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Business Intelligence Techniques
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Book Synopsis Business Intelligence Techniques by : Murugan Anandarajan
Download or read book Business Intelligence Techniques written by Murugan Anandarajan and published by Springer Science & Business Media. This book was released on 2012-11-02 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Data Mining for Business Analytics by : Galit Shmueli
Download or read book Data Mining for Business Analytics written by Galit Shmueli and published by John Wiley & Sons. This book was released on 2019-10-14 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R
Book Synopsis Seven Methods for Transforming Corporate Data Into Business Intelligence by : Vasant Dhar
Download or read book Seven Methods for Transforming Corporate Data Into Business Intelligence written by Vasant Dhar and published by . This book was released on 1997 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information systems: past, present, and emerging; Intelligence density a metric for knowledge work; The vocabulary of intelligence density; Method one: data-driven decision support; Method two: evolving solutions: genetic algorithms; Method three: simulating the brain to solve problems: neural networks; Method four: putting expert resoning in a box: rule-based systems; Method five: dealing with linguistic ambiguity: fuzzy logic; Method six: soilving problems by analogy case-based resoning; Method seven: deriving rules from data: machine learning; Appendix saving time and money with object; Appendix case studies.
Book Synopsis Business Intelligence in Economic Forecasting: Technologies and Techniques by : Wang, Jue
Download or read book Business Intelligence in Economic Forecasting: Technologies and Techniques written by Wang, Jue and published by IGI Global. This book was released on 2010-06-30 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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, TEI@I, 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.
Book Synopsis Business Intelligence by : David Loshin
Download or read book Business Intelligence written by David Loshin and published by Newnes. This book was released on 2012-11-27 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Business Intelligence: The Savvy Managers Guide, Second Edition, discusses the objectives and practices for designing and deploying a business intelligence (BI) program. It looks at the basics of a BI program, from the value of information and the mechanics of planning for success to data model infrastructure, data preparation, data analysis, integration, knowledge discovery, and the actual use of discovered knowledge. Organized into 21 chapters, this book begins with an overview of the kind of knowledge that can be exposed and exploited through the use of BI. It then proceeds with a discussion of information use in the context of how value is created within an organization, how BI can improve the ways of doing business, and organizational preparedness for exploiting the results of a BI program. It also looks at some of the critical factors to be taken into account in the planning and execution of a successful BI program. In addition, the reader is introduced to considerations for developing the BI roadmap, the platforms for analysis such as data warehouses, and the concepts of business metadata. Other chapters focus on data preparation and data discovery, the business rules approach, and data mining techniques and predictive analytics. Finally, emerging technologies such as text analytics and sentiment analysis are considered. This book will be valuable to data management and BI professionals, including senior and middle-level managers, Chief Information Officers and Chief Data Officers, senior business executives and business staff members, database or software engineers, and business analysts. Guides managers through developing, administering, or simply understanding business intelligence technology Keeps pace with the changes in best practices, tools, methods and processes used to transform an organization’s data into actionable knowledge Contains a handy, quick-reference to technologies and terminology
Book Synopsis Mastering Tableau by : David Baldwin
Download or read book Mastering Tableau written by David Baldwin and published by Packt Publishing Ltd. This book was released on 2016-12-06 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the intricacies of Tableau to create effective data visualizations About This Book Arm yourself with an arsenal of advanced chart types and geocoding to efficiently and engagingly present information Map a grid over a network node diagram and use that grid to demonstrate loads, processing time, and more in Tableau Integrate R with Tableau by utilizing R functions, libraries, and saved models Who This Book Is For If you are a business analyst without developer-level programming skills, then this book is for you. You are expected to have at least a fundamental understanding of Tableau and basic knowledge of joins, however SQL knowledge is not assumed. You should have basic computer skills, including at least moderate Excel proficiency. What You Will Learn Create a worksheet that can display the current balance for any given period in time Recreate a star schema from in a data warehouse in Tableau Combine level of detail calculations with table calculations, sets, and parameters Create custom polygons to build filled maps for area codes in the USA Visualize data using a set of analytical and advanced charting techniques Know when to use Tableau instead of PowerPoint Build a dashboard and export it to PowerPoint In Detail Tableau has emerged as one of the most popular Business Intelligence solutions in recent times, thanks to its powerful and interactive data visualization capabilities. This book will empower you to become a master in Tableau by exploiting the many new features introduced in Tableau 10.0. You will embark on this exciting journey by getting to know the valuable methods of utilizing advanced calculations to solve complex problems. These techniques include creative use of different types of calculations such as row-level, aggregate-level, and more. You will discover how almost any data visualization challenge can be met in Tableau by getting a proper understanding of the tool's inner workings and creatively exploring possibilities. You'll be armed with an arsenal of advanced chart types and techniques to enable you to efficiently and engagingly present information to a variety of audiences through the use of clear, efficient, and engaging dashboards. Explanations and examples of efficient and inefficient visualization techniques, well-designed and poorly designed dashboards, and compromise options when Tableau consumers will not embrace data visualization will build on your understanding of Tableau and how to use it efficiently. By the end of the book, you will be equipped with all the information you need to create effective dashboards and data visualization solutions using Tableau. Style and approach This book takes a direct approach, to systematically evolve to more involved functionalities such as advanced calculation, parameters & sets, data blending and R integration. This book will help you gain skill in building visualizations previously beyond your capacity.
