mining for Business Intelligence PDF Book Detail:
Author: Galit Shmueli
Publisher: John Wiley and Sons
ISBN: 1118126041
Size: 17.46 MB
Format: PDF, ePub, Mobi
Category : Mathematics
Languages : un
Pages : 428
View: 3482

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Book Description: Praise for the First Edition " full of vivid and thought-provoking anecdotes needs to be read by anyone with a serious interest in research and marketing." —Research magazine "Shmueli et al. have done a wonderful job in presenting the field of data mining a welcome addition to the literature." —computingreviews.com Incorporating a new focus on data visualization and time series forecasting, Data Mining for Business Intelligence, Second Edition continues to supply insightful, detailed guidance on fundamental data mining techniques. This new edition guides readers through the use of the Microsoft Office Excel add-in XLMiner for developing predictive models and techniques for describing and finding patterns in data. From clustering customers into market segments and finding the characteristics of frequent flyers to learning what items are purchased with other items, the authors use interesting, real-world examples to build a theoretical and practical understanding of key data mining methods, including classification, prediction, and affinity analysis as well as data reduction, exploration, and visualization. The Second Edition now features: Three new chapters on time series forecasting, introducing popular business forecasting methods including moving average, exponential smoothing methods; regression-based models; and topics such as explanatory vs. predictive modeling, two-level models, and ensembles A revised chapter on data visualization that now features interactive visualization principles and added assignments that demonstrate interactive visualization in practice Separate chapters that each treat k-nearest neighbors and Naïve Bayes methods Summaries at the start of each chapter that supply an outline of key topics The book includes access to XLMiner, allowing readers to work hands-on with the provided data. Throughout the book, applications of the discussed topics focus on the business problem as motivation and avoid unnecessary statistical theory. Each chapter concludes with exercises that allow readers to assess their comprehension of the presented material. The final chapter includes a set of cases that require use of the different data mining techniques, and a related Web site features data sets, exercise solutions, PowerPoint slides, and case solutions. Data Mining for Business Intelligence, Second Edition is an excellent book for courses on data mining, forecasting, and decision support systems at the upper-undergraduate and graduate levels. It is also a one-of-a-kind resource for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology.

Mastering Tableau 2021

Mastering Tableau 2021 PDF Book Detail:
Author: Marleen Meier
Publisher: Packt Publishing Ltd
ISBN: 1800560745
Size: 30.70 MB
Format: PDF, Kindle
Category : Computers
Languages : un
Pages : 792
View: 4057

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Book Description: The perfect guide to master your Tableau skills and become a BI expert. You will learn to build advanced dashboards and improve your storytelling to derive key business insights. An all-in-one resource to become well versed with advanced functionalities of Tableau in the business intelligence domain.