Book Synopsis Fundamentals of Business Intelligence by : Wilfried Grossmann
Download or read book Fundamentals of Business Intelligence written by Wilfried Grossmann and published by Springer. This book was released on 2015-06-02 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Adaptive Business Intelligence by : Zbigniew Michalewicz
Download or read book Adaptive Business Intelligence written by Zbigniew Michalewicz and published by Springer Science & Business Media. This book was released on 2006-12-02 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive business intelligence systems combine prediction and optimization techniques to assist decision makers in complex, rapidly changing environments. These systems address fundamental questions: What is likely to happen in the future? What is the best course of action? Adaptive Business Intelligence explores elements of data mining, predictive modeling, forecasting, optimization, and adaptability. The book explains the application of numerous prediction and optimization techniques, and shows how these concepts can be used to develop adaptive systems. Coverage includes linear regression, time-series forecasting, decision trees and tables, artificial neural networks, genetic programming, fuzzy systems, genetic algorithms, simulated annealing, tabu search, ant systems, and agent-based modeling.
Book Synopsis Oracle Business Intelligence with Machine Learning by : Rosendo Abellera
Download or read book Oracle Business Intelligence with Machine Learning written by Rosendo Abellera and published by Apress. This book was released on 2017-12-18 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Data Mining for Business Intelligence by : Galit Shmueli
Download or read book Data Mining for Business Intelligence written by Galit Shmueli and published by John Wiley and Sons. This book was released on 2011-06-10 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Mastering Tableau 2021 by : Marleen Meier
Download or read book Mastering Tableau 2021 written by Marleen Meier and published by Packt Publishing Ltd. This book was released on 2021-05-31 with total page 793 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build, design, and improve advanced business intelligence solutions using Tableau's latest features, including Tableau Prep Builder, Tableau Hyper, and Tableau Server Key FeaturesMaster new features in Tableau 2021 to solve real-world analytics challengesPerform geo-spatial, time series, and self-service analytics using real-life examplesBuild and publish dashboards and explore storytelling using Python and R integration supportBook Description Tableau is one of the leading business intelligence (BI) tools that can help you solve data analysis challenges. With this book, you will master Tableau's features and offerings in various paradigms of the BI domain. Updated with fresh topics including Quick Level of Detail expressions, the newest Tableau Server features, Einstein Discovery, and more, this book covers essential Tableau concepts and advanced functionalities. Leveraging Tableau Hyper files and using Prep Builder, you'll be able to perform data preparation and handling easily. You'll gear up to perform complex joins, spatial joins, unions, and data blending tasks using practical examples. Next, you'll learn how to execute data densification and further explore expert-level examples to help you with calculations, mapping, and visual design using Tableau extensions. You'll also learn about improving dashboard performance, connecting to Tableau Server and understanding data visualization with examples. Finally, you'll cover advanced use cases such as self-service analysis, time series analysis, and geo-spatial analysis, and connect Tableau to Python and R to implement programming functionalities within it. By the end of this Tableau book, you'll have mastered the advanced offerings of Tableau 2021 and be able to tackle common and advanced challenges in the BI domain. What you will learnGet up to speed with various Tableau componentsMaster data preparation techniques using Tableau Prep BuilderDiscover how to use Tableau to create a PowerPoint-like presentationUnderstand different Tableau visualization techniques and dashboard designsInteract with the Tableau server to understand its architecture and functionalitiesStudy advanced visualizations and dashboard creation techniquesBrush up on powerful self-service analytics, time series analytics, and geo-spatial analyticsWho this book is for This book is designed for business analysts, business intelligence professionals and data analysts who want to master Tableau to solve a range of data science and business intelligence problems. The book is ideal if you have a good understanding of Tableau and want to take your skills to the next level.
Book Synopsis Improving E-Commerce Web Applications Through Business Intelligence Techniques by : Sreedhar, G.
Download or read book Improving E-Commerce Web Applications Through Business Intelligence Techniques written by Sreedhar, G. and published by IGI Global. This book was released on 2018-02-02 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Business Intelligence Using Smart Techniques by : Charles Halliman
Download or read book Business Intelligence Using Smart Techniques written by Charles Halliman and published by . This book was released on 2001 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Business Intelligence Strategy by : John Boyer
Download or read book Business Intelligence Strategy written by John Boyer and published by MC Press. This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geared toward IT management and business executives seeking to excel in business intelligence initiatives, this practical guide explores creating business alignment strategies that help prioritize business requirements, build organizational and cultural strategies, increase IT efficiency, and promote user adoption. Business intelligence, together with business analytics and performance management, eliminates information overload by organizing the massive amounts of information available in the modern enterprise. Addressing the challenges of business intelligence operations, this resource supports the goal of better business decision making and identifying unrealized opportunities. Each chapter includes a checklist of recommended approaches and a strategy overview template.
Book Synopsis Managing Data in Motion by : April Reeve
Download or read book Managing Data in Motion written by April Reeve and published by Newnes. This book was released on 2013-02-26 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Managing Data in Motion describes techniques that have been developed for significantly reducing the complexity of managing system interfaces and enabling scalable architectures. Author April Reeve brings over two decades of experience to present a vendor-neutral approach to moving data between computing environments and systems. Readers will learn the techniques, technologies, and best practices for managing the passage of data between computer systems and integrating disparate data together in an enterprise environment. The average enterprise's computing environment is comprised of hundreds to thousands computer systems that have been built, purchased, and acquired over time. The data from these various systems needs to be integrated for reporting and analysis, shared for business transaction processing, and converted from one format to another when old systems are replaced and new systems are acquired. The management of the "data in motion" in organizations is rapidly becoming one of the biggest concerns for business and IT management. Data warehousing and conversion, real-time data integration, and cloud and "big data" applications are just a few of the challenges facing organizations and businesses today. Managing Data in Motion tackles these and other topics in a style easily understood by business and IT managers as well as programmers and architects. Presents a vendor-neutral overview of the different technologies and techniques for moving data between computer systems including the emerging solutions for unstructured as well as structured data types Explains, in non-technical terms, the architecture and components required to perform data integration Describes how to reduce the complexity of managing system interfaces and enable a scalable data architecture that can handle the dimensions of "Big Data"
Book Synopsis Business Intelligence and Analytics: Concepts, Techniques and Applications by : Samuel Brooks
Download or read book Business Intelligence and Analytics: Concepts, Techniques and Applications written by Samuel Brooks and published by Murphy & Moore Publishing. This book was released on 2021-11-16 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Business intelligence and analytics refers to the set of techniques and strategies which are used by enterprises to convert raw data into meaningful information which drive profitable business actions. These techniques can give insights into historical, current and predictive views of business operations. Some common features of business intelligence technologies are analytics, reporting, benchmarking, data mining, business performance management, predictive analytics, complex event processing and prescriptive analytics. Technologies used in business intelligence are capable of handling both structured and unstructured data. While understanding the long-term perspectives of the topics, the book makes an effort in highlighting their impact as a modern tool for the growth of this discipline business intelligence. The topics included herein on business intelligence are of utmost significance and bound to provide incredible insights to readers. Those in search of information to further their knowledge will be greatly assisted by this book.
Book Synopsis Computing Predictive Analytics, Business Intelligence, and Economics by : Cyrus F. Nourani
Download or read book Computing Predictive Analytics, Business Intelligence, and Economics written by Cyrus F. Nourani and published by CRC Press. This book was released on 2019-06-26 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume brings together research and system designs that address the scientific basis and the practical systems design issues that support areas ranging from intelligent business interfaces and predictive analytics to economics modeling. Applications for management science and IT have been of interest areas for business schools and computing experts during recent years. Among the areas that are being treated are modern analytics, heterogeneous computing, business intelligence, ERP (enterprise resource planning), and decision science. Consumers have been pledging their love for data visualizations for a while now, and data is the area being explored, such as B2B and EC (E-commerce), E-business and the Intelligent Web, CRM (customer relationship management), infrastructures, and more. The digitization implications of these many new applications are described and explored in this informative volume.